Learn about past events
Read about workshops, lectures, and other events that have taken place at the India Gateway.
Read about workshops, lectures, and other events that have taken place at the India Gateway.
This three-week in-person program was designed to improve the English language academic and communicative skills of underserved first and second-year students in New Delhi. The goals of this program were to prepare the underserved population of Indian students with academic skills for future exchange opportunities, further study, and employment and strengthen the capacity of local English educators.
This in-person meeting critiqued the draft chapters of the Oxford Handbook of Indian Politics. It was being held under the auspices of a Presidential International Research Grant from the Office of the Vice-President of Research at Indiana University Bloomington, and in collaboration with the Centre for the Advanced Study of India of the University of Pennsylvania, New Delhi.
The focus of this virtual workshop was to help the creative instincts of high school students to explore the design and basic blueprints of combining AI with Human Intelligence (HI). They also learned how to design conversation paths and train their own software bots.
Description of the video:
Styles for high-school students, kilojoules to be kept in mind during the workshop. I can see that most of you being in yourself, if you could add your city name for those, if you haven't added, it would be great. Please keep your microphone on and you can use the raise your hand option when you want to ask questions. I do request that you keep your video on throughout the workshop. Please keep a pen and paper ready if you'd like to take boards during the workshop. And of course be less points are the cells that you will receive a certificate of participation and attending the workshop today. Please note that be those of you that quoting this session, I'm taking shots at, maybe used on our social media pages. Or what to watch out. Professor today. A very warm welcome to Professor Sauer was a faculty at Indiana University, Purdue University, and welcome to this evening's workshop and thank you for joining this session. He has been an educator, administrator and the pandemic flu jab at the campus income levels for more than 29? Yes. Thank You could see. And what do you hope you'll enjoy the workshop? Alright, let me start. I'm going to start by sharing my screen. Okay. It's pleasure for me to be doing this with you guys virtually. And thanks for everybody for also attending. We're going to be talking about bonding. And a subject may be that some of you actually have already may be interested in, or maybe hopefully at the end of this session, you may get interested in. So what we're going to be covering today, we'll talk about what is academies, but what are bonds? What is a cognitive bot? And then we're going to do a little bit introduction to I selected the platform that I'm going to use for you to actually to use, to practice at the same time. So by the end of this session, you should be able to build your first AI bot. And it's going to be in a form of a video button instead of a chat bot. And the difference, of course, is that with the video, but you get to choose what you want your body to look like and you get to choose the voice, you get to choose agender. And you also get to choose at some point if you pursue this later, you get to choose like the type of person, etc. So most of you probably, you talk to bugs, even though we live in an age where sometimes we actually pyramid. There we go. For a minute here my mouse stopped working. We live in an age where actually there is people they're literally use in Boston on and don't even know that they're actually communicating with bots, etc. And here's a fun fact about bots. Okay. There's recent actually report, let's say hundreds of thousands of people. They say good morning to Alexa every day, or you've got 0.5 million people or so that they actually profess that they're in love with Siri. And they've got more than 250 thousand people that literally proposed marriage to a virtual assistant. So you may think of buses actually virtual system that we're using on a daily basis, but it's nothing new because box is something that we've seen that started back in 1966 with the introduction of Eliza. Eliza was actually created, I created to be a conversational bot back before even people, you know, back when, back in the AI ages, in, back in the age of AI when for a, I've actually started back in 60. And then it kind of like, uh, took a, took a back seat for a while. Another another bot that we noted in 995 was Wallace. Okay. Walls of course, is a little bit more fine because you can actually carry a conversation with Wallace. As you see here from this conversation where I can ask you about like things like interesting things about you or you can ask Enter. You can ask her about carry conversation about something that maybe you care about and so forth. So what have changed though, is that because AI has come a huge CAN, made a huge come back. We started to see the rise of bytes to the point like bugs or become an almost the new apps. In fact, they are the new apps in some a, and so many ways because now we're starting to use Bart's in so many different application, whether it's Gaiman or whether it's utility, whether it's actually, how can US. Manage our devices or happiness. Like helping us manage our TVs or happiness manage our personal or other personal mobile devices and so forth. Now, what's interesting about that is that according to actually few, few people that we consider smart people like the CEO of Microsoft, if you want to consider that person smart. But anyway, a bunch of them are saying that bots are going to be the new apps. And what that means is that they're not going to be, bots are now going to be coming in looking like this, right? So we're not talking or it's not going to be about that's going to help you water your plants or do your dishes or bill baggages for you and cetera. Or it's not going to be about, It's going to look like this, although it may do exactly that. In other words, about can actually open an application, can, can read emails, can actually help you respond to e-mails. Can, can also help you. Set up schedule, can help you actually communicate with other people or multiple people the same time and so forth. So that's actually is given Bart's a huge value in the sense of like now we're seeing bars not just used for conversation, but also going beyond that where many companies are racing to use bots to literally X number the production, which means take the, now what one human can produce. You can have a bot that will produce the same as 1000 humans, for example. And so that's a big value now in use and bots and in the real world as far as commercially or foreign the business, because they can reduce costs or they can handle so many different processes in a more standard way. They can also speed up the way things are being done. They can handle the quality much better than humans. Because let's face it, buds are not gonna calling sick. They're not going to ask for a raise. They are also not going to have then they're going to do the same thing specifically at it. Do it over and over again without, without the human error. And also that in many ways does lead to not only better production, but also more compliance for these organizations. They are starting to use them and so forth. Today however, we're going to focus more on conversational bot and cognitive bot specifically. So you may ask yourself a question, okay, what is the cognitive part? This is simply a bar that is actually, and for some people they use this. They call these software robots or software bots. Okay? Now, these are actually nothing but nothing but entities that use machine learning and natural language processing and generating and as well as understanding. So they can handle a conversation and they can also perform tasks. The reason why we call them cognitive biases, because they are capable of learning, because they have built into them. Different learning models that use, again, using machine language, machine learning, and deep learning, and use in conversation driven development to carry on a conversation. Now, many of you, probably like I said, you may be familiar with certain virtual system that be that you have been using in the past or maybe recently you've actually carried on a conversation with your try and for example, you're trying to book, book a trip or you're trying to actually order something, et cetera. And you did have a conversation with a bought at a bar of some sort and above a certain level, as we're gonna see. Now, not all bonds are created equal. We should also note that because there is such thing as good, bads and bad bots, okay? A lot of the chatbots have been used recently. They have been used, for example, for customer service or they have been used for like detecting fraud or they have been used for given people half-steps, including a up to counseling people. In some cases. There's also bad bots that had been used recently. Where literally we've seen bots that raised to the level of steel and an entire election or spreading so much this information that you actually ruin the reputation of a huge organization. Or you can ruin the reputation or the, or the brand of a certain individual and so forth. And a big part of that is because bots Becoming a lot easier to create and also a lot easier to actually, not only to manipulate, but also to, to, to get them to learn more things and to actually also use multiple bots for multiple, multiple purposes. Now, it's also. Fact that bots or become a little bit harder to detect particularly bad bucks. Because in social media we know for a fact there's quite a few bucks or so sophisticated today that you may be talking to you about. And like I said, are not known that you're talking to about because they behave like a human. They sound like humans. And in some cases there are more and more look, looking like a units. And that's what makes actually bought detections a little bit harder. Also the fact they can bots. So when we seen, for example, the 2016 election here in the US, that was literally there was the use of bots to, to mess with the election was a huge thing here internally. I mean here nationally as well as at the international level. Because you have Twitter bots that we're able to get people to follow them. They were Twitter bots. They were, they were able to scrape the web or collect information and push a lot of this information. They can also send messages from realist and behave like Lee said, poses real humans. In fact, they were, but they were created to be literally malicious bots. Now, an example of that was to create a back using the Twitter API Python. And just within a period of only 90 days from being launched, they had thousands and thousands of followers. Why is because they were behaving like literally they were behaving like a human. They will behave like a human. And they were also, they were able to actually mimic the human behavior in what they're, what they were posting and how they were behaving. That of course, led to a lot of, you know, a lot of, most of the bad parts that we're seeing today are more about spread and all this information, which is different than misinformation because it's a deliberate way to descend form or misinformed people. And so we're seeing a lot, for example, a lot of fake news in at some point. It's become an even harder. Now when you add not just conversational bus, but when you add video bots that look and behave like humans, as you see, for example, in and, and deepfake and some of the other technology there, there'll be news. Now, this information is probably one of the, one of the biggest concern up to this point with the malicious bots or bad bugs, particularly when they attack financial institutions, or particularly when they're used as weaponization, as a cultural weaponization war, particularly when they used as corporate to corporate reputation. That's when, of course, the damage becomes more significant. Now, so, so much for bad bots. Let's talk about the good bots and let's talk about how you actually going to be creating your first bot at the end of this session. But before we do that, again, talk about the ease of green, but it has become so easy that you can literally build a bot a whole lot faster than you can build an application. You can also, you know, it takes to build an application or an app. It take maybe 550 people in some cases to build an app and it takes a lot more time and takes a lot of money. Whereas to build a bot than a cognitive bias that can learn and they can functions at different level, does not take a lot, lot of time. They're easy to, easy to change in. You can only have, you can have one person or just a couple of people that build some powerful bots. Now, let's talk about the different levels of bots we started up to probably are just a few years ago. We only had bots. I can only do certain basic level of notification, for example. And what I mean by that is, for example, you say hello. The order may greet you and say, okay, the temperature today is it's going to be this and that. Okay. And that's, that's that. That is the extent. Now we move to where we are today. Look in that first Buster with a chatbots or even cognitive, cognitive bots. In level 2 and level 3 will start to look. We're starting to have bots that can actually do more things and then start to carry more cow conversation. So not just the answer frequently asked questions such as, where do I find this product? Or? Or for example, what was, what is the rating for this restaurant? Or all basic question that you may be asking you, your Siri for example, or your, your, your Alexa. Now, what we're moving toward right now is. Level five in five years. But I think we already there actually with level 4, personalized assistance where we will actually instead of having a Siri or Alexa, which as you all know, these are not created to be your personal assistant, all your virtual assistant, as much as their query as massage that were created for the purpose of either collecting information or learning. Learning from you are learning about you. But they're not, they're not truly are personalized assistance. Now, in probably it's estimated in five years that we will have bots that will be our very own personalize their system. So they can, for example, they can notice that your insurance is about to expire and they can tell you, okay, you're anxious about to expire. Let me help you find let me help you find a new insurance or your your car tag is about to expire. Let me help you with that. And I think in ten years we will get to more total automation of this box that will actually become even more capable with even built-in emotional intelligence to literally talk to us almost like a humans. Now, there may be a scary thought for some people, but that is where we are and that's what probably we have where we are headed. Now, let me stop there for x1. See, raise your hands here or just put something in the chat. Those of you that have actually had. What's your most recent experience with boths, either chat bots or video bots or personal assistant. And let's go to the let's see you guys or you guys are being shy here. You see a couple people in chaperones and let's take a look, okay. Okay. Let me ask you this. Any of you actually were surprise you had a recent conversation and then you realize that you're you're talking to or you're literally carry on a conversation with about. But you didn't realize it right away? I would I would say there are probably many, few of us. Okay. So let's ask Alexa to play a song, okay? Now, let's pick on that. If you ask a listed to play a song, more likely. If you do it right, don't do it right now. But if you'd if all of you did it, you more likely to get something different. Because then Alexa is already gone. I pretty much have no The tops of music that you've listened to before or know the type of use it that you like, because Alexa is already does already have access to information about what music that you've listened to or, or what sounds that you played in the past and so forth. The other thing too is that if you don't, you may get, for example, you, all of you will probably get different answers such as all the way up to like, I don't know what you're asking from I don't know what you're asking to what type of music you want to listen to or what type of song you want to paint, apply, et cetera. And that by the bucket. But that by itself is the, give you the proof that this Alexa is not your is not your own virtual system. And then also the respond. When Alexa does respond, usually, the response may vary from one device to another, but also will vary from one user to another. Alright, so let's talk about, okay, how does this all work? Okay? How does an AI virtual system or an AI bot works? It's all because based on artificial intelligence, using, like I said, using machine learning and deep learning in having access to a natural language processing and natural language generation and also understanding, use an automatic speech recognition. And so in others, in other words, Okay, Most of the, most of the AI platforms or deal with conversational bots, chatbots or video bots. They are pretty much using the same thing as we're going to see here shortly. But generally, the brain behind chatbots is the AI ML, which is basically the artificial intelligence markup language. And that allow a bot, for example, to understand what the user's sayin and then convert what the users sand to something that, that is matched against is match against an answer as we, as we see here shortly. And then, so for example, let's say the boss, say, or you may say hi to about the bot will respond UK with, how are you? You may say great, okay, and then the boss may say, Okay, Good to know. Okay? No. How does the bot know that? Understand that you did say hi. Okay. Because many people do not say high. They may say, for example, Allah, or they may say WhatsApp, or they may say how your them. And so there's, as humans, we have so many different ways we can say hi. Okay, So how would then understand that the user saying hello or that's a greeting from the user. That constitutes literally, that's what referred to as an utterance or what the human says is taken as, or what the human utter must understand. And then for the buyer to understand, of course, you have to train the bot to understand what that what that utterances now in now going to be. We're not going to like give all the 1000 ways of how to say hi to a bug, but rather give few ways or train the bot on understanding what they mean, what they mean the, the, the greetings basically or how the user is saying hello or hi or basic greetings. So in other words, you may just then train the bot on understanding by simply Given few ways of saying hello or a few ways a greeting. And then the bot will learn from that mean and that at some point is going to escape this 775 different ways of understanding a greeting, but also different users are going to, are going to start Greenland about. And then the bot will learn also from different users. So the learning takes place not just from what we train the bot on understanding where the greeting is. In this, in this case, a user trying to greet by saying hello, but also how our different user may say hello or May actually communicate their greeting. And so in conversation then it becomes all about intent. In this case, the intent of what the user that user intend to, intend to say or intend to do, or what the user actually wants once from the bot a, the ones from the body as far as an action from the body, such as, for example, the user may, you know, may ask, Okay, tell me about how much it has. Spend a Starbucks last week, okay. So the intent of the user this point is to get the spending at specifically a star but for the last week, okay? Now, for that, of course, let's say if you, if you build an About that will, that will do that. The first thing that you're going to do is to build a Bach and give that a name. And then, then train the bot on understanding the utterances of the, of the user. Asking for, asking different questions, including valence or ask them for a balance. And that becomes then once the, once the bot is able, is able to respond, that will become an intent fulfillment as we're going to see here shortly. Okay, so in other words, everything is all about an intent from the user, which is means what the user wants to do or wants to know, or wants to get what the user says. In this case, in other users say how much did I spend a Starbucks, okay. And then what the bot will do is to extract an entity from what the user set. So in this example, the user saying, how much did I spend a Starbucks, okay? So what's important here is the Starbucks, which is the vendor, okay? And what's important also is the way the user uttered that, how much do I spend that Starbucks, they could have asked it in different ways. Okay. Now, in order to, for them to understand that the bot is going to take that. And it's going to go through a connector, module. Connector modules, as we're gonna see, Can, can vary from, they can be anything that connects the bot to the user, to send that distance, to send the user utterance through this natural learn and model. And so this machine learning model to get the response back to the user. So in this case, it could be a live chat, it could be a messenger, it could be an email. It could be, it could be so many different, different ways to connect the bot to the machine learning and AI model to send a response back. So once then that response goes through a natural language understanding is converted than two in a way that's in here. The conversion is really nothing but converting that language into vectors are basically into down to literally nothing about ones and zeros, in this case, a way that the machine learning can understand it. And then at that point, okay, we're going to reach out or reach out to an outside source to get the, to fulfill the intent of the user. In this case, asking how much do they spend? It's going to have to reach out to their bank account or, or reach out to where they have their financial financial information in order to respond to that. So it gets a response and then sends it back to the user. And simply, I will say like for example, you have spent $45. So it's really as simple as that and a sense of that. Again, you've got an intent that starts with the user saying hello and then saying, they had now how much do I spend as a Starbucks that the bot then we'll extract an entity from that, that entity. Because maybe, for example, like a phone number, maybe a balance that the user is asking for. Or maybe maybe for example, a name of a person, name of a place, name of a town, et cetera. And then from that, we'll actually, we'll convert that or the, the machine learning model, we'll, we'll convert that to a slot. In this case, it becomes an actual value. And that value is being processed to get, to respond or to fill full the intent of the user. So in other words, it's all about, what's important here is to remember out of this, It's all about using artificial intelligence and sense of using natural language processing and have an access to. Databases are two sources of knowledge or content in order to fulfill the intensively used. Now, most of bot platforms, as we can see, they all pretty much have the same thing in common. So every single platform that you're looking at, that you may look at for building bot. So software bus, whether cognitive or conversational, video bars or even just basic chatbots. They're all going to have a natural language processing model built into them as part of the machine learning and deep learning. And they're going to have a multi-language model which allows us for different languages. So allows you, for example, to get your answer in Spanish instead of English. They also going to have a machine learning engine that does the translation. So the bot can have, can extract the entity or, or extract from the intent of the user. And then many of the new platform that we'll see and also have a sentiment analysis which then make, make actually bought, understand and understand more about our human language in order to respond to, for example, they say, they say, when you say I'm not happy today, okay. So the bar is not going to say, Good to know. Okay? Because if it's equity now that makes that makes it even worse for you that you say, you know, or you, you asked about the bot, ask you how you doing today. I'm doing horrible and the response will be great. So that's, that's, again, that's a funny thing. That should not happen when you have built-in sentiment analyzer, analyzes analysis or analyzer as part of the platform. So let's look at a basic structure here in the process. Suppose for example, you want to build a trading bots and the trade embargo. The first thing you look at Azekah were who are the stakeholders and the straight inbox, okay? In this case you've got, for example, the traders, investors, financial institutions that you need to get information from and so forth. So the first thing again and to, to do in building about is to identify the stakeholders and to identify the role and identify the functions that they want to achieve or the or, or the functions that they contribute to, or the functions that they may impact. Okay, Now next is to identify a platform that you're going to use for degree your box. So if you create, for example, if you use in Microsoft as x2, okay? Microsoft is due. We'll, we'll give you or allows you to use their machine learning model. Also allow you to use their language understanding and generation and, and, and make an intake. And also reaching out to, for example, through APIs, reaching out to different data sources or different database systems and so forth. Now, I should say also that the general AI bot key structure, aside from have in your chat bot dialogue design and aside from heaven, selecting the platform, the dataset, and also the knowledge management is where you would, you would also consider because without actually without some training data and without data sets, you're going to have, you're not going to have a good conversation or you're not going to have a good result from from the bot that you're that you build in. Are you planning to build? Now? It's also it should be noted also that okay, a basic anatomy of a but despite, let's say, I'll get a run through the whole thing here. Let's say human is using. Device such as a smartphone. Okay? And in your smartphone you're asking again, we'll use the same example you're asked and how much to spend on Starbucks, okay. So that is going to go the fact that you say it or the fact that you type it, that's going to have to go through some channels. Like I said, in that channel may be it could be an email or could be me. You may be using Slack or you may be used in Telegram, or you may be used in any other form of any other form of communication challenge to get your message to a bot connector. Which the bot connector then as part of, as part of an AI bot model, we'll take that message and then connect that message to two you bought model where then you, you have a Cognitive API or any other API to understand the message to our, to extract your will, to extract an entity from your intent. In this case, how much they spend a Starbucks, for example. Okay, and then reach out through the API to where the box is going to get that information and then put that information back through the same route, that information back to the same connector and routed through the same channel. And then you get your answer either either by tax. So you get your answer by, if it's an audio about you, it will tell you literally, use an audio. So bottom line again, and I'm going to summarize this box. It's something that's undoubtedly it's something that's that's here to stay. And why I'm saying that? Because like I said, we'll see and we'll see in our entire computing computing environment, as well as computing technology changes from the old way of computing to the new way of computing, which is what I call cognitive computing. And in, many other people started to call this cognitive computing mean. And that instead of the old way where you have, you have an input that goes in. The input can go, can be through your mouse or it can be throw your or you just type in it through a keyboard, et cetera, that goes through the old natural or the old way of processing. And that's basically an operating system of some sort, whether it's Windows or Linux, or whether it's the Mac OS, etc. They're all basically use the same process in terms of use and CPU that they understand. They have an arithmetic logic unit and then have a bunch of controls and use memory and then does the process. And so it spits out something to you in a form of an output that you can see it on, on your monitor screen, et cetera. Know what's happening and what's making then the future of Bots, AI bots and cognitive bots even more, more, more, more so to take over just about everything that we'll be doing in our daily lives, including what we do at home or what we do at school, or what we do in a work environment. The fact that everything becomes pretty much a smart input through natural language. Processing. Meaning you don't, you may not have to type anything. You simply talk to. Talk to a device. That device already have natural language understanding. And they may even have computer vision, for example, where it'll actually recognize, for example, recognize who you are or recognize what you're given, what you're saying. And that goes through the new way of processing. And that's going to be more an artificial intelligence, sort of an operating system. So that makes than the output, makes everything output smart. Okay? So that brings us then to how you're going to be actually getting your hands on the first and the first example of building your building, you first software bot. And for that, like I said, that shows a platform that hopefully is going to be very easy for all of you to follow. And for all of you to also to be able to build your first project here. And in this first project, okay, after we go through this platform, the platform that selected for you guys to use is a CocoaPod friend of mine that it actually had been working with them on, on this AI platform to create different types of software bots that also have built-in persona's or they can behave like more like a human and so forth. So for the purpose of this project, you're going to be able to create your own bot that you are actually asked to to start to come to live in your and then you, you are, you commanded to dangerously. This bot should come in and you get a chance to invite it to our classroom, to the Zoom classroom here. So it will present you to the rest of us as either you bought can be a BFF mean and your best friend. Or it can be one of your parents. So when you bought shows up to our or our meeting, it should identify you, such as saying, hello, I'm, you know, I'm for example, Johnny, I'm mocked as best friend or unmarked as father or mother. And I'm here to tell you something interesting about them. And so this bar should be able to tell us something interesting about you that you don't mind sharing, of course. And also should be able to tell us your favorite thing to do. So for example, you like to play sports, so you like to play music or your, you'd like to travel, et cetera. And also should tell us about your favorite movie. So if I ask her What is marked as favorite movie, I should get the answer exactly that. Okay. Mocked his favorite movie is this. And then tell the rest and tell us or if somebody asked that video bought or you're about to tell us, for example, a joke or riddle, it will tell us and Joe burrito, okay, now, you're, you're actually deliverable for this is going to be before you actually, before you get started on this. And once we go through once we go through I go through training with you on how to use, you know, how to use this AI platform from the very beginning and how to actually build the compensation, etc. At that point. Okay, I'm going to ask you then to design your conversation. And what do I mean by designing compensation? You're going to identify based on, based on this project here you're going to identify the exact components that you're going to use for this video. Back to literally do this for things which has to tell us something interesting about you. Were first introduced to tell us something interesting, tell us your favorite thing to do, and then tell us your favorite movie. And then tell us a joke or tell us a real, okay. And then you'll, we might have enough time for many of you to invite your bot to the Zoom session. And we'll have the conversation with it. Or maybe we may have time to do it for everybody. Hopefully, if not, at least we'll do it for most of you. Now, what do I mean by you build in a design? Here? I'm going to show you a basic design here for what it, what it means to have a framework by design. So a framework by design will literally tell you literally what that But does and how that bar is connected to the user. So in this case, for example, I use a bot for one of my classes or different classes where this bot is capable of actually taken, taken feedback. Feedback by taking input from me as a faculty. Or allow my students to ask questions such as what's in this exam or what? So where do I find the syllabus or what do I, I don't understand this learning activity, etc. Now, that's going through multiple channels so that students can go through different channels, whether they use in, for example, use an email or whether they using Skype or you using any of the other channels or, or Messenger, facebook Messenger, et cetera. And then this, as part of this framework, this bot for example, will reach out to our Indiana University Student Information System, or reach out to a library, reach out to the course management system to fulfill the intent of the user. Asked, for example, do I find the syllabus or what's in exam two, etc. And then using, using this AI platform that I selected for this bar that bought then is, is, is able to fulfill the intent of my students. Okay? Now, I want you also to think about, okay, for your, for your project that I'm asking you to do. Think about a similar a framework that you will put together for this, for you bought that you are about to build here once we go through the platform together. Okay. Now let me stop there for a second and see if you guys have questions and comments at this point. So I will, I'll be going back to posts here to post the parser, the projects and the two parts of the project that you need a complete once we go through the platform together and once you get enough, enough, actually practice for all of you. At some point at the end of this, I'm hoping that everyone of you, like I said, we'll be able to build your first video, but that will do exactly that. So let me stop there for, for some questions or, or comments from you guys before we jump into learning how to use the platform to fulfill this or to complete this project. So let's go to the chat here and see if we have any specific questions from you guys. Okay? So framework, a framework mean and select them. First of all, the first, the first thing that you would select and a framework is again, identify your stakeholders or the users, the groups of users for the buck that you're building. Okay? So in this case, for example, you see my groups of users. Here are the stakeholders. Faculty. It can be faculty and students in a classroom, or it can be students access and this, this bot from home. Okay? The second thing is to identify the target channels that you're going to use. Okay? And, and, and then next is to, is to show the framework that you selected for your buck. In terms of what model or what AI model or what AI platform you're going to use. So for example, the framers that you're looking at. I chose to use a Zoom or Microsoft Azure, which as you see, give me access to vision, speech, as well as natural language, understanding and generation through their Louis model. This also gives you access to other, other functions such as allows you to actually through APIs to reach out to other, to other databases or to other systems or to other applications. And also that, that same frame also does allow for hosting as well as does allow for use in using this with different channels. So here you see in this frame, okay. Your friend does not have to be, like I said, does not have to be this elaborate at this point. This is, this is your first time perhaps and dealing with bugs. So in and construct a new frame, at least if I, if I see that you, you've you've identified your users, identified the type of channels, or you, you show that you have a user's gone through channels and then going through the bot connector and the AI model that supports the bot that. And then also what what database that or what other system or application that you bought my reach two to get to either pull to pull data from or to push data from. This other thing too, as part of the framework is to identify where the bot is going to access data from and where the bot can push data to as part of your framework. Once you have all that identified and then it becomes much easier than to, to build the bot to perform these different tasks around that. So hopefully that answered your questions there. And also I see there's a couple other question here. I'm going to be able to see all the questions here. Since this is kind of you can unmute. You can navigate in and jump in with your question. I'm also going to SR moderator here to help me monitor the chat and then so I don't miss any questions. Okay. So last question which even from just a thought, it's just a Buddhist stores are aspirin and Kashmir need to watch and memory just to one Preferences. See, I wrote some ways. Yes, absolutely, but not Alexa because Alexa is not going to store Alexa only store certain things about you. Notice like if you say if you tell Alexa, remember this, like for example, you can you can do this later on. Okay. Ask Alaska who? Ask? Ask Alexa, for example, who's the fifth president of the US? And then she may give you an answer, right? And then you can tell Alaska, remember that, for example, Obama at the fifth president, it won't do that, I guess so in other words, is not going to want remember that? Whereas if you build in your own virtual virtual system using a bot framework and use an About Mao. You can have, you can have, remember what you've seen or you can have learned from, from what you say. And that's, again, and that's the, that's what's so cool about building software bots these days. So like I said, we're getting to the point where we can have our own virtual assistant that will remember what we tell them to remember. Instead of Alexa or Siri that only remembers what it was programmed to remember. So while they do remember, for example, your passwords or you remember other things, that's because they were programmed to do that. But they don't they are not they're not actually trained or program to remember things that you We asked them randomly to remember, such as okay, remember my address. If you simply say I remember my address to Alexa or Siri, you're going to get all kind of garbage or you're going to get all kind of different answer anyone remember? Now the next question here. Yeah. Yeah, Google Assistant is a robot when it comes to money as well. Again, because the Google Assistant is not, it was not built to be your, your, your personal virtual system. And so what we'll see is that while this, while this virtual system also are capable of learning, but all the learning they are programmed to learn is again, not, not for us specifically or individually. It is based on so many other things that applies to either groups of peoples or applies to certain, certain groups of people or apply to everybody in some cases we say. So. That's why you get like all kind of different crazy things. When you ask Siri or Alexa, Does that make sense? Yeah. Nsaid drains more battery and we're certainly okay. What's the most difficult part to make an AI? Okay? Now, very interesting question, but okay. To do. What do you mean by making an AI? Is Jim in building, building the whole AI entity or building an AI model. Or, or simply building or building like a software bug that we're talking about. If you're talking about building an AI entity, okay, The most difficult part is to identify the type of training data that you're going to have this AI model learn with. In this case, we're talking about neural networks and setting up neural networks using machine learning and deep learning. In that's the platform that allows then this AI entity to learn. So starting with the training data and then of course, the better the training data, then the better the AI model is going to learn. And that's why you hear things about, for example, like previously. So someone said, the Google get and you get junk or when you get crazy things from, from some of these some of these AI entities include an Alexa or Siri. Okay, That's because the big part of that is the training data rate and also the type of data that's used and the type of data that's that that entity has access to. So that is the toughest part is the training data and how clean that training data is that will lead to learning. So for example, let's say we're building an AI entity that's going to help an autonomous car drivers a scar, recognize rock, and a cat that recognize the difference between a rock and a cat. Again, now in order to have an AI entity as part of, as part of driverless car, recognize a cat and in Iraq. And then you have to provide it, for example, with so many different, so many different pictures of Iraq, so many different pictures of a cat, so many different different actually a description of a cat and a rock. And then, and then have that training model then go through, go through different iteration within this. In this case, we're talking about a neural network, right? And then to the point where then it gets, it gets very close. It's not going to be a 100 percent. It's never going to be a 100 percent unless maybe down in the future. We're then that AI entity is going to be able to recognize that this is a cat and then this is a rock. So while they may go over the rock, it will avoid hitting the cat. Okay? Or for example, recognizing other objects or recognize and even recognizing people, for example. Okay. That's the same thing too. So it's based on the type of training data that you provide. The AI, the AI, the AI system or the AI model. To, to, to learn on how to recognize, for example, you from your twin brother, are you from somebody else? Okay, So how can we be certain that any part is not a threat to our privacy, dignity, or safety. Very interesting, we can't, we cannot be sure that, for example, again, the same thing about Alexa, Siri and some of the others. Okay? You've heard some horror story where like for example, like some maybe less than all the time or even Siri is less than all the time. And sometimes even haha, you have AI bots or you have bots in some other devices such as it could be. It could be in the simple things such as a TV for example. Okay. Hiv could have a software bought that may be listening all the time. And yes, that is actually when it comes to privacy and safety, that is always a risk. And that's, that's probably one of the biggest problem also by using software bots and using AI entities in different devices. A weekend. Or we're not going to be able to literally eliminate all these bad bots out there. Because it's dust, just a fact of life. And that's just the fact that you have, you still going to have people, that you still going to have people or even entity, not just necessarily people, including up to some organizations are even or even governments for that matter that would use software bots or that we use bots for their own interests. Meaning if they wanted to spy on you or if they wanted to. They wanted to actually learn something about you or learn something, or learn something from you for that matter. So that's, that risk is always going to be there. Unless we get so sophisticated building bath, they catch bad bots. Something that I discussed in some of my classes. You know, at some point I think we're also, we're entering an age where we're going to need almost like software bus that play the role of cups, okay? Or, or, or policing for example. And what we've seen in social media or the craziness and social media, okay, we still continue to see a lot of craziness and social media. That's because we don't have we don't have AI bots are smart enough to monitor or to police social media conversation, or even to ensure that your your safety or your dignity or or your your privacy is now compromised. Does that make sense? All right. So a couple more questions and then we'll get into how you're going to build your first spot. So what commands, instructions are important to create a video, but you can know the commands and instructions are going to vary. The function of that you want the bot to accomplish. And also is going to vary on the top of a platform that you're using. Okay? As we're going to see with the platform the selected for this workshop, you'll see that your only have certain, for example, certain sets of commands or certain sets of components. Now you can build your own components to add to that may be mean and you can build your own commands. But again, these commands are, these components will vary dependent on what do you need to do or how do you need to respond to the different users. So due to privacy concerns, should there be should there not some guarantee that information stored will not be shared? Yes, a good point there. And that's why we see a lot of push and because this is something relatively, although, like I said, birds have existed since 19, since the 60s. Okay. But we didn't have the same technology that we have today. Where you can have, you can have bads. The ability of a software bus day is almost infinite mean. And again, that's the thing about artificial intelligence for us, for example, for us humans, it's okay. Intelligence is how we process and analyze information. Now, artificial intelligence is the use of any technology. And what I mean by any technology, it could be it could be a software bought, it could be a programmer, could be something else. At some point, it could be even a mechanical, mechanical entity in the form of a robot. That's got, that's got the ability to process information. That's what makes, that's what, that's basically the basic definition of artificial intelligence. So a technology that can process, analyze information back and reason. Almost like humans. Now, what that means is that, okay, That's something that's relatively then, that's that's growing and that's morphing and changing every day. New. And many of the laws and many of the legislations are behind. So this is why we're seeing, for example, things like the RS hers ask and when in terms of privacy or in terms of the even the shared information or should be shared, what should be not, etc. That's still pretty much still up and it is still being debated. There's there's not enough actually, the order let me put it this way. There's not current laws and regulations when it comes to the use of AI entities and the use of AI entities as software bots or as cognitive bots. How secure are bonds that store or personal information? Is there a way to ensure there is not misused? There's not really a way to ensure that it's not misuse. Biggest case in point, for example, all the stuff that these bars are learning from you, either through Facebook or through other social media. Guess what that information is. Actually ISBN, either monetize or be in use, are being sold, are being traded, et cetera. That's just so after this point, like I said, we don't have a specific I'm Alice, I'm talking about here in the US and maybe a little bit different in India. And this is going to vary from one government to another. In not just federal government there maybe even a state government like we have around us. But we don't have yet clear rules and regulation when it comes to the misuse of information other than basic attacks. So we still continue to see companies that literally use, use the software bots together information and then to trade it out, to sell it or to use it. Yes, it does. And it's very much similar to HTML because it's a markup language. For a either the question that was asked, what is the most widely use Kelvin language for AI? Excellent question, I like that. Okay, the most widely used language that I hope some of you, they're actually thinking about a future in AI. For thinking about actually learning how to, how to, how to either build software bots or hobby, or how to design software bugs. Okay? You will have to, you'll have to learn the basics behind machine learning and the languages. Most usually in machine learning these days is Python. So I recommend that you start looking at Python seriously. Now Python, the reason why Python is also is a good language for the AI models that we'll see and particularly in machine learning. It's also, it's becoming more than de facto of data science is a very good language and easy language to read, not just, just to compile. So sad, yeah, for me outside Python. No. Entity. Tp, what do you mean by entity? Or you ask and what is an entity? And the next question that we're asked to do. Okay. An entity? Yeah. Okay. And entities, what about extracts from two from the intent of the user? As we're going to see here in the model that we're going to use, okay? In other words, an entity will become the action that the bot will fulfill. Two, O two will perform to fulfill the intent of the user. So for example, if you ask and where can I find? Where can I find a good restaurant, okay. Or where can I find this piece of information? Okay. Now that's your intent. Now the entity becomes for the bot to extract good information or bad to extract. For example, good restaurant, okay. It's based on that. Then we'll perform, will actually go through, go through the AI model to come back to fulfill that. Your, your utterance of where do I find out? What is it that restaurants are? Where do I find a good restaurant? Yeah, neural ink is an example of using AI is an AI application. Is it possible to make a centralized bought Store? Absolutely. Yeah. Yeah, it is possible to have an n factor. There's been several attempts at doing that. And if you look at different AI models for bots, you will have very much that most of AI models that offer software bots and cognitive bugs do actually have examples that you can take and customize. As we're gonna see from the model that I had selected for this, for this class or for this workshop. Alright, the rise of cyber warfare, bads get more and more sophisticated. Can the role of bots in cyberwarfare pose a serious threat? Big, big yes to that. Absolutely. In fact, what we're talking about these days is that software bots, again, is can actually be used to launch different types of attacks. Okay? Whether it's a misinformation attack, whether it's a denial of service attack, whether it's whether it's even an attack on an infrastructure, et cetera. So yes, software bots can be used to launch cyber attacks or even to carry a cyber attack or to propagate cyber attacks. Scary thought, right? But that is again, that's a reality that we live in. We live in today. I like the next question there is then this bar concept. We create unemployment as the companies would go for a patent. But as that is, that is what's happening today. So we RC and because many companies, okay, they're pretty much true race and to create a digital workforce. And what I mean by digital workforce is literally a workforce that is done of work, that is done by software bots. Okay, so naturally that is going to replace some jobs. But by the same token, that, that itself is creating more jobs because bots also need to be monitor. Awesome. Bots also need, need to be, need to be taught how to perform tasks. And also need to actually need to be tweaked once the process does change. So while maybe in our people that perform certain tasks such as handling customer service or example. Now you can have about that handle customer service. But if that bought the handle customer service, you had let's say you have three employees that were handling your customer service. You can replace all three employees with only one, but that does the job of three and even more. So now you have about the handle, your customer service, and you don't need these three people. Okay? Well, what if that, but actually, at this point that Bob was not taught how to handle certain, certain actually circumstance as well or, or learn from learn how to actually offend customers instead of, instead of actually handle customers, right? And then you go from, you know, you go from like upsetting few, a few customers in this case will be three, because you have three people that may upset three customers. You go to a bot, they can handle thousands of customers, and that same Batman will upset a hundreds of customers instead. So then the new job that may be created or will be created instead of, instead of the human handling the customer service, the human is making sure that the bot is learn in the proper way to handle customer service and also to follow the right processes to address customers. Does that make sense? So then you have a new job that was created, which then someone that knows how to handle customer service very well now their job is helping the bot learn how to handle customer service and also staying on track. As far as not piss enough, customers are not upsetting customers and also respond in the right way, et cetera. Does that make sense? So yes, there'll be some loss of jobs, but also there'll be other jobs are created as a result of that. So the root of the dialogue, that's also a good question that we're going to get into here shortly when we start talking about the platform that I've selected for you guys to use. Okay? The root of the dialogue is, is, this is all the bugs in our dialogue is above conversation. A conversation between a human and between an AI software block or an entity of some sort. In this case, let's call it an AI, a virtual assistant, okay, or simply as a software bug. Okay? Now the dialogue will consist of what the, what the human says and how the, how the, the, the bot will understand what the human says in order to respond to the human. And then this dialogue is going to result in two things. Either the dialogue is going to the bottom. We'll understand what the, the utterance of the human and then can carry on the conversation or come to an end or simply may understand actually that. For example, when you have when you have a conversation that's not going anywhere with the bot has gained confuse or maybe the human is become and start to say, say all kind of crappy things or inappropriate things, I can. That then at that point, of course, that the dialogue will, will end or the conversational end. So do I believe the concept of robots do in our daily tasks will improve our livelihood or in fact worsen it. I happen to believe that it will help okay. To give you an idea. Okay. Right now, as you all know, okay. We all are dealing with the Internet of Things. And the Internet of Things is simply extreme connectedness. That means anything that can be connected, is already connected or will be connected. So that means all the technology that we use, okay? And what I mean by technology, not just computers and smartphones, etc. I mean, the shoes, for example, shoes is a form of technology. Choose, at some point will be connected. In their shoes are already connected. Again. Your toothbrush will be connected. Your pot maybe connected. So you know, so it cooks to the right temperature or your refrigerator as many fresh eggs refrigerators are connected these days is a so when you have that many connected technology at home or, or used, or being used by you. It's only a matter of time that we actually, that we need either an AI entity or even, or even a robot for that matter. A robot that can actually, for example, handled everything that you have at home, okay? They handled it can the extreme connectedness of your home, as well as the things that you do such as or use such as your car and your bicycle or your other things that use at home such as your TV, etc. So the fact that we live in an, in an extreme connected world and that's, it gets more and more can I connected? And the fact that we're adding more intelligence to the connected, to the connect to our connected world. Mean unlike now we have smart toothbrush that can tell you, for example, that can sense that you have a cavity or a sense that something is going wrong with your teeth and alert, alert, you are alert you Dr. You have a smart fridge aerator that can actually tell you this stuff is about to go bad or this stuff is, are you loan eggs? Are you allowing this or that, et cetera? And then even placed the order for you directly, etc. All these, all these different things makes then the use of AI entity or even the use of robots. In some cases, many of us are using robots at home, typically in our carpet or to clean our floors, etc. Or we may be using other software robots, software bots in this case, because robots can be into, that can be mechanical, but they can also be in a form of software, in the form of a bat, okay? And foremost, the software. A software robot will allow you to manage all your connected devices. So it allows you to turn on your car and set the temperature for you. Set your set your route, identify a better route if the traffic is going to be bad and so forth, okay? Whereas a mechanical robot may clean your carpet, may actually, and if you get more sophisticated for those that can afford better robots taking, you know, that there's people that have robots that do other things such as fatty things or or maintain the security of their home or whatever the case. So that's a good question. Can boss we design with fully autonomous capability in order to be use for missions like keep space exploration. Very much so, absolutely. Okay. Bots can be designed to be at the autonomists. Because cognitive bots and the sophistication of cognitive biases that are built today, okay, are capable of learning, of non assisted learning. Okay? So meaning that in a, with machine learning and deep learning, we started with us having to, having to actually supervise the learning and also monitor, monitor the learning or help, or help this AI entities with the learning. Now we're at the point where we can have autonomous software bus. They can also learn on their own and then continue on learning. Now as, as I said earlier, I can, when it comes to artificial intelligence, okay, we, as humans, we can only process this much or we can only reason this much. Whereas for AI entity that the amount of information they can process and the amount of information they can reason and they can synthesized is infinite. And that's therefore, if you, for example, if you have an AI entity that's set to infinite loop of learning, it'll just going to continue on learning. And to the point where again, it becomes at some point the fact that we talk about super, for example, Superintelligence, That's very, that's bound to happen at some point for that very same reason mean and that AI entities have the, have the opportunity to be on infinite learning loop. N, Since we have infinite amounts of ones and zeros or infinite amounts of information, they can process. That. They just, they can continue to get smarter and smarter autonomously as well. Good question there. So do we need to learn Python to create an AI bot? No, we don't. Okay. You don't need to learn Python. You can actually, as the example that we're going to be going through here shortly. Be able to build your own bar without even knowing any coding or known any Python. So there are multiple models of AI that allow you to build your own software but without no encoding, know, it's helpful if you know coding because then you can actually, you can customize these bots for you can build your own bot from scratch by now in Python. Is there any possibility to the fact that employing balls and a non-core, core activities of human activities reduce human effort to 0 and future. Will the concept of human effort even exist in the days to come? Excellent question. I think sometimes we, we actually go or I do go over that and some of my classes as well. When it comes to that. Because like I said, when you have an entity that is program for infinite learning with access to infinite information. At some point in the question is that, does that mean that the human value, human intelligence will be devaluate it or will go way in relationship to the AI intelligence? My answer to that is not, okay. We're not going to see the human intelligence be evaluated or the human be reduced to 0. Because still, the intelligent analysis that also humans are capable of doing is not something that, you know what I mean? Intelligent analysis. So that's a, instead of artificial intelligence, that's only something the human can, can, can actually perform. An intelligent analysis is about understanding. For example, let's say you build an app. Understand that if you're going to be building this app, this app is going to have multiple, actually multiple, multiple parameters and also multiple effect and impact, etc. So this app, okay, for example, needs to consider social factors, needs to consider ethical things. What is right, what is wrong? Needs to consider, for example, the type of users and what they like and what they don't like, needs to consider what someone sees as beautiful versus what someone may see as not beautiful. So many different factors, so many different human factors. The only human can, can actually construct or can, or can build into, into a technology by this intelligence analysis. That's why the humans and the humans are not going to be replaced. Unless we get to the point where AI entities can do that as well. Okay, which I don't think is going to happen, at least not in our lifetime. For an AR entity to develop, for example, for conscious to understand what's right and what's wrong. And you can teach at the regulation. But regulation does not cover every single instance of ethics, okay? Or everything, or everything. This, of what is good for certain people and what is bad for certain people or what is, what is proper, what is not, and so forth. Does that make sense? So in the days to come, the human intelligence is not going to be evaluated by AI intelligence. So intelligent analysis is still something that only humans can do. Take it by taking into account all the different human factors from conscience to, to spirituality to affix to, to, to, to human design and so forth. So is a Zoom live transcript. Jim, in R. For that question is the Zoom live transcript I bought a you ask an F, This is going to be transcribed. Next question. Okay. We are seeing some big companies like Google, Microsoft, and merit dominating the Internet sector. Doesn't that defeat the whole purpose of Internet, which was created to provide an establishment or decentralization. And now that we know that these companies are going to create and plots which will change our lifestyle. How can we, how can we go about that? Okay? Another factor, another fact of life, okay. Or another something that's, that's out there that we have to deal with. Again, these giant companies because they have the resources to create AI entities. And whether you know, whether we're talking about a multiverse or whether we're talking about the Google Alexa, or whether we're talking about when we're talking about the Microsoft software bots or talking about IBM for example, Watson software bots and AI entities, etc. I think this is just something that bags, bags. The questions, when will, when will they actually when that, when will there be standards, either international standards or at least national standards and national regulation that will help us as consumers. So we don't fall victim to this. Ai. Entities are created, created by Google, Microsoft, and, and alike. So until that happens, I'm afraid we're, we're pretty much at the mercy of this, this giant companies that they are racing to create AI and even super intelligent AI. Could be used to make satellites lose their orbits. Absolutely. Yeah. Don't try it. But what language will, will, will we use in future if we are going for lifo voice commands? That is an excellent question because in language there are many words, okay? A word, they have the same way. Same them, okay? Now, the fact that we're getting very close now to create software bots. They can understand The human language very well, as well as generate human language very well. And as well as actually as well as prompts, process the human language very well. We are very close to the point where languages, as we know today. And here I'm talking about programming languages will probably cease to exist, at least in a format that we haven't today. So at some point, it does not matter whether, you know whether it's Python or C sharp or C plus, plus or IRA, or whether it's R or whether it's whatever these languages. We will be able to actually, we will be able to train AI bots to do programming for us just like you train your puppy or trade train your dog. Okay. Which is something that many of us can't wait to get there. Not to do away with the jobs are programmers. Because programmers jobs is not going to go away. Then it's going to come to that intelligent analysis that can be done by human to follow, to create a logic, to perform tasks, or two. To create the logic. Transfer that logic to an entity that will build, then build the program to perform these different tasks. Does that make sense? So in other words, Okay, our jobs or the future Java programmers is not going to be syntax is not going to be like how well, you know Python, the syntax of Python or R, or R or any of the other languages. But rather, how well can you do intelligent analysis to create the logic and to create, and to also communicate the right steps. And what are the entities that, that will, that can be extracted to fulfill? In order to fulfill again, either to perform certain tasks or to fulfill what they, what us as humans are ask and ask. And four, does that make sense? So yeah. So how long does the implementation of chat bot takes? Not very long. It doesn't take very long to implement your chatbot, as we're going to see here, all of you will be able to create your own chatbot, except that it's going to be more than Judge chatbot. It's going to be an actual video about that. Can you can talk to you as it as your I'm talking to you or you may be talking to me. So just a thought. Would this came from IU logo? Okay. Would you like to check the remaining question towards the end of the session? Absolutely. Okay. Let's do that so we can jump into. All right, so that's why knowing the South during the battle. So some remaining questions, I just make sure that we answer that question. All right. So yeah. If you would help me then get all the questions that I don't get to your questions during this session because I do like to get to us doing some as actually practice in how you're gonna build you bought and then get new to build your bot and then communicate with your, with your back during this session. So let's jump to that rates and let's save your question to the end and we'll get started here with our first meeting, the components. And so before we do that, I want you guys to follow along. So I want you to go to let me put this, I'm going to put here this. Go to cocoa hub, that AI. And it's going to ask you, this is actually decide that I want you guys to go to the cocoa hub, that AI, and to be able to use this platform for today to build your bot is simply going to ask you for that guest are in fact, I'll do that real quick so you guys can follow. So it's cocoa hub that AI will take you to this screen. And then here I want you just to see if you click just start now, okay. Is simply going to ask you for an email address and a password to continue. Okay? So if you enter an email address to that, and so let me let me use a different account there since I already have their account. So I'm just going to use already have an account cells is going to be there. Okay. So once you guys actually get inside the platform, once you you enjoy password and e-mail, you should be looking at pretty much what I'm looking at right now. Okay, so we're going to start creating a conversation now before we, before we do that, okay, I'm going to talk about generally about this platform. This is a platform that actually use already have built-in components. Now built-in components is literally, in fact, let me, so you start with, let's call this, let's call this My bad. Okay. So within this platform, like I said, you have components. And components is literally something that was already built there and that's already built for you. So for example, how to get mail, how to get somebody's mail or how to ask for somebody's name, etc. So this particular platform has got these components built-in, which literally they are actually in the form of, in a form of entity already that, that fulfill certain things such as, for example, a user is asking. Now, let's go down here. For example, a user wants to talk about Thanksgiving, Okay, well there's a component that's built there and so forth. So the beauty about this platform is like I said, it's got already these components. So what we're going to be doing here today is to learn how to use this platform to build. The video about that I asked you to build, to bring into the class, to ask to come to this class, to present to you and also to tell us something interesting about, about you, et cetera. So we're going to start from the very beginning here. In this particular platform, everything starts with, this is the first thing. Anything that is connected to that that would be, that would be the start of this of this spot. So in terms of components, okay, things, what I want you to actually to talk about now at this point is that you've got components that starts, starts with say, Which means what you want the bot to say. Ok, so that's actually the bot saying something to the user. And then you can capture what the users sand in a form of input. Or you can capture what the user saying in form, in the form of an intent. Again, navigate. The component is allow you to actually kind of pose. So the bot can pause to, to listen to what the user is saying or get the input from the user, what the user is. Stipend basically the users and tap, Okay? And then we can customize any of these, any of these components as we're going to see. Now first, before we do that, let's talk about, you know, perfect things and say things what to do, what's not. Okay. You always want to stay within, within the tweets length amine and like you don't want the bot to say a lot of texts like say for example, Hi, I'm so, and so I do this, not do that. And it's a very long thing. We want to keep your say to a very minimum. And to make it also sounds very, very human-like. Okay. You can also, what do you need to do with your conversation? Somebody asked me earlier about the dialogue and conversation. A good conversation is the one that where does not say a lot, but say something very specific, very clear, very concise. But also the bot say something where the questions are also clear and mix different kinds of questions. And also whether the questions have been asked to the user or whether that's something that's being passed back to the user, that it must be clear and focus. And that has led also have a consistent personality. So if you bought is you can have, for example, an angry birds that would say crazy things. Or you can have, okay, or if you're a person may actually simulate or emulate your personality. So you'd have to be careful on the type of the type of conversation that you build with your butt when you're talking about the different types of personality. As long of course as you're consistent. You also want to avoid unwanted dance. Now, a dead end is where what happened with the conversation, when the conversation stops. When or when the bot is confused or when, for example, something may happen that's completely, that's completely unexpected, Okay? You also want to embrace hooks and then t-shirt. So you want to, you want you bought to actually have seen certain teasers or so, or things that makes you bought humor have a sensor. At least a sense of humor and a sense that makes the conversation or dialogue more human-like. Things that you should not do in your dialogue or conversation. You don't want to throw heaps of tax at once. Like again, throw a lot of stuff. You don't want to ask questions. They're only yes or no questions. Unless you need to specific yes or no. And also prompts what you can deliver. You can't say this, but it's going to do this and this and that and when in fact it does not. You can be too open ended because two open-ended may actually break the path or break the dialogue or break the conversation. In your so you can assume you uses will be nice. So in this case, you bought must have a way to, for the bug to end the conversation. If the user is not nice or user become belligerent, or the user may say something completely inappropriate, et cetera. And you don't want to apologize in mundane way. So in your dialogue or conversation, you don't need to be up apologizing. And that meant mundane way. And you don't want to include empty prompts. And also you don't want to also to leave unintended dead ends because that will break your conversation. Now, how to expects user inputs? A guy, like I said earlier, your user inputs is going to be based on the intent or the utterance of the user, what the user thinks, what the user means, what the user want to say, or what the user wants to talk about are what the user choose to convey and so forth. Okay? And from that, okay, then in this particular platform as it is and so many others, okay, the bot is going to learn the basic behind these phrases. And you can learn the basic behind these phrases through the machine-learning. And at some point there's always going to be some error in our, some margin of error with the machine-learning. So that means that a machine learning, even with deep learning included in it. And some of this platform, that doesn't mean that the answer is going to be always correct or that the bot is going to understand everything a 100 percent. Okay? And that's why sometimes we'll then you may be using keywords there specific instead of, instead of an entire phrase. Okay? Like for example, you know, like with with users saying that, saying the same thing in a different way? No. As far as the conversation that was asked earlier in the dialogue, again, let's say, okay, the conversation starts with what is your name? Okay, The bot ask you, say hello, say hi and say what's your name? Okay? Now the user is going to cooperate and the dialogue is going to go this way. So it's, the dialogue is going to go with the user, say, okay, say their name because they cooperated. And then the bot will verify name and that's it. So the goal here is achieved. So you come to an end of that dialogue. Or if that piece of conversation, if the user does not cooperate. Okay, there's two ways here we can go, okay, we can ask the user again. Let's say you ask the user what is the name? And the user say dog. Okay? Well, I'm sure the name is not dog, right? So you then you want to convince the user, say so you would say, Oh, yeah, You're joking, right? I'm only asking, give me give me a correct name. What is your name? Roll it. So you try to convince the user than to give you the right name. So if the user say something such as, you know, they may say piss off, then that's a, that's a reason to stop the dialogue right there, which means the goal was not achieved. And then the button, then we'll understand that this is a failing point in a conversation or dialogue. And the dialogue Mr. end or the user may, at that point becomes co-operative and then give you, instead of saying My name is Doug, they'll give you say my name is John. Okay. Are My name is mocked our fuzzy or whatever. Does that make sense? Alright. So that's the way that this conversation is going to continue or the dialogue continue. What we call and the borrowing world, we call that a path or a happy path. Happy path, as we're going to see here shortly, is when, and then go ahead and get started here. So right. So let's say our first thing, okay? And you follow, If you follow through with me, we're going to start with a say, Okay? And let's say the ball is going to say, hi, Okay. I'm your bot. How how can I help you? Okay, So let's test that. Type anything to get started. So I'll say, hi, I am your bad. How can I help you? Okay. No notice at this point That's a conversation is not going anywhere anyway because the bot already filled, already actually made the expression. But here, this is this because the path breaks right here. So at this point this is not a happy path again. So let's say, okay, we want to ask, we want the bot to ask for a name, okay? We'll say, but let first can type very well here. First, what is your name? Type, anything to get started? Hi, I'm your Bot. How can I help you? But first, what is your name? Okay, So here, okay. We'll add, let's hype anything to get started. Let's stop there for a second. Okay? So here we're going to then make the, continue with this dialogue. Okay? And we're going to say, okay, we want the bot to pick up the name that the user will say their name. Okay, Now, in this particular platform, this is where we actually have. Utilities are tools that you can use the getName or to save input. Let's start with the same input. Okay? So we're going to add a few fallen through here. You can be doing the same thing here. Okay? So we're going to add a little pause there for this bot. And then we're going to, the user, then is going to say their name. Now, if they say their name, we want to capture that as a value equal to name. Okay? And let's then we'll save that. And we test anything to get started. Hi, I'm your Bot. How can I help you? But first, what is your name? So I can say My name is fuzzy. Okay. Now, notice at this point, okay, conversation again has ended because we don't have a happy path because once the bot now it's got the name, okay? But what comes next? So what I want you to get out of this activity here is that it's all about the Congress sick build in the conversation. Keeping in mind that you have to have a happy path. And happy path, Meaning know that the, the sorry, yeah, I I pulled my my screen down so I can see my larger screen. Okay. While I'm working on, on my larger screen, I do realize that my camera is pointing down. Okay. So we then a happy path, meaning that whereas you get understanding the, the utterance of the user and then where to go to next. If at any point there is a breakage or the happy path breaks, that becomes and happy path. Or for example, the bot does not know where to go. Let's say, for example, at this point. Now we experience with what you want them to say, okay, and the users talent their name. So how about now we add another, Let's add another, another say, type anything to get started? This for a second there. Notice that with this particular platform, it's very easy to actually test what you're doing and tasks you bought at the same time that you build in it. Which is a very good thing that make this platform also very visuals. And you can follow your path because again, these connectors that you can also take out at any point. So I can go directly from, for example, from here. I can go directly from here and, and say, Okay, hello there. Okay. Type anything to get started. Hi, I am your Bot. How can I help you? But first, what is your name? Hello there. You say. So in other words, because I dive in managing the Get Started, type anything to get started, let's stop the test in there. Okay? So in other words, keep in mind that you're happy path depends on these connectors connecting what the boy, what the set connected, what the user is done as say, or the navigation, which means what you want. What you want actually the next task to be. As we're going to see here, you can have different tasks within a navigation. Navigation is, it's going to allow you to, for example, add intent. So if we click on this, you can, there's so many different intact. So for example, there's some that are already built in. Some of them are actually built in there. Myself and some of the others that contributed to this. Okay? Like for example, I built this one here that talks about personal brand. Okay? So if you want the user to say something about what is a personal brand, you would select that, or you can simply create your own, your own, actually intact. Now, an intent is, could be things that you want the user or not you want the user to, user may say, and you want the bot to understand. So at this point, an intent can be in a form of an actual plain English, okay? Or it can be in a form of literally keywords. And we don't see that here shortly. So let's, let's add first, let's add to this path to make this path, this path better. So now, remember here what I said about this. Now we have a value that's stored in there that captured what the user said, what their name is, okay? And so if you want to address that user by their name at this point, the user may be anybody, but the user said their name and it was captured as a value. Okay, that's, that's that's associated with the word name. Okay, so if we want the bot then to address the user by their name. And then we will use the context and the variable that we called name. And how can I help you? So at this point, I will simply just delete that just to make the conversation a little bit about ourselves. And then let's connect this here, okay? And so now we, we have, we have a better path in the sense that the user is going to out or something that's equal to their name. And then the bot is going to start responding to them with their name. So let's test that real quick. Type anything to get started. Hi, I am your bot. First. What is your name? Hello, fuzzy. How can I help you? Okay? Now you see at this point, okay, so we've got still our path. Does and the, the, the bought did fulfill my, my intent. When I, as I said, height and then also gave it gave it a name, given, gave my name. So the bat from this point is going to start address and meet by this value. Because if you look at C up to this point right here, you see you've got what's being built at that point as the bot is capturing the name. Then over here you see that then the name is equal to fuzzy because as a user I uttered my name is fuzzy or a type, my name is fuzzy. Okay. So let's go ahead and give all of you actually just a, a quick, a quick actually five minister to practice this. So I want you to start, start a new bot. Okay? And again, just to start that, you're gonna go to the builder. Let's go through the process again. So you go through the builder, you give it give you borrow name, okay. And then you get started. So the one that I just created right now, let's go back to that. I call the My bots. So I want you to build just a couple of things here. So you're going to, you're going to have you bought greet, greet us with the name that you give it. And then have you bought, capture your name using the same input. And then once everybody's got and then have the bar also respond using then from this point on, using the name. And then we can move on to something else a little bit more, more advance to get to the point where you're going to be able to build your entire video about. So let me give you guys just about let's say see how we doing on time. I would say ten minutes to practice this first part. And at any point in this time, if you have questions or if you're not if you're not able to follow, just raise your raise your question or just let me know. Yeah, go ahead guys, your questions in the chat box. Okay, So how to create a transition, for example, okay? You create a transition by adding another component, whether it's a component that is selects that's already in this model, that's built in already, or a component that you create, okay? By adding an intent or by adding. So when you click here, outside, in Canvas, you have all these different components. Or you can also find components. Like for example, you can say later on we're talking about say frequently asked questions, for example, FAQ. So you can ask, there's, there's actually, there's a component that's already built, therefore, asking questions. So you can use that component. You can also take a component and customize it as we're going to see here. So you can take this for example. And when you crack, when you right-click on that, you can customize these components and that becomes your own component that you make. You can take, make changes to. And we're going to do is, we're going to see that here shortly. And feminist wants everybody had a chance to practice this very first. Startup. Components also, notice that with components you can modify them or you can delete them. You can duplicate components. So if you have different save an input, you can duplicate that. You can duplicate the size and then go in there and change it. You can also copy nodes. You can also start from here. So if you want your bot directly to start for example, from over here, where it says, skip all these three and says, Because that's what you want to test right now. You want to test from this last say. And then you can move the salt. So simply right-click on that component here and say start here. So if I do start here and end now, the hype, anything to get started, the stock will move to there. Hello dollar, contacts, dot name. How can I help you? Okay, no notice there. When I started there, it's saying hello contexts, that name because I did, my, the path here did not take, did not go through saving the input, asking the user for their name. So it jumped right into that set. So that's just there. We'll just another way to demonstrate that you can, you can, you can start. Let's get rid of this one right here. Type anything to get started. You can start from any component or any node that you have in there. So let's go back there. All right? Okay. Hopefully everybody had a chance here to just follow through with that. And then we're ready to go on to the next, the next next thing in this, again, The next here is to actually find and customize components, okay? Now, within this, actually this platform as it is, and so many other platforms again, you can actually take a component and customize it. So if we go back to here, let's say, let's use the getName, okay? So instead of, in this case, okay, instead of save and I'm going to actually delete this component. And instead of, instead of saving the name, I want to actually use something that getName. So I'm going to use a built-in component and customize that. Okay? And many of you actually will end up doing this for your extra, for your project to make it a little bit better there. Alright, so let's connect this. And I'm going to say when it's done, we're going to go over here. Okay? Now, if I wanted to customize this, I would give that a different name. So let's say I'll simply call them my name. Now, anytime you're customizing somethin, okay, you're going to be able to actually edit. You'll be able to view the actual JSON raw, raw instructions, or the raw coding that goes with that, with that component. And so if you already know Python and, and you know artificial intelligence markup language, you can then customize that component however you want to directly from the JSON. If not, you can just change, change, change. For example, if I go back here and say the name of the bot, that's something that you can change. So instead of, you know, Hi, my name is, let's say you call you named your bot, cocoa, okay. Then you will enter that name there. That becomes then a way to customize that getName. Know this particular function is going to allow you to literally then ask the user for their name. So if we go back here, let me actually get rid of this now. Okay, and then let's run this type anything to get started? Hi, I am your box. First. What is your name? Now at this point? Okay. Let me go back here to talking about customization of these different components that you can add for, for the, for the project that I'm asking you to complete here, you should be able to use either the getName function. You can also use the same input, okay? And you can also use as part of this also you're going to use several says. And then navigation. Now for the two just to help you out here for navigation, for example, you can say the first navigation way, and we're going to create our own. And that first navigation is going to be, okay. Let's say, I'm going to call that something interesting. All right, So here, okay. If for example, you're going to be asking, if you're going to be asking about to tell you something interesting about you, okay? There's several ways that the user may ask that. So the user might say, for example, tell me something interesting about, let's say lockdown. Okay. The user might say here, what we're doing here is what is interesting about them, is correct, is about MCDA. What you can type today with time and type in? Correct? The user might also say, okay, like what is, what is knocked out like that? So the idea here is then you're actually okay. You throw a few things, therefore, the bot to, to learn on how to respond. If the user say, Tell me something interesting about mocks up. Okay? So at any point, if the user say that the bot is going to extract, actually, there's something interesting and of course that the two main things here, okay? Is that the interesting? And then motor. You don't have to say this, you know, to, to teach this back, to remember every single way on how to say what's our ask what centers and mocked up but rather few phrases. You can also use keywords. But for, for the, this, for the sake of this project, it would be better to use, to use phrases. Because if you just say the word interesting, Okay, a few based only on the word interesting. And you could have a different conversation there or you may not get, you might not get the right outcome. Whereas again, what you're trying to go after here is that for someone in the class or for me to ask, to ask you about, to tell me something interesting about you. Okay? So if we save that, type anything to get started, let's stop that here. And I'm going to delete this node here. Okay? So now, okay, You can add your answer there, okay? So at any point, so let's say mommy loves you. Trouble. Okay? Anytime, once the user, once your body as you say, How can I help you? If I say, at this point, if I say okay, tell me something interesting about the response is going to be mocked up. Loves to travel. Okay? So without giving you more hands, because I still want you to actually, a guy's a practice that and get that. Your entire project is basically can be, can consist of literally nothing more. Nothing more than just the navigation where you're going to have the different things. So you could have something interesting, you could have favorite movie. So in other words, you're going to be adding, adding additional intense there. So if my intent to ask for your favorite movie, you could have an intent that's called the movie for example, or component and so forth. And then put the answer to that. And then once you're done though, you want to close you want to close with either away. So let's keep it simple. Okay? If it's something else, okay, You will end the conversation. Or you might at the very end here once, once that wants to see that at this point the path is still open over here. So this is not a good happy path. Because once the, once the bot answers my question about what's interesting about Makita, okay? We'll do I go from there. Okay. Then of course, the answer is that you want to tie that back to going back to navigation so that the user may ask the next thing in that from that navigation or ask for that or communicate the next intense. So my next and that will be tell me something, tell me mocked as favorite movie, which I will have, you will have to build it, you'll have to add to that navigation box, okay? Now at any point to, you can also add something in there such as a way to end a conversation where once everything is done, you could have your bot say, okay, if you have, if nothing else I can help you with, Have a good day. Okay? So be sure then you're you're be sure that your your conversation does have an end. And you can also, for those of you that are actually get this very well. And then when I want to experiment with this more, you could actually also add in there something, a fallback where if the user say something completely inappropriate or if the user says something out of the, out of the conversation, desired conversation, you can simply tell them, okay. This is the end of our conversation. Goodbye. Okay. Does that make sense? Everybody ready to get started with this? So let me then stop here because some some questions on on proceeding. Okay. I see that RS, if you're unable to save your name as input. Okay, well, let's go over that real quick. Okay, so first you want you using the same inputs, okay? So when you're going to collect connect to save input, to wear, whether you connected directly from, after, from the navigation or if you still working on this, you connected it from the first, say, okay, once you have that connected, when you click on this, okay? You need to give that. You need, you need, you need to actually give that input to be kinetic, collected a name, or basically assign a variable to it. So in this case, again, I call their name, but you can call use whatever you want to. Okay? So now you see if I go to, you know, I'm saving that value, okay? Whatever, whatever the user says, I'm saving that under the value or variable called name. Okay? So when here, you want to. You want to call that variable, you will have to use the dollar sign and then open the squiggly parentheses there and use context dot and the name of that variable name. Okay. So then, so let's go from here then. All right, so type anything to get started. Hi, I am your bot. First. What is your name by dollar context dot name. Right? I wanted to also see that in the path. You see I did not give the bot a chance to pause and to get the input because you see I disconnected that navigate there. So anytime you have a say and you want the bot to capture an input, you would want to add in there and navigation type anything to get started. You would want to add then the navigation to allow the bot then to get to get the name. So now if I test this again, okay. Type anything to get started. Hi, I am your body. First. What is your name? By dollar, context dot name. Let's see. They have something that's not supposed to happen there. I can see what it did anybody else experienced the same thing with using the Contacts Name, did not give you the name. Raise your hand or let me know. There are two options I'm done and one failed, but my body is not able to recognize when the task is done or failed. Yes, So that's interesting then there was earlier, so type anything to get started? By dollar contacts, dot name. All right. I have a little, a little, a little issue here with this, with this bot not recognizing the value because the name of the name of the parameter is there. Okay, I see. So let me work on that issue here. I think is something that we have here, something that happened, which we save in this parameter as a name. So I'm going to work on that. See the dash n. Sorry if I mispronounce your name, you raise your hand and go ahead and unmute yourself and tell me. Okay, while I get this little bug here fixed, less than straight, jump straight into creating your first video. But this is actually is going to be, well, we can still get around actually this little bug here until I get, get that fixed. Okay, let's go ahead and jump into creating your video, which will do the same thing as we'll see in just earlier, but there'll be some components that you'll be able to customize and still complete this project. Okay? So if we go to when you click on bots, okay. The first step to Cree in new video Baht, okay, Is going to click on Create Bot. And if you follow through with this, again, notice that for this particular platform, we've added also emotional intelligence avatars. These are actual boss, they can carry in a different emotional understand, have emotional analyzer and can actually carry a human-like conversation. Okay? But let's, for the sake of this activity, less than just choose one of the other regular avatars. Since you just, you don't have access to the, You haven't paid for this application to be able to use this emotional for more sophisticated video bots or AI assistance. So first thing, let's all this. I'm going to call this again my box or my v bought my video about okay. And now that I gave it a name, I'm going to give it a character, so I'll choose this one. We will choose him, okay? Now once you choose a character, and then you would want to choose a voice. Now to choose a voice, you can listen to the voice before you choose itself. Here, my name is my video bond. Okay. Was checkout Justin. Hi, my name is Maggie and I can just adjust. It sounds like almost like Justin Bieber. So I'm not going to deal with Justin's alga with Matthew. So Math High School, my name is my video bond. So I'll choose Matthew for further and rate. So given in that, in that is actually in this particular platform, it's got different already personas built into it. So at this point, okay, You could actually choose the persona, friend persona, because what I'm asking you to do is to create a bot that's going to present you that you're going to invite to the classroom as your best friend or parent. So that you could actually also then use this, this preexist in persona bought as a friend and then you can customize it to do exactly the three, the four things I'm asking you to do. So let's choose this one, okay? And I'm going to call this one. I am my video bot. Helping you with. Let's say motor is the first and let's rebuild and as you can. All right, So at this point, we've got our video about built and ready. There's, there's a brain that's already there, okay, which we can take a look at, which is the actual components. There were already pre-built for this particular one, for this particular bought my video back. Okay. But that's the part that again, to get around the other issue of getName or for some reason it was not written the remembering the variable name, even if it did it when I first did it myself. To get around that until, until fix that bug. You guys can actually use this existing video bar and then customize it. So we're going to take a look at how you customize it before we customize it. Okay. What did you notice there that you can actually add some knowledge to this bar as well, okay? So this knowledge can consist of questions that the user might ask and responses that you give they use it, okay, So for example, I can pretty much already say that likes to travel. Okay? And let's add add another response. Likes to travel. Now. I could literally add questions here that the user may ask. The question example maybe, okay? For example, what is, what is interesting about that? Right? So I think that's enough for right now, just for you guys to get you started. So notice I already have a couple of pieces of knowledge already built into that and to this bot. So if I start talking to this box, I could ask if I say, okay, Makita or what's interesting about MCDA, I should get the answer is that mocked likes to travel. Okay. And that's how you guys can actually do that. But you can also do it directly from the component that you're going to customize and add to this, to this. But let's first start the conversation with this, but just to test it. So in this case, I'm going to actually tested as a video. Okay. Does that tested as a video? Okay, let's choose a background. We already chose the voice and chose what we want this bar to take a look, to look at, and let's talk to it. So once you build your bot, are you customize this, but you select a video about New customize it to achieve the four things that I'm asking you to do. You can then bring this back into our classroom and then we can talk to just like I'm about to talk to this. But that I called my doc again. So to get together, to get started, as you have to take it out asleep by saying wake up high on my video by what would you like to talk about today? Mocha. That's a great name. I like it. What do you do for a living? I like music. What kind of music do you like? I like all kinds of music, but my favorite is country. I play football. Oh, that's cool. What position do you play? I play the drums. You're lying to me. I'm not lying. I'm Mohamad. What is your name? You're lying to me. I am not lying to you. What do you do for a living? I'm a football player. And that conversation there. Okay. So that's what I was showing you right now, is already the top of persona. There was already built into that, but now, what do you need, what you need to do to add to this part to me to customize it in what I'm asking you actually to customize this, but is the four things that I talked about earlier, which is for the bot to introduce you. To tell us something interesting about you, to tell us what is your favorite movie, and also to tell us a joke. So let's take a look about how you're going to do that, okay? So you're going to do that from the brain. Which means we're going to go to edit this, the brain. And here you see, you see that the path similar to what I was talking as shown earlier, right? So you see here the bot starts where it does say its name, okay? Whatever the name that you gave it in this case, we gave we gave it a name. My video about so I say, huh? Um, my video about what would you like to talk about? Okay. And then it pauses there to wait for you to say something, Okay? Now, you can literally come in here, okay? And customize this by adding instead here, this right here. Okay? So before, before the bar goes to, you can make that actually the bot can go to that conversation. If the conversation falls outside anything, then tell me something interesting about you all. Tell me your favorite movie or tell me your Tell me a joke or tell me a rental. Okay. So this is where you can go in here, okay? And you can start adding your component. So I can go in here and say Create. I'm going to create my first component there. And my first component, I'm going to call it or a column sum. For the sake of a better name, I'm going to call it something interesting, Okay, right in here where I can start then, given my buck the phrases that I want my, my bot to understand that I'm asking something interesting about about, about this about you basically. Okay, So here we're at, then I can start saying, I can start entering some of the phrases that I want. The user may say or may ask, okay, such as tell me something. Interesting about, about you in this case. Let's say your name is not much, okay? And so forth. Or you can use a may ask what is so interesting about and so forth. Then you save that. Okay? So now, okay, this is where then you can add the answer to that. Let's move this up a little bit here, over here. And you would connect that and then give your answer there. So what's interesting about more, as we said earlier style, you could say likes to travel, for example. Okay? And then when it's done, I'm going to go back over here. Okay? And so now if we save that, then we go to, back to our bot that we created for this letter called my video bot. And let's test it. Let's choose a different background this time. So let's choose this as a background. May take a few seconds to recompile. Come up. We're almost out of time here. I didn't realize at the time is just some there there is there is so much things here to pack and it's only two hours. But before, before actually we jump into questions and et cetera, I see that maybe this was a little bit too much for the time that we have. Just want to okay. I hope you guys still can go through this and still build. You're going to actually send you the entire presentation here, which have in it the things that you need to complete as far as your, your, your project, which is again the part one and part two. Okay? And and once you complete that, then you can actually then if you wanted to, then to bring you your bot, if you want to bring you back to, you would connect your butt to bring you back to Zoom or you want to send it to somebody through Facebook, or you want somebody else to interact with it, even by phone, et cetera, possess all these video bots can be connected to so many different ways. Okay? But for the sake of this workshop, I wanted you guys to actually invite the bot to your resume. And you invite you bought every time you create a. But again, you have to give you bought than an e-mail address, so I could say my video. But so now at this point, this becomes the e-mail address of that bought that you created that you want to invite to a Zoom session with your friends or if it's done allowed, would invited somebody robots here to our session. Copy that, and then that's the address that you invite. So you do like a regular Zoom invite. Invite you bought by just providing that e-mail address. So be sure that again, you select an email address and that would be the same email address every time you buy that. But you can also invite you bought through Connect by phone or if you want to send it to somebody and, and through Messenger, you can have your other friends talk to this video about once you've customize it and once you, you know, you can have fun with it and make it do other different things again. So I'm going to actually, because we're almost out of time, realize that there are probably still a bunch of questions and et cetera. So I'm going to ask our moderator to, to probably help me streamline some of these questions and still be able to follow up with some of you guys. And make sure that all of you, at least, if not, most of you, still won't get a chance to build, to customize this bot that we're, we've talked about here, which is the my video. But then when you customize this video, but like I said, we're going to go back here to the, to the brain of that. But you're going to add something interesting. Favorite movie, a joke to this navigation. And then every time you add one of these navigation, give the answers through a say, and then link it back to the navigation. And then once you're done for anything else, then you can link this to the persona. So than someone who doesn't, who wants to do more can start having to carry on a conversation with that as a as a BFF or a restaurant. Does that make sense? So if you're sending this to your friends, are sending this to somebody, they can literally have fun with it. Notice earlier when I showed you, is that this bot has got, it's already got built-in, a way to identify different thing. So if you say, if you're talking about music and that's a sudden you say football. And then the conversation might change. Or you might ask like, for example, when you like to do. And then you jump, you jump into different conversation. So in other words, it will allow someone to carrier, to carry a pretty decent conversation with this. But in addition to performing the four tasks that I'm asking you to do for this project, wishes to tell him something interesting about you, your favorite movie, and to tell a joke. And also what you'd like to do. Before we run out of time, there are probably see if there's any most, most pressing questions here for you to be able to complete this? Can anybody think of anything that might keep you from completeness or does everybody feel comfortable they know that your urine, you've been introduced to this platform. Keep in mind you also we can ask for help within this platform. But, uh, but again, like I said, the best, the best way to do is to use pre-built bots, which is in this case a friend and then customize it to do the four things that I'm asking you to do for this. And then you can send me the JSON file. To send me the JSON file, you simply download it. So when you download that, it's going to Assisi notice here it downloaded that as a JSON file and that's the file that you can send me know if you have an issues and you want some help with it too. You can download the JSON file and send it to me. And then I can look at it and then fix. Fixed. Basically, if you have some errors in there or see if you have a broken pass somewhere or unhappy path. I can fix that and send it back to you. And then you can import your JSON file back into their platform and then you'll have a working but. Okay, let's go, let's go to our moderator here and say, Oh, because I know we're about to run out of time here. Yeah. So Sarajevo should have reminded you, but then you were going with the flu. I didn't want to stop that. So what they would do it at after the sessions are well by tomato, one doctor finds he sends me the presentation. I put forward that along with his e-mail ID so that once you create your heart, you could send it to him, like he just explained to you. So is that okay with all of you? We can give me a hero. Can we connect? Yes. Yeah. Okay. Yeah. So everything that we talked about and everything that I was showing is actually part of this presentation. So you see that in session 1 and session to include in the customization etc.. So that would give you a way to go back. And so it's all in that presentation, which I'm going to be sending the presentation. So you'll have the presentation and then you shoot. At that point, I'm hoping that all of you actually will be able to build your to complete this project and then send me the JSON file. Thanks. So now you have anything else that you'd like to share? We can get to low milliamps if you'd like to sharing. Yeah. So I think we will talk about actually, I so I see and what we do at SUSE, we recently actually started an AI program. And the purpose for the a, this AI program is not to be because, you know, there's so many different aspects of AI. Our program is actually is about applying AI, which means I, for example, a computer science person May look at the ask about the mathematical are there or the electronic, electrical physics, etc, of way of making, for example, converting an English item to two machines item. Whereas in our program, we actually asked, we asked how we asked about how to apply, for example, machine learning and deep learning into building Conversational AI or building an entire digital workforce, for example. Or into building or applying AI functions, including software bots or robotic process automation to build digital workforce. Or, or even using machine language, machine learning and deep learning into for data science analytics, for example, or for AI analytics and so forth. So in other words, our program focus more on applying AI to solve problems or two to see is opportunity. Such as, for example, again, of AI Analytics or use of robotic process automation to create digital workforce. And that's again using AI to make us smarter and do things better. Instead of how to, how to make the AI itself smart. Does that makes sense? And this program also. And I'm here, I'm just telling you about the program, but there's so many things that our SOC school that feed into this program but also support this program. And I'll let you guys actually discover that for yourself. So I invite you definitely to look into that. And regardless, what you're going to do in the future. I wish you luck with that. But remember that AI is going to be in your future in one way or another. Whether it's going to be part of what's been used for you to work with or work on or the news on you to perform your work. So it's important that you start considering AI and AI functions and AI application as something that's going to be part of your daily live in moving forward and more importantly, part of your future job. And I'll leave you with that. Again. Wish you guys the best of luck. And perhaps we'll hear from some of you as far as your interest in our programs or interest in our school. Thank you so much. Dr. Z. By taking the time out today, hopefully, we can do any Bletchley Park chunks and then soon we will. Pretty common situation also gets resorbed. And, and thank you so much just audience for participating in today's workshop. I will be in touch with you for your certificates for the presentation and also Professor Bouazizi e-mail ID. I will share that with you. So don't worry and you can always get back to any details, any doubts that you have. Thank you so much for this wonderful evening and for this wonderful interactive workshop. Stays safe or loved you.
And good night.
The Media School at Indiana University Bloomington (IUB) & Jindal School of Journalism & Communication (JSJC) at OP Jindal Global University (JGU) marked the beginning of a teaching and research partnership with a virtual seminar on media and democracy. Faculty and graduate students from both institutions presented their research on the media’s crucial role in democratic governance in the Global North and South.
Description of the video:
From India, everyone Welcome to the media and democracy seminar hosted by Indiana University. I'm the fenestration, the director of IU in their gateway and my colleague menu and I worked to facilitate Academy and research collaborations between Indian higher education institutions and Indiana University. Today we have with us faculty and graduate students from the media School, Indiana University Bloomington and Jindal School of Journalism and Communication, oxygen dial university, Sony, but who will be presenting their research on the media's crucial role in democratic governance in the global north and south. We encourage you to ask questions and interact with the speakers to make today's seminar a productive and engaging session. Thank you so much for joining and I hope you all will continue with such engaging conversations to be yeah. Thank you. Over to you occasionally. Kinds of vena, a very good evening from India there, good morning to the rest of the people who joined us from across the seas and welcome to the first collaborative seminar on media and democracy, as Athena said to mark the beginning of a partnership between the two schools. And thanks to everyone involved to make this happen. I wish she was here, but she's infected with this damn virus. So she is out of if you ask me about what this seminar is about, then I'm willing to fall back to the cliche, excuse me, for a cliche and we know what Bertolt Brecht said when asked that there would be, or could be poetry in dark times and reply about poetry in the dark time said, Will there be singing in the dark times? Yes, there will be singing about the dark times. But what does a journalist, what does a writer, what does an artist do when the medium itself, the language, has been commanded and manipulated by the forces of political and cultural power. Propaganda, for example, on the surface level is the distribution of slanted information today, if not bold-faced, lies with its vocabulary repurposed Orwellian style, perhaps more nefarious today. And it's relentless denials of truth than the crude cries of Joseph Goebbels. And again, excuse me, bear me out because I think we've reached the limits of democracy and democratic authoritarian governments. And when I say limits of democracy, I mean in the name of democracy, whatever is happening, particularly in the country from where I am speaking. Which journalists, which author writing in English today can use words like fake or tremendous without gasping for air while drowning and caveats. And I loved this line, which I'm borrowing from a poet who said that even orange has lost its innocence. Blush. Today, or language or vocabulary our imagination, our words have been denied their meaning. I have been on the roads since the early December last year risking myself, but I went on this tool just to get a sense of what's happening in the country last two years. I've been more or less bound to in my village in Sony, but on the campus of OP Jindal Global University. Now while touring the state support that today's Maharashtra, Madhya Pradesh, Punjab, and then the SAM, it appears all is good. Which means all is pretty much chaotic and anarchic as it used to be in India, but as we are used to. But on one hand, you can understand, I think you'd get a sense that there isn't a marquee that's getting used. A different kind of era, a different regime. And by saying different regime, I'm not really insinuating entity, but it is a different India today. We all know what's happening. India's Hindu nationalist government, which has been criticized for silencing descent and undermining independent media with critical journalists have been branded anti-national, the charge on the anti-terrorism laws. And I don't think so. We should hesitate to say that under our present Prime Minister, Narendra Modi, press freedom has deteriorated. Within the dropping 242nd place and the list of a 180 countries second year in a row in the world, press freedom index. Newspapers and television networks critical of the governments have either had their advertisements blocked or their officers raided. Activists have been thrown in jail for organizing peaceful protests. I had this young, not so young now, but I haven't. I knew him. He was really young photographer and Sam who came and met me when I was there and set that give me a job because there is nothing else left here to do. All the newspapers, all television, every single press platform in a same. Unless if you, if you report anything negative against the present Chief Minister of the present government, then in the following week, the norm is for three days, all government advertorials will be withdrawn from you. And that's pretty much almost like a diktat. Now, it has resulted in widespread self-censorship on the part of media. A sectarian agenda critics have said, have accorded many more primetime slots in tune with Hindu nationalist government, right-wing politics. And we all know that Modi has not conducted a single news conference since becoming Prime Minister in 2014. And that's why I'm saying the limits of democracy. In a democracy, the world's largest democracy, the Prime Minister, has refused to meet the press in the last seven years, eight years now. Before an abrupt decision to announce coronavirus lockdown, we know that he met editors and owners of at least 20 major media organizations asking them to publish positive stories. Now this has become the narrative in India. Even the Indian citizens and the viewers. They find journalism, as we understand, problematic because they say, all you talk about are negative stories. We want to hear good things. It is not possible that a government, everything that the government is doing is wrong. There must be some good things that the government is doing. Why gone to tell us the good thing is if you're telling us the bad things and so on and so forth. Because mean, of course it's a particularly dangerous case, the extreme case on the limit case of where India will go with the kind of things Modi is doing. But I would like to flag this out here. A fair assessment will tell us that democratic India had never been truly covered by media. And misinformation or disinformation is not today's ailment. So the way we see this is a new regime, the new era. There's a new way of doing things, but it has never been really as robust as we imagined it to be. And I say this with a sense of responsibility after having spent three decades in Indian newsrooms as a journalist. And I sometimes point fingers at myself for not having done as much as I should have or could have, or as much as we should have or could have. I think this is something that we need to look at rather than pointing fingers. Pointing fingers at ourselves is extremely important. India, maybe the largest democracy, but I rest my case saying that it is not a constitutional democracy me longer, because for it to work. The checks and balances of institutions on the press. It may be a democracy in the sense that the majority rules, that the mob rule is in some sense. But it is not a constitutional democracy in the real sense today. And I think over the next few hours when you discuss about media and democracy, it is to be able to strengthen that institution so that the constitutional democracy can survive. At Jindal School of Journalism and Communication, we make a sincere and spit it an effort, at least I believe we do, in helping students make sense of what is happening around us. The prime responsibility of journalists is to make sense of what's happening around them. Often a lapsed we witnessed in today's world. At j is JCB imagined an undergraduate program in the best tradition of liberal arts that informs us why we need freedom of speech. How do we strengthen democracy? Our pedagogy is dynamic, but no other time can perhaps be as fluid at the time we are in. A time when we must think of the dark times, but a time when we must, in letter and spirit, hold hands and collaboration. I will appreciate if each one of us can ensure that this is not one of seminar and sharing some papers and ideas, but a collaborative process with a sense of continuity. Because I think that is probably the only way or the only roadmap to the future. Thank you so much. And I'm looking forward to the presentations. Times Minow. I think that I'm handing it over to radical now. Thank you and hello everyone, delighted to see you all here. I'll start with on a personal note by saying how wonderful it is for me that my old and current lines are coming together through this, a seminar. I never imagined this would happen when I came here as a grad student almost 30 years ago, right? I did not imagined I would be here facilitating something like this. So personally it's such a meaningful collaboration for me. And as I pointed out, I hope we can view this as a starting point for many more wonderful future collaboration. Not just in research, but also teaching and other types of collaborations. This is a, I would say, the media School here was formed not very long ago, right? We are still a relatively new media school. They represent the coming together. Different departments on campus, from journalism to communication science, to Media Arts in production and cinema and media studies. This is a school that's very committed to the current project that we're exploring. We have scholars across all these units were working on papers that in some way or the other addressed democracy, freedom, citizenship, global citizenship, local citizenship. And more. And to kinda build on what casually talked about, about poetry in dark times. In the US in the last week. There have been a lot of poetic deliberations about the introduction that happened here a year ago. This is the velocity of that introduction. And we'd been, the news media have been conducting some really great analysis of exactly what happened at the Capitol Building a year ago. Why did it happen? Why did mobs takeover? And of course, a lot of the analyses touch on the various topics that we're going to hear from our presenters today. Whether it be a gender, race, class identities, that there'd be disinformation, whether it be how the pandemic might have led to some of the events that have happened, one and so forth. So I just wanted to say, I want to start our deliberation feel by first thanking all the presenters. Without their research, without their poetry, there would be no seminar today, right? So I wanted to start by thanking them. And then of course I want to thank everyone on the Indian side from Jim Dahl to gateway, to the people at Gateway. And then I want to end my tanks by saying, thank you to two very special people here. And that is my colleague, Jim Kelly with whom I have enjoyed collaborating to make this happen. He has spent a lot of time in South Asia and adds a lot of interests in the region. So it was very special that we got to work on this together. And then none of this would have happened at our end. Without the help of Elizabeth. She has been stellar source of resource for us here, pulling everything together. So I want to thank code as well for doing all this wonderful work here today. So thank you Elizabeth for joining us and making making this happen. I'm looking forward to all the presentations and I'll hand it over to Jim Kelly now. Hello. I am Jim Kelly. I am the associate professor and the director of journalism up unit in the Media School. Tibial muted. You're muted. Yes, I think I was saying I'm an expert at technology. Sorry for that as well. I think that you just mentioned that today is an ominous anniversary in the United States. One year ago today, insurgents attacked the US Capitol and attempted to disrupt the transition of power in the year. Since journalists bravely reported extensively on the insurrectionists and their allies in government and even in media. They've reported about the findings of the congressional select committee to investigate the January 6th attack. They have commented upon the parallel those events posed to democracy. They've been countered by commentators on social media who do not share journalist ethics and do not adhere to fact-based reporting and the truth, but instead spread the big lie that a presidential election in the United States was stolen through voter fraud. For 110 years, the journalism program at Indiana University has educated students in the proper conduct and role of journalists. Journalists in a democratic society. We have consistently taught them that the fourth estate is essential to the governance of a free people. And that their role is journalist, is grounded in ethics and regulated by their peers who do not tolerate false hoods or deceptions. Those former students are today doing the reporting that informs us about these threats to our democracy. And we're grateful for their good work. But this sad anniversary in the US also marks the start of an encouraging collaboration with journalism colleges at colleagues at OP. Jindal Global University. And I welcome you here today with excitement. Like erotica, it is good to be back in India. The journalism faculty at Indiana University are 28 professors and lecturers still dedicated to democracy and a free press. That takes its responsibilities seriously and with purpose are teaching prepares our 450 bachelor students for careers in newspapers, magazines, radio and television news programs and all manner of online news outlets. But also as public relations personnel's at corporations and civic organizations that speak honestly and openly about the day's events. They are REG, they regularly when national reporting awards and PR competitions. There are very few major news or public relations firms in this country. We do not have alumni, were proud today to associate with journalism educators at Jindal School of Journalism and Communication, who share our commitment to honest and reliable journalism and Ethical Journalism Education. At Indiana University journalism, about half of our faculty members hold doctoral degrees and engage in research published in national and international journals as well as on the world's most prestigious university presses. They had research institutes, sit on the editorial boards of journals and chair dissertations and theses. Our students in doctoral and professional master's degree programs. The other half of our faculty are professors of practice and lecturers with years and often decades of experience as professional journalists and public relations practitioners. While primarily teachers, they also engage in creative activities including books and reports on pedagogy. And they sit on the boards of professional organizations. Indiana University and the journalism program of long looked forward or headlong lot beyond US borders and engaged in international collaboration. Reaching back to the 1940s, we've recently hosted scholars and visiting journalists from India, Pakistan, Sri Lanka, Bangladesh, Afghanistan, Uzbekistan, Kenya, South Korea, the Ukraine and elsewhere. Because we know that our journalists live in a multicultural world of interconnectedness. We regularly send classes of our students to Europe, Asia, Africa, and South America so they can learn from journalism faculty and students with different perspectives. We also host graduate students from around the world, two of whom you will hear present their research in today's seminar. It is for this reason that we look so excitedly at the future where our belief in democracy in journalism can be supported and strengthened by our association with journalism scholars at O P Jindal. I'm excited to learn if your scholarship today and I welcome additional collaborations in the very near future. Thank you and please enjoy yourself. Now I'm turning it over to welcome everyone. Thank you, Provost Kelly. Welcome everyone. I'm Bill Thomas, program coordinator that you inject gateway Delhi. Quickly run through the format for today's seminar. We have four panelists today with three presentations of 15 minutes each, and a chair for each panel. At the end of each panel presentation, there will be a Q&A session for 30 minutes. Please make use of this time to ask your questions and actively participate in this discussion. We request the speakers to keep to the time allotted. And our colleague, Elizabeth from the media School will help you stay on track. At the end of panel trick question and answer session, there will be a half-hour break at 1115 AM EST or 945 PMIS. Just moving on to a few guidelines for today's seminar. Please. Ensure that you mute your microphone and you could use the raise your hand function whenever you want to ask questions. Alternatively, you could also use the chat box to type your questions. We request you to keep your video on as far as possible throughout the workshop. And we also encourage you to stay until the end. But if you do leave and rejoin the seminar, please use the same link which you received in your confirmation email. Please note that we will be recording this session and taking screenshots that may be used on our social media pages. I would now like to handle what those session to crouch radical, pardon me, spring. And the chair for the first set of presentations. Thank you everyone. Have a good day. Hi everyone, just to introduce myself very quickly again, because some people joined a bit later. I'm radical perimeter and the Associate Dean in the Media School. And I'm like to chair the very first panel. And so just because this is Zoom, I want to make sure all our presenters are here. So let's see. Benson. Yes. Okay. Lucida? Yes. And so Kumar? Yes. Okay. Great. Thank you. All right. So let's do the waiver doing the panels is we're going to go in the order that you will that some of you would have seen on the schedule. We're going to start with Benson and then go to Lucida and then so Kumar, I'm going to request each of you to please state the title of your panel and you know, because I don't want to say it. And then people, by the time they come to your presentation, they may forget. So I would request you to state the title of your panel. We have a wonderful set of people feel crisscrossing so many topics from online dating to migrant discourses and to the pandemic. I'm really looking forward to the presentations. The three presenters from the Jindal School today are Bentsen, Rajan, Lucida sand, and so Kumar, motor leader. And I'm really looking forward to our panel. Let's go ahead and get started with our first presenter. Who is Benson? Benson, Are you ready? Yeah. I'm just opening the slides. No problem. No problem. Alright. I'm assuming everyone can see it. Thank you. Alright, let me just start the timer. So good evening and good morning to all the people that I've showed up. So my work is basically looking at online dating. And specifically from the woman's perspective. The study is ground like specifically looking at bumble as the app. Now, historically speaking about online dating, I hope some of us over here can relate with some of the things I'm talking about. Because the 1990s was like probably the first instance where we had a particular app which helped us out in staying in touch with people, especially long distance. So for me specifically, I think these two apps were really important. These chat groups that emerged from the MSN Messenger and yellow messengers were very important to keep my long distance relationship going during school is I think whenever we would have our winter breaks or some outbreaks, I used to spend hours on these and I don't know if others here have also done this. In the nineties were one of the primary species were online intimate relationships had an opportunity to be formulated. In the 2000s, we had the coming off things like Hi-Fi, MySpace are good and Facebook. I did not use awkward, but I was on hyphen Facebook. But again, this was another space where you could form some kind of intimacy and relationship, not for marriage purposes because for that we had a separate set of sites. But what we do have is the like. The past couple of decades, we've had the coming enough tinder bundle grinder happen. All of them have come into the country and they've come in and they've done really well, like in terms of the revenue with the market revenue that they have been able to pull has been insignificant. Like we're only second to United States in terms of the revenue that is drawing, even though the reaches small but 31 million users basis quite big. So what we also have is a kind of normalization of digital dating is taking place now. And I think pandemic has really accelerated that in India. And I realize before I go any further, I just wanted you guys to know that this is this is my proposal to add and this is a nascent stage of my study. I'm just presenting the proposal. Data collection. Nothing has been done yet. So this is just a nascent stage and spoke to through the NGOs on board with it. So this is what it is. So yeah, like speaking about the normalization, there is a significant concern that comes through when we talk about dating practices and culture in India. Majority of the population in terms of gender, is male. When it comes to dating, what we have is like 29% of the users are female, but 67% of the people on the platform are men. This has hampered women's experiences on the apps. Basically, they're bombarded with attention. This list, them feeling intimidated and harassed on there because of the sheer volume of messages that are coming across. And there have been studies done by not an informatics. We speak about eight or ten people have been facing harassment and this is. Of course, supported by National Crime Bureau reports, which support the fact that there is a growing trend when it comes to sexual harassment and exploitation across India. And this trend has been picking up and crime against women has been on the rise. Especially. Now. Also when we talk about reported incidents to the fullest. Like we also understand that there's vast number of cases that are under-reported as well. Especially I mean globally as well, but especially for India. So dead woman centric crimes, cybercrimes that also increasing. So keeping that in mind, we have to remember that the emergence and entrenchment of online dating platforms is coming with implications for women's experiences and gender-based violence in India. This is something that like we've had a few civil society bodies look into it, but there is a center for cyber victim counseling. They've done a report on it as feminism in India, social media matters. These are some other civil society bodies that have worked with this. But there's generally a dearth of work which has gone into really understanding the kinds of intrusion and also the kind of technology facilitated responses. So this is the contexts that I'm trying to set into which the studies of Bumble has come up as one of the most popular apps to do the same like it has over 10 million plus downloads in India. And this on Google Play Store and rotten inside shows that since September 20, 24th, most popular app in India. And it's done so in a shorter amount of time than you would expect. And a lot of it has to do with this marketing strategy. What it has done is it has to be presented itself popularly and explicitly as a feminist app. It's been talking about like it's a space that is used as empowering women. And it's helping overcome archaic misogynistic culture and giving women back the choice and giving equity in relationship. And what, what's interesting if you look at this Datastore data here, what you will notice is if you look at bamboo, you'll see that the blue is female and the black is male. But you see that 24 per cent women are there, in contrast with 70% men. So it seems like this, the narrative, this promotion that they have gone ahead what has worked and which whiskers study also shows that women have moved from Tinder to bumble thinking that it's a safer space based on the way it has marketed itself. And of course, they have inspired enough to have India specific features. One of those is like only allowing first initials and sort of the names. So for women like the stigma associated with independently finding partners, because traditionally it's a task taken on by family based on class, cars, religion. You see that this helps to give them some kind of privacy. And Bumble has been quite successful in drawing a large number of female base because that is also what initially has been struggled to get on this platform. So their marketing is something that got me curious and it's also one of the reasons why I am keen on doing this study. Because it explicitly is marketing itself. Like What's a receipt. Talks about the Whitney Wolfe came out and said it's a 100% feminist, gives more agency to women. And one of the things that they speak about as they have in both technological solution to make it safe for women. And this is again covered in the study by Brian hawk. But this promotion about making the first move is something that they had set is quite niche to their app. I mean, of course now things have changed. But when we thought about making the first move, It's about the conversation initiator. So those that I've used this app wouldn't know that like once a matches set, they're given like 12 hours to initiate contact if the contact is not initiated than the magic spires. So in this consequences, so dividend Hawks work shows that like the logic behind this was, if a woman approaches the guy, it is supposed to be flattering. In contrast to say, man approaching a woman, which is an all. So what they have done is they've tried to play the social technological play that they've done, and they've reversed the gender roles. Because, I mean, this has its problems, which I will just mention. But the idea is the fact that if men are rejected, they become aggressors because they can't handle the rejection. And this leads to a lot of fluid remarks and a lot of aggressive content which are extremely intimately intrusive. In contrast, if a woman has coming, there will be flattered. And of course, this is extremely narrow and stereotyping like and like wise man who is thinking that men are, men can handle rejection. They're aggressors and we were all like naive and like gentle. So what we have is this is the strategy with which they went. And they also talk about other forms of technology embedded tools like they have. Speak about this AI, which is artificial intelligence, which is private detector, which is supposed to detect any load pictures, especially dick pics is what we're talking about specifically, are they automatically draw those out? Again? They also came out with like, we have not only that, they clearly like marketed it, saying that no more dick pics and things. So supposedly creating a safer space. And they also have come up recently with standard for safety, which is safety guidelines for others, women, how to respond to incidences of intrusions and abuse and so on and so forth. However, despite saying, despite all this promoted content, which speaks about how it's a safer space, which has resulted in me, women moving from, say, other dating platforms to Bumble. Media reports clearly show that we went across India, continued to be harassed, stalked, bullied, on dating apps without any recourse from the platform. And this is true for bumble as well. And Dani would lock also comments on this from an Australian perspective where she speaks about how new technologies are providing new avenues for men to inflict violence against women. To texting social media, dating apps and mumbles own study reveals that this is a volume. What is, what is strange about this? I really tried to get more information about the survey that they did, but they don't really specify which app what forms of harassment any of those information is coming forward. So I always have this kind of statistics was pretty much for them to say that they're safer space than other species out there, especially targeting Tinder Kotler, the biggest, the biggest user base here. So some of the built-in ideas about safety that bumble promotes. One, we've already spoken about the initial contact. The other one is about the design. Where safety is, the authenticity. You need to be able to link it with your Facebook account so they can verify. They also have photo verification where you have to take a selfie and it has to match. Apart from that, the regular options you'll find on most of these platforms, which is to report, blog, and then match. However, the concern is the concern primarily which is, which leads to my research question is the fact that like bumble is designed for people to identify, understand, and quickly connect in a very short period of time with someone. And the technological affordances that it promotes and it markets creates this idea of a safe space for women. But women have faced harassment on bamboo. The profiles of the perpetrators keep coming up despite being reported. And there is no change to that, which comments about the efficacy or the platform and creating that safe space. It talks about the lack of accountability of the platform and the inadequacy in addressing these concerns. And overall, it talks about the effectiveness of the apps in terms of affording us safe space for women to date equals footage as man. And with that background is where I come up with these questions. Where I'm looking at what are the safety affordances that we find on bubbles? Do the safety afforded safety features play a role in women's experience? As well as one minute, one minute. Alright. I will do this. My methodology for finding this out as an primarily relying on in-depth interviews. And this is because it enables people to recontextualized the lived experiences of using bamboo. And also give me some idea about the social world of dating that one's navigating through. My Idea is to couple that with a diary. The diary interview method, Bessemer man, is what I'm planning to use as well. Because looking at where agrees work, where she was looking at street interviews, there is a nature of ordinariness or every day next to these type of intrusions. And which is why in her studies she saw that people were struggling to recall instances. So having a diary, as well as using the scroll back method where you basically go through those shared communication tools such as the chats and everything. So it will supposed to help with the recall because these are the historical digital traces we can refer to the parts prints. I'm looking at our 20th female bumble users and thinking saturation will be reached little bit for that age group I'm thinking is 1835 because they are the largest user base for bumble. 72%. That is time. Thank you. These are my references. Alright. Thank you so much for that wonderful paper. And yes, the search in progress, It's totally welcomed, right? Because that's the whole point of this photon. To give people ideas. If we could all use our reactions and give applause to Bentsen because That's what is so missing from the in-person. The audible appreciation. That is what so let me do that myself. Thank you. Benson. I have lots of questions. I'm going to hold back and because my one of my areas of research on gender and media so fascinating. Thank you so much. Let's move on to our next presenter. As Lei pointed out, unfortunately, we don't have subroutine that does BV, sure, well and speedy recovery. So our next presenter then is her co-author, Lucida. And I'll just say the title of the paper. Voices from the margin, mapping, migrant discourses and digital activism. Appreciate, thank you. It's great to be here. Well, I shouldn't say a lot of things at the outset. For one thing, it's great to be talking to friends and the Midwest because that's where, when I can't say that's where I'm from, but that's where my PhD is from. Missouri, Kansas City. And I totally, completely relate to the weather and all of them. So yes, it's great to be here. The other thing I should say, I'm an economist and solute cheese, My Media Studies person who I follow. I am going to try to do this work as much justice as possible. It is intended to be a contribution to media studies rather than economics. And therefore, it's, it's, it's a bit of a challenge for me to really do justice to it. The coping I should say before I begin, is that the title voices from the margin mapping, migrant discourses and digital activism. This is our working title. Working title, why? Because this is the title under which we got our ethics clearance. Just being really honest out there. We've been we had to get ethics clearance really quickly because we wanted to collect data and do it quickly. So that's why the topic is so broad. But by now we have narrowed into one area of research where we're looking at the role of inflammation Leiber and creating trust. But I'll get there and I laid this out properly. The image that you see behind you, behind the screen is by Raj raj of the Hindustan Times. And this is very typical of applauded proliferation of images that came out during the migrant workers crisis. I'm guessing the migrant workers crisis needs no introduction, but I should just give it one anyway. When a national lockdown was declared in India in March 2020, with barely for us notice. It did a lot of things. Primarily it lead to panic. It was certainly a kind of authoritarianism. It was a complete sort of like bulldozing of participative democracy. There was no participation here. And as an economist is the most interesting thing to me about what happened. It's just the invisibility of migrant labor in politics to policy. It is no secret to Indian policy makers that close to almost 70 per cent of our labored is informally. Nonetheless, clearly policymakers took the labor of migrant workers for granted to the extent that the declared lockdown in for us without considering relationships between town and village in India, without considering the need for the village economy. Act as a subsistence background to migrant workers who work in the cities. Picture here is a very famous than each city key picture. And of course we miss him a lot since we've lost him. And here is the Aramco schwa high. He's a migrant worker. He's carrying his five-year-old son on his shoulders and they are walking. One time when we talk about the migrant workers issue, he said something that really stayed with me. He said migrant workers have been walking for a long time. The idea of walking is not so unusual if you are a migrant worker in India, the differences that you can take a bus, sometimes you don't need to walk the entirely. You can rely on informal networks. You can rely on the TBA hours and food joints to give you food, water, shelter if you need it, right. So there are provisions that are available to you if you're migrating in normal times. But when there is a national lockdown, all of that is taken away from you. So you start having exhaustion debts, you start having starvation deaths. Colleagues of ours from the law school. Along with it's an international collaboration. They have collected data on just how many migrant workers died of exhaustion, starvation, and so on during the first lockdown. So here it is that you have an invisibility of labor to policy, but you also have an invisibility of labor in the Indian media since the economic reforms. But suddenly at the time of locked down, what you suddenly have is this proliferation of images, sudden digital media visibility of migrant workers traversing these long distances. And these are called the anime images and they became almost ubiquitous. We started seeing a lot of images are calling upon, calling attention to the suffering and trauma of migrant workers during this time. And when you have a proliferation of images and media, you also start having a proliferation of scholarship. So recent studies have adjust the sudden spurt of media attention to the migrant crisis. Image here is from Ravi child three. It's sticking out from the Delhi UP borders. So I really like this one. I think the nice photo is my favorite, but this one would come close second. So studies that have addressed this sudden spurt of media attention, There's a really nice one by Mohan jade that he talks about the idea of kindness. And he says that the migrant workers discourse, media discourse around migrant workers simply focused on the need to provide food packages, the need to provide relief. And he says that this is an extension of neoliberal governmentality. And he says that this is distracting from the real transformational, structural transformation issues about labor rights. Then there's some other from the calculator research group. He has a really nice essay where he says that migrants returning home is a point of resistance innovate to the idea of the occlusion of borders. During this time of crisis. You have, you have crisis in a neoliberal policy background. And then suddenly you have the borders closing in. And then you have the small by agent who is also seen as a carrier of disease, but it's still moving as some sort of resistance has a critique of temporality and space. Which says, they say that in policy discourse we do not consider, I mean, we tried to say that the pandemic is egalitarian, but some people are more favorable than others. That's the word he uses, solvability. You start having this Just as you start having immediate lead proliferation of images drawing attention to the migrant crisis. You also start having a proliferation of scholarship looking at how the migraine has been discussed in the media. This contributes in part to also further background of digital and political action in India. For instance. That is the idea of how, how has the digital contributed to political action in India? There's new forms of civic engagement. For example, Kumar has a very interesting paper on viral parody and satire as a way of online deliberation. But also the digital has given new kinds of discourse and new kinds of engagement. Too many Indians who can access the digital space. Like there's more expressions of caste, class, regional identity, religion. Now, there's more urine during the anterior protests and New Delhi, there was more of a moral critique of establishment political parties. So you also see the digital brings a change in the political contexts. We are trying to speak to these two streams of literature. It's a conversation in part with the discussion on migraine discourses. And it's also a conversation with the digital within the engagement of the digital and the political right. What are we interested in? We are looking at trust and we are looking at how the digital give, migrant, give activists networks the ability to build trust at a time of crisis. So we are exploring the relationship between To between activists networks. We focused on two so far. And how these activists networks have engaged with migrants. Build trust within an, a sort of a public or a social trust. So trust within their own networks, trust within civil society and trust within migrant workers networks. And uniformed innovate some sort of a bridge between stranded workers and activists groups. So there are two handles that we've looked at primarily, we've so far looked at their Twitter handles. One is the migrant women Solidarity Network, and then the standard Workers Action Network. And both of these have been engaging with the they've been engaging in digital activism, but in different ways. Both have presented reports on just how many standard workers that are, what are the needs of the standard workers? How to provide relief? Swan, which is the standard Workers Action Network in particular developed in a way as a way of engaging with they developed as a way of engaging with stranded workers. So for instance, we interviewed one very prominent local workers activist. And he talked about actually he's one of the founders of Swan. He was connected with the MNR EGN networks. I'm trying to protect my sources and not reveal their names. That's why I'm stumbling. But anyway, so this particular activist, work workers activists, he engaged with them, you know, MNR, UGA job guarantee activists and which who he knew from beforehand because they were doing a joint projects earlier. And he just reached out and said, Hey, there are so many workers who are stranded in this, in this town are at this border. They are in need of cash transfers to which the swan activist, who was, he had previously been friends with this other activists through through other joint projects they've done earlier. So he was able to then send out a message through his activists networks and get like collect funds and transfer them to to workers who were stranded. So that meant that you have this kind of micro crack cash transfers happening across these channels. And this time they're happening on networks like banking systems like BPM and Google Pay and so on. At the same time, you don't doing this requires a good deal of information labor, you have to constantly documented the transfers. You have to maintain a database of these transfers. Workers are sending their account details to these activists who they've never seen or they don't know. The activists, then this uniquely, it's almost a position of power in a way to have someone's account details. So you then, in order to be ethical, you then have to protect those account details. You have to ensure data privacy. And you're just a volunteer activist networks. So that takes a good deal of information labor to ensure data privacy to these workers who are depending on you to transfer them money and help them out so that they're not stranded. Two minutes. A minute show here is that actually a tweet from Swan, standard workers Action Network. And they are, they're making a first appeal for farms and they using the Twitter space to do that. They're saying that, you know, over the last four weeks will be made micro cash transfers to 4,500 plus migrant workers and distress contribute here. You can see here that's one has developed trust within the workers who are trusting them with their account details. And at the same times one is also trusted by that activist and academic and student networks. Trusts want to collect the money and transfer it to the workers rather than, you know, embezzled funds. So there is a certain role of the digital in creating trust and in creating bridges in this multi-class environment. So that's what we're trying to understand. Here's a quote from a private conversation that we had with the swan activist. She says swans main task was to do micro cash transfers to workers. A worker would call us up and say I'm stuck or I'm stuck with x number of people. And then they would just see, okay, how much funds do we have? So let's a lot, three hundred, four hundred rupees per person. And then we would just transfer the amount of this person. It was completely on the basis of trust. We had access to their bank account numbers, we had access to them bio-metric information, to very private information that they would just easily give away, right? So this puts a lot of urine. This is a very unique kind of information, emotional labor that these activists are doing. Many of them are students, many of them are academics, and they have to do this kind of work. So what are we doing? We have interviewed about, well, not too many people yet, but we are interviewing migrant and activist networks. And we've interviewed the m ws and sworn handles the people who are running those. We are trying to interview more people. We're reaching our respondents threw snowball sampling where each person we interviewed suggests three others. Sorry, I'm out of time, let me hurry. And then we'll do a quote. We've extracted all the tweets using are very nice API and we are thematically analyzing them and we'll talk about how they've developed. And we're looking at media reports, including the reports of these two handles and ws and Swan who have bought, made reports and presentations to the governments, to local, state and central governments. So how do they build a social trust? They document the data, they document the information. They present evidence of suffering. And in part, this is where we are critiquing. One that does work, where just a relief itself is also social transformation. Just because there is a provision of relief doesn't make this less radical. You have the building of a multi-class society and abridging of the two. And that itself is radical. That's how clean. And of course, we also have these activists networks also recentering the claims of citizenship, such as this is how they document evidence. So they're saying that he has a migrant labor. He has been he has borrowed 23 thousand rupees to afford travel for himself and family. Money lender is insisting on repayment, so he seeks relief and relief. Payments have transferred to him. You also have said the system migrant worker solidarity network. They are talking about how these workers are making these journeys. They deserve voting rights. So because they're moving, they're often not able to vote. How can we make voting rights available to them while they're on the move? So you can see sort of a demand for trains, demand for relief. So recentering claims of citizenship is also another way of building trust. I'll stop now. Sorry for taking so much time. It's okay. Please wrap up. It's okay. We have a minute to know. Yes. I'm done. I'm done. Okay. Thank you. Thank you so much. Yeah. Excellent presentation. And 1 second, you highlighted something that, you know, it's so interesting to think about when you think about economics and media. And in India, establishing trust like that is really were considered a low trust society, right? Where you just Trust that nothing will work. That's what you trust him dead, right? So to have a situation where this is not just a state organization, but actually a volunteer activist organization. Very interesting paper. Thank you. Let's go on to our next presenter. Darren, and the title of the paper, this pandemic as a transformative moment. Thank you so much. So yeah, that's the title I gave and I just stopped sharing the screen. And I gave a subtitle which is kinda prohibition on it's about it's about the credibility crisis, credibility and creditors, the term I use because I think by alliteration, but the references to financial well-being. So I'm trying to find a better title, but I'm trying to reconcile how in a crisis situation, the media copes with the necessity of a financial liability and what implications that has for its credibility gets public trust. So the figure that I have, of course, the first problem that we have with the Indian media dealing with any kind of large-scale study of being the media is severe absence of for libel data. Now this is not just me saying, so here's a quote from one of the media leaders. I hope you can see the slides. Yeah. Yeah. Okay. So it's an annual conference by one meter chambers of commerce of federation chambers of commerce and industry. It's called 50 frames and this is a quote from the chief executive of the study in my dock on the enterprise, which has a pretty flushing presence in India. So here's what he's seeing. Numbers are supposed to be the foundations of rational business decisions. But how can we make decisions when professionals in the business of numbers can get the numbers straight. The lack of reliable data is not limited to television audience measurement. In fact, saturate certain basic point is that we don't have a very level figures on newspaper readership, on that advertising expenditure on television audience and so on. There's a lot of fiddling around and those, those bills into these, because financial fortunes depend a lot upon finding these figures. So what we did find is that there is an organized sector, which is the advertising and entertainment sector, which does try it together. We are trying to make best use of those figures. One of those sources is, is the annual report produced by the pitch Madison. It's an advertising agency pitch Madison that plays a report which puts together all available data sources and tries to estimate how much money is being spent in the media. Then of course, the keyframes is an annual conference room. They produce a bot, which is done by some major accounting firm, which used to be price for House Coopers earlier. Now it sounds in young, these are the main data sources for that kind of information that you're seeking. Here we heavenly figures a total advertising expenditure in the Indian economy since 2011. And you see the bar is steadily growing from just over, just under 300 billion, the figures on 2 billion to just under 700 billion in 2019. And then you have a sudden drop in the pandemic, right? So what you see here is that the orange part of it, which is the share of the digital advertising and the total, is steadily growing. It grows both in absolute and relative terms and be endemic year. So while traditional media suffers a serious loss of revenue, digital media does not see. And looked at it. Looking at the sector wise, you see that television suffers severe erosion and advertising revenue and pandemic year. The blue bar is 2019 and orange bar is 2020. So to print and print, and in the case of printed, it's near catastrophic. It's like a 40% drop in. And then of course, the radio and cinema also suffer severe drops, but those are not significant concern to us. What is the key here is that digital goes against the trend. Digital still keeps growing, though not as robustly as before. From 32%, growth rate is down to 9.7 per cent. But clearly there's a digital shift going on and does not unique to India. Of course, this has been happening universally all over the world. But the pandemic may have consolidated and accelerated that trend. So here you have the figures as far as buzzing expenditure in the economy by media sectors. And we see that print is kind of close to television up to 2019, but then serve as a severe drop because of the pandemic. And digital for the first time exceeds sprint in the pandemic year. And this kind of showing us strong signs of possibly catching up with television. So keep trends. This is from a different source. The first three slides were from pitch Madison. This is from the three keyframes report. And you see that online gaming and digital subscriptions of lonely sex doesn't have media that are growing. All the others have suffered a significant drop in the pandemic. So that's the, that's where I get the title. Current pandemic is transmitted moment. Not that this was unforeseen, it was a slow moving transition that we were missing, but now we have a sudden catastrophic collapse, almost tough for traditional media and possibly an acceleration of that trend. So of course, the key, another peculiarity of intermediaries over the years has been that the advertising revenue has been far, far ahead. Subscription, always more so than in any other country. That was reversed to some extent, the pandemic here, because the subscription revenue showed significant, kind of, you know, did not drop as, as sharp because if you look at the functions of the media industry over what you put what you call the period of liberal, liberalization and globalization, you had a massive growth in the EU, had significant acceleration, growth rate of the economy. And advertising tended to be ahead of that book. For obvious reasons because I'm tracing targets, the upper income strata, which normally do veterinarians high-growth period. You have that that trend persisting right through these years. The blue bar here is the nominal GDP growth. And the orange, orange line here is the advertising expenditure growth. So when the pandemic year, the nominal growth of economies drops, but not by as much as the advertising. So this is kind of payback for those years of buoyant growth when advertising tended to be ahead of the economic growth curve, but now well below the economic growth. So what does that mean to the newspaper industry, to the media industry generally, and how is it, how have they responded to numerous challenges? On the next slide you see now interpretation, largest state in India heading into an election rather in a matter of months from now. And they've unleashed a major publicity blitz. And here's a difficult news newspaper advertisement that the takeout, there'll be model of COVID control. This came out someone's back. But what's notable about this is that it mimics the format of newspaper. It announces right at the bottom that this is a special kind of editorial feature but mimics the format of each paper. And what's more important perhaps is that it uses, you can see it in decibels small, but all these names, yeah, the bylines that you see here are all of journalists who work with the Times of India and look now. So you are in a sense, giving, lending credibility and creating a kind of zone of ambiguity where real news and advertisements are confused one for the other. So is that going to be the the future of the news media? That's some serious question that we could possibly look at. The distinction between the two kinds of news and editorial. Use an editorial advertisement, the creaky differentiate, of course, these structural appeals. And this applies in both the print and visual media. Stylistic presentation story. And it's placed on me. Overall. Format of media platform influences audience perceptions. But when the Lisman mimics the format of the news stories, then you crave that ambiguity. And you created an ambiguity in which there is scope for fake news to flourish. And if there is a, there is a financial incentive for the news media, the news media industry. Then there are very few impediments to a kind of proliferation of fake news. So what possible remedies could be think of this, come to that. But what does it mean operating now in a new kind of social media ecosystem, which is conditioning our understanding of how news is produced and how it is put together and how it is presented. There's a blurring of lines between professional and citizen and dilution of traditional gatekeeping functions. Now, more and more Germans are taking their cues from social media to figure out what are the stories we should be chasing. So you don't have the guiding hand of the editorial process that determines priorities and new selection and presentation. You have people who are focusing on trends within social media. That becomes the basis on which you we know vast amount possible news and to endure it onto a constricted space. Now the constricted space at one time was the overall duration of a news broadcast or the overall number of column centimetres in a newspaper. But now the constraints, there is no constriction on the space. The space is infinite. The constricted spaces, the attention span of B, audience. So the competition for the audience, which is also at the same time a competition for advertising revenue could lead the newspaper industry into certain kinds of avenues where traditional values or sacrifice and you have a possible contexts for fake news to flourish. So now of course, this is a subject that's being much talked about and there's ventricle. I can offer by way of definitive conclusion and a 15-month presentation. But let me just wrap up by considering two different models of social media, or rather internet-based news dissemination. You have. The Google model. And the Google model of course, has been likened to a funnel. Now I don't think family is a good analogy because implies that everything that goes in at one end comes out the other. What I would see uses a see metafile like a C. There's a lot of stuff that goes in here and you have finer and finer meshes as you go down. And you'll see you out depending upon what your judgment of fi, of the user's interests and the advertisement comes in at the last stage, the finest mesh in that sequence of scenes. And it does kinda unobtrusive. It is text-based. The loud kind of visual display ads that brought the earlier search based advertising went just to grief, no, Yahoo and so on. Start at the back-end load, display advertisements will encounter significant consumer resistance. So Google learned lessons and kinda tailored advertising strategy differently. What is the social media? Facebook, for instance. Facebook entire strategy is based on engagement. It's not on search, son engagement. How long have you there? What are the activities you're engaging in there? And that activity is being monitored every state. It's not just that there's a sitting out of inflection. At every stage you have a mixing up of the advertising and the and the user generated content. So few minutes. Yeah, thanks. So, so to say that the news and advertisement content are now become mixed, would be an understatement. Is there a way of separating with you out? Now, there's a lot of literature coming out on this. I'm looking at recent work by two New York Times reporters. Your friend says He account who wrote about an effort by Facebook to attend to public misgivings about that election interference and the height of an intelligence operative. We'll look at the little operative proposed that it could have possibly the same bacteria applied to advertising as a reply to the organic content, that they should be some untruths. Check. Now this proposal, of course, didn't gain any traction. Immediately shut down because Facebook was not about to, about to jeopardize its most lucrative source of revenue. So one other solution is possible. Facebook has tried algorithmic solutions, techno fixes. Now we know that this cannot be possibly responsive to all kinds of cultural contexts. You cannot have the manpower to develop those kind of algorithmic detection methods. And secondly, there are possibilities that you will mix up because of a lack of familiarity with deep cultural contexts in January. So what I would propose, and of course, this is just the opening kind of effort at arriving at these questions that I can. There is a case to be made for revisiting the free speech fundamentals. Now typically constitutional protections are extended unconditionally to political speed subject to certain limits. But is that true, test feasible for political speech in talked over the years. But I think the question is now mortgage and then before our media platforms oblige to subject earnest. And what forms of liability could be enjoined to secure such an a. So that's where I end and I think I'm out of time, but obviously I'm opening up questions which you will be, which are being debated now and will be debated long into the future. But as the journalists, I guess our main objective should be to ensure that there isn't an adverse outcome from this debate to do the objectives of authenticity and trust and news gathering. Thank you so much. Sorry for exceeding the limit. Time limit. Buy a minute, I guess. Thank you so much took Ahmad and I just want to thank all the presenters again for giving us such a wide variety of perspectives and topics that they've addressed for us to think about. We would like to open it up to questions and perhaps so commodity can stop screen-sharing now. Well, yeah. Is that okay? Yeah. Just tell me. No problem. I stopped them and like them to figure it out. Stop sharing. Okay. Got it. Yeah. Thank you. So now we'd like to open it up to questions. And as you pointed out, you can raise hand. I'm looking at the screen. I have to I'll go back and forth or you can put your question in chat. I would like people to start. You know, please feel free to actively participate. As our presenters noted, these are not complete but works in progress. So whatever feedback you can give would be very helpful to them. Is there anyone? Jim, please go ahead. Yeah. I'm curious question. I'm photojournalists by trade and so I was wondering if you could talk to us a little bit about the media effect. That was the photo journalist. Journalism by folks like Danish CDK and rubbish other clever. Yeah, Thanks. Thanks James. This is a really great question. By-and-large, it seems that photojournalists are among the main drivers of media discourse or the migrant workers issue. And those images played a very important role where you, firstly, you'll see this sort of what do they call it a helicopter view. Not that it was shot from a helicopter. It was not. But you'll see this view of buses and thousands of people jumping on these buses. So one often sees these images of particularly South Asia because these are very popular, a populated spaces that high-population density. So you see these images and you get really stressed out thinking, Oh my God, here are human beings in large numbers in close contact during a pandemic. But you also, I mean, what I love about the niches picture is that he also shows a parental instinct Where that is this father carrying his child on his shoulders. So it also humanizes the migraines. There in the scholarly literature is now divided on the issue of, should we, what are these images doing? They're making us feel sympathy, but are they taking away the attention from the larger transformation of issues? I certainly do not think so. Because When you, I think there's a role for care and empathy as radical. And that is missing from the mainstream literature on the microphone position. Thank you very much. Very nice. Thank you to TDA and I couldn't agree with you, Lord, that the label neoliberal can be applied so easily to so many things, right? And so it becomes a very convenient sort of theoretical framework that you can just apply the various things. And of course, Feminist have long talked about carrying kindness, which are typically seen as feminine qualities, right? And therefore not part of radical discourse. So I, I appreciate what you've pointed out very much. Yes. We have a question from Schober and then didn't show up, please feel free to pose your hi. My question is for Benson, I'm curious to know if you have if you plan on interviewing men for your project and if yes. Why? I mean, how you plan to go about it and if no, why? I would really like to know about that? Yeah. Thank you. No, I'm not trying to introduce men for the study. Primarily, I'm looking at women's experiences of intrusion. And that is to fit in with the larger discourse on feminist criminology as well as dealing with larger Gender Studies discipline. Having said that, yes, I am aware of the fact that men also face harassment. And they are also at the receiving end of multiple abusers. And these are experiences that are extremely real. But looking at the larger context of India and the larger culture of patriarchy and misogyny, think there is a dearth of work done with women and globally also, there's lot more work done with other countries. You have a lot more work than women. But in India, like these are mostly associated with cyber violence, cyber harassment, but hardly any work with dating apps. So which is what I would like to start with women. What did you have anything to add? Yeah. My question did not come from the space of I mean, right now, it did not come from the space of trying to understand the violence that men face. But it came from the space of in the backdrop of the fact that dating is dating, as we talk about it, is a relatively new phenomenon in Indian society. If we can't see, not the dating has not happened before, but dating through an app. As a phenomenon that we understand through say in India, through the pop culture of how it happens in the US or in the other Western countries. So apart from, I think wireless, I feel that there is a lot of general awkwardness associated with the whole process because there is no reference point so as to speak socially. So I'm also curious to understand how menus these platforms. And I feel that if in some ways to understand the violence or how to understand the experiences of women in the platform. Somehow I feel it's, it's, it's imperative to understand how men in India using this. Yeah. And it experiences yeah, I mean, I completely agree with what you're saying because there's this cosmopolitan understanding also of the spaces in which a lot of these apps are being utilized. What was interesting and like my research literature so far, what I was looking for is how the diet to T3 cities are also seeing an explosion of these apps and its usage. But again, similar problems of skewed gender and those issues are quite big. So yeah, I think it's too early for like, based on whatever literature I read, there's not really anything really addressing this. But there is some work we speaks about cosmopolitan realities and how we're living in multiple spaces of modernity. Post-modernity. Some places are just feudal within India itself. So there are multiple negotiations people are undergoing when they're moving between these pieces, for instance, migrating from the urban spaces to the villagers once locked down to place. So these are some yummy, I'll be curious to know as the study progresses. Actually, Benson, there's another question related to your project in the chat. So let me just share it from Kadoorie, right? So she, she asks and says that Bumble has simultaneously been hailed as inclusive and being condemned for being oriented specifically to a heterosexual dating. Does your work intend to look at, you know, look beyond the heterosexual paradigm. Yeah. I mean, there's lots of criticism about like what categories just mentioned. However, I am not planning to go into unplanned. I mean, I'm starting my study looking at heterosexual dating before I go into anything. Because for me there is a literature gap. There's a significant literacy gap even with heterosexual dating. Before I go into the other dimensions. Because we rejoin me and we can you can look at the other side. Yeah. Thank you. Thank you. Appreciate it. Let's have two more hands raised from withdrawn. And then Rama Krishnan, I will go first. Thank you. Thank you. My question is also for Benson and Benson recently, Bumble came out with a set of its own data about what helps you succeed. And I did share that data with you as well. And I was wondering, and it's very curious that the data has been pulled out. I mean, some of it is practical advice like what what information will help you get better matches, like, you know, what jobs do you do or what your interests are, et cetera. Would you like to go for a date? Would you like to go for a coffee? I would like to go for a beer, et cetera. But also things like what zodiac sign gets the most matches. Like, I think for women it was Leo and for men it was Scorpio. This also does say something about our perception of gender and our perception of gender relations. So do you have any insights on this or maybe it's too early to think about it. Thanks for sharing that. That was, that was a fun green because it was just talking about giving practical suggestions about. And it is based on a concept because we have to look at the skew gender ratio in our country. Because they were giving tips about like, what time should you be on the app? And for those that are on the app, it's between seven to 10:00 PM. Otherwise, also, like they were saying like, what are the preferences that works the most? So they're saying like what? Zodiac signs to like, preference for coffee, to like movies, adventure. And so when I was on the app, I had put museums, which is why I think I did badly, but I think it's for us to just written share that with everyone. Thank you. Brent from Rebecca snapped. Can you ask your question? Yeah. Thank you, Rebecca. Thank you all for very interesting presentations. But my question I have one question really, and one remark for humorous presentation. Thank you for that background sigma, but two things. One, in terms of advertorials within Indian journalism especially, and the insidious way in which we can no longer distinguish between what's an advertorial and what's news. I think one of the submissions I have is that to me, a lot of the presentation of editorials in modern Indian journalism today is actually being cross pollinated by methodologies and tropes being used in e-commerce. The way, for example, a certain kind of editorial, editorial is placed within our new space in order to match formats, match presentations, things like that. You will find that a lot of that emerge from the way sponsored items on Amazon, for example, are presented along with our dynamic search for other products that match your search parameters. So that's an even more insidious cross-pollination happening between e-commerce and journalism in the strangest of ways. And that's very interesting to see. I mean, it's a, it's a preliminary thought, but I've been increasingly observing this and your presentation actually triggered this thought a little deeper. The second part is in terms of regulations, regulations and regulatory processes on advertorials. I know, for example, that in the UK, the Advertising Standards Authority has pretty clear rules in terms of how to distinguish an editorial vis-a-vis real news in terms of how you're supposed to mention that it is advertising very clearly and so on and so forth, I think in the United States and please US colleagues, please correct me if I'm wrong, I think the Postal Service actually enforces those rules. The US Postal Service has seems to have a very clear set of guidelines in terms of especially news materials that are transported through the postal service, in terms of how that presentation should be done and how the distinguishing factor should be presented. I don't know if there is one in India. So it occurred to me to ask, is there a process like that in terms of regulatory standards or is it some kind of default? It does. The press council or the who who enforces the rules. Are there any rules at all in India? I'm not sure. It's not an area of really gone into Dino. So commodity You need to unmute. Yeah. Yeah. Yeah, sure. So yeah. Thanks. Very interesting observation about e-commerce and how it can accuse up certain problems for our customers based upon their history of buying behavior. Look at it in terms of the possibilities that it offers for traditional media, they went to limited because you can't achieve that end up precise targeting. Because of the traditional media, both print and television, goes by certain kinds of aggregates. They have an aggregate kind of estimate of what their audience, demographic, response to. The advertiser himself many places and add in a traditional media outlet goes by that very broad aggregate. He's not even for a very specific target. I don't think it's possible for me to achieve that level of targeted. So I know that the advantages of traditional media as it can provide broad context rather than 280 character news. News item. It offers a possible abroad perspective. But in the, in the, in the, in the winnowing process that is led by the hashtag. Each of those large format news reports as being sliced and diced into Canvas. Sub-units, and each of them is being kind of tagged with some hashtag. And so the whole thing is being fragmented and there's a complete loss of contexts. So I think it's a few times we'll have pursued. So you need to get into a different kind of endeavor where you emphasize just want values and seek to, seek to monetize those. How tough that isn't. How many of our news enterprises have the financial resources to achieve that does another question. Of course, our news industry is not very transparent. We can make that estimate without significant insider knowledge. But I think It's something that needs to engage in, not because frankly, the social media, which we all thought would be a great empowering and democratizing influence has kind of turned the other way. Now whether it's social media itself is responsible for that or the underlying socioeconomic, political dynamics are impelling social media in that direction. That's another question. But something that we need to engage with others and personal ads, but instead it's canceled. Yeah, we do have one in India, ascii Standards Council, India. But it's a fairly ineffective, but it's, it's become a lobby for the advertisement. Of course. The other side of the story is that immense concentration that plasma industry, to the extent that there are three conglomerates that control, like coffee, somebody per cent of advertising expenditure on the Indian income. In fact, globally for foreigners. So there is a significant imbalance and asymmetric. And then media industry which is extremely fragmented, tries to get terms from the advertising industry. Thank you. Any other questions? Let me go to the second peak. And if anyone wants to just unmute and speak, please feel free to do that as well. I had a question for Benson. Benson, could you talk a little bit about the founding of bumble? Who are the people behind it. And I could see that some of the advertising definitely has sort of feminist ideals built into them. But could you share a little bit about the founders or the women have, have they expressed their feminism very openly? Could you share a little bit about the ownership side of the political economy of Bumble? Yeah, So Whitney Wolfe was on Tinder. She's the one there was a sexual assault kits and she separated them. There was a settlement and then she formulated bumble. And she has been extremely vocal about this being a different species from that of tender. And that point of differentiation is what drove it to become feminised app, or a 100 per cent feminist app promote. And even in India, this was basically Priyanka Chopra is the one who is driving the, the campaigns and everything for India. And she was, she played a big role in the launch of it. And it has completely, even in terms of people working in Bumble as of now, it's primarily a feminist, feminist female tea, couple of friends there as well. And they are, they are. What, what is interesting that I noticed is the fact that a lot of these things which were seen to be niche with bumble like women first. And those kind of strategies are now even on Tinder. Tinder is using the similar strategies as well. But what do I what differentiates them is the fact that they were the first ones. They were the first ones to introduce that. And it has kind of stayed with them, which has given a lot of the Shorty, do women do assume that this is more of a feminist app? Then say tender or hinge or OkCupid or any of the others. So it's really Wolfe who's the founder, and she broke away from Tinder and alone issue of sexual assault. And she formally to in Bumble. And it has ever since self-proclaimed that is a feminist step. Yeah. Thank you. Bentsen, any requests? I have another question for Shira. I'm unfamiliar with digital cash transfers in India. I'm more familiar with them in East Africa, where it's simply a matter of knowing someone's phone number and they having been registered already in a, usually a cash transfer operation that's run by the telecom in India. Is it more a bank transaction or can you talk to me a little bit about the technology that's used for these transactions. A gym that UPI, PO2, pure chance fluids. So there's Google Pay that is PTM, PTM. Most popular migrant workers will probably, I mean, now they have smartphones. So there has been a bit of a revolution with regard to smartphone technology. I noticed it when I came back from the US and then I realize the proliferation of smart phones and also easy or rather cheap data on the phones which we didn't have and I was a student. There has definitely been a change here. However, with most workers, they prefer their transactions to be through AMPS, which is instant money transfer system, usually through the bank account. So for that, you need both the bank account number and it's something called an IF C code, which is it identifies your bank. The US equivalent would be your routing number. So basically you have to make your account and routing number details available. Yeah, Sure. Come on. That that's actually I mean, I'm just looking at the chat here. He says, WhatsApp has been permitted to start money transfers in India. That's right. And a lot of the workers aren't on WhatsApp. So this will change. But at the time That's one was doing most of the work. They were collecting bank account details. So the cheetah quick follow-up question about your project, which is that you highlighted sort of a structure of care, a structure of kindness that seem to emerge at the time of the pandemic. Could you speak a little bit about migrants have been in, rural migrants have been going to urban India for a long time, right? What is that? A visible or absence of the structures of care in general, you know, on the whole prior to the pandemic? Well, migrant workers sort of on their own. You know, yes, we have the sudden emergence of an NGO focused on helping them economically. But I get the general feeling that they're basically on their own in general, right? So if you could respond a little bit odd on their own for one thing, you know, as soon as she likes to highlight that, there has been very little discussion of labor up to this point between 1991 and up to this point. That itself is a big moment. Then also, swan is not technically an NGO, so it basically known as the m ws. And these are networks of activists. They have been around in the social space for a while doing other things, like say, being with the minority workers, minority pseudo key struggles. They've been active in the MNR EG struggles. They were definitely very active with. They developed something called IP Jan. No, not that leptin, but another kind of we are collecting data and creating databases to make money transfers happen more smoothly. The activist we spoke to who the interview I found most interesting. He was actually involved in the menorrhagia struggles and his vision. He was a migrant worker himself came to Delhi as an electrician, moved back. When he moved back, he found that the mustard rules for the National Rural Employment Guarantee Act, they were not up to date. So he had on-the-ground knowledge of the people who were involved in jobs and the muster rolls that were there. And he found a gap between data and reality. And he connected with activists to find out why this gap exists and what he can do to ameliorate this gap. He became an RTI activist for a person who could barely read. He didn't know how to use a computer. He taught himself how to use a computer. So this, this has all kinds of information labor education also happening in multi-class environments where they are learning how to use computers, use information, collect data, or create data and kid with data essentially. Particular, that's very helpful because, yeah, because it looks like this. The example you talked about shows that someone from the community actually helped create this network. And so that also adds to the idea that it's not always neoliberal, right? Or top down. It can also be an organic formation, right? And so that was very helpful. Any other questions? Anybody else? I'm looking in chat as well. Let's see. No, I think I think does anybody have any last comments or so I had a quick question for so Kumara, which is about really looking at the media industries and the advertising industry themselves. Is there an insider industry discourse? About, you know, how do you separate truth out from, from from false claims? And are they trying to address this within, from within without necessarily talking about government regulation or external constraint. Yes, I think that's the approach that everything should be done voluntarily. And why self-regulation and we have press Cancel that just got a fairly long existence in India, but now it's ineffectual lenders is no mandate in terms of television. It has no mandate to regulate television. Television in fact, grew on the blind side of policy. So there was just literally framework that has evolved. It was just a technological development that had its own momentum. Space. So now occupation has half the lots of the laws themselves. Advertising Standards Council of India is the regulatory body for the advertising industry. They do have norms. They do have norms, not portrayal of women in the use of children and so on. But they do have moms. But I don't think the absorbance on these loans has been very distinguished. We know that there's frequent breaches. Just to name one example, the blur fairness, marketing and media, which is, which is a huge market. And there have been activists who've been lobbying for decades and decades to get this stream out of the market or to stop for the aggressive advertising of this, which promotes all kinds of values. But they've had very little success because the, the company, unilever is one of the biggest advertisers in this economy, right? So that's where self-regulation standard this moment. When I am speaking of a truth. That can sound like an invitation to totalitarianism. But, but you know, what I'm suggesting? That's a debate that we need to begin at this time. It's a deviant that we need to begin in the context of our inability to make a successful, successful venture out of self self-regulation. Thank Kumar, and that was perfect. We're on time to move on to our next panel, and I would like to hand it over to Lucida again. Thanks you too. Q we do not have much time. It's 746, so this is where we begin, is an honor and a privilege to be chairing the second panel. We have three excellent presentations before us. We have Elaine, whose work I've been following for a while. She'll be talking about Indiana University's observatory on social media, which would serve as a telescope into the media ecosystem. Ambiguous. We have Jason human talking about a cross national study of perceived news media importance and the social media importance for fulfilling citizens needs. And we have a rigid who will be talking about public perceptions of local journalism as a public good. So we're very excited to hear this excellent session. I will quickly without further ado, I'll turn it over to Elaine. Do you want to share your screen? Yes. Thank you so much. Let me just see what it looks like. It's working. So that's always good. Let me just maximize this window and press Play. Okay. It's so nice to be here with all of you. I'm really grateful to have an opportunity to talk to you about the observatory. I should probably see a little bit about how I come to this project from, as you can hear, I'm from Scotland. Actually a Russian graduates, Oddly. But after graduation, went off at two Reuters into the world of journalism and traveled around the world until the lens it in Indiana 7.5 years ago very happily and continue to love being in Indiana. And my role at the observatory is an education and journalism focused one. I'll be coming at this from that perspective as I can't give an overview rather than a technical insider overview, which is something I'll be happy to help people with if the contact me separately. But we'll be looking at the nature of this organization came to be, how it supports itself and what his goals are. I do just want to touch back on this idea of singing about the dark times. I feel as if the observer city has, like I said in my subtitle, built a telescope into these dark times. And then my fantasy world, Wendy, we will send astronauts eight into this dark time to fix all the problems. But at least for now, we can see them with this observatories. Work. So sorry, there we go. So first of all, we have to talk about how we raise the money for this center to support it. The big breakthrough was when we want to grant from the Knight Foundation. And this is a screenshot of their home page today, but it's kind of interesting that they're focusing on the insurrection as a sort of interesting moments. And these are additional funders. So this is an organization that has many networks, including funders. As you can see, I won't read these all out, but I think it's interesting to see the breadth of support that this work has attracted. These are the people inside that organization here at IU. I do just want to mentioned that we lost our dear by OpenShift on New Year's Day. But this is our lineup of humans who were involved in this organization where that company, as you can see, of investigators, core staff and students. We also visiting scholars who are helping us to look at newsroom needs, which is something of course, the I, as a former journalist at Reuters, I'm very interested in this is a big part of the application of the research that we do at the center. We also have a rather star studded external advisory board to help us keep our focus on what we're doing and provide external insights into what they think we should be looking at. And of course, this includes people from industry, for example, your roles at Twitter. And we have non-profit involvement from, for example, clear warm up first draft. Other philanthropists, for example, Craig Newmark. And so this helps us build our footprint globally as well as in the United States. Again, on this theme of taking a lot of people to do this kind of work. It is a kind of a snapshot, snapshot of the network of humans and organizations that are involved in the work of the observatory. You can learn all about this if you come to our website, which is awesome. Mentioned is the way we refer to ourselves, the observatory and social media. For nice, awesome. Our website, awesome.edu.edu has all of this information and more. And if you want to find out about the work that we do, as well as do some of your own. You can access the tools that have been built at the center by going to this website. And I'll be talking a little bit more about that shortly. This I have to give a little mention to our new building, which is called the lady center for artificial intelligence. And there it is. So what is the absorption social media. So it's a joint project of the Center for complex networks and systems research at the Luddy school I knew and ourselves, the Media School, Network Science Institute of Indiana University. It brings together data scientists and journalists to study media and technology and society and build tools to analyze and counter disinformation. And when the population on social media. This is a brief but where I have to get the journalistic approach, the who, what, when, where, why. This is some of the solid when the timeline of our recent developments. As I mentioned, we want a $3 million grant from the Knight Foundation that money was matched by IU. And my role in all of this is to help with education piece of this work. And as part of that, we've created a concentration in data journalism, which has just reached full approval stage and we'll be launching as we move forward. I'd want to just mention as well in terms of the timeline, we've built something that I hope we'll have relevance for many decades to come. Given all of the huge challenges that we have ahead of us that we're living through now. So this is our mission. And as part of this mission with see ourselves as having city core activities. These are, first of all research. This is the piece that is less in my wheelhouse, but nonetheless of great interest and relevance to the work that we do. And we meet every week all of the co-investigators, which includes me to talk about all the research that's underway and also our conversation that we're having with scholars. I didn't trace the parties around the world as the observatory and tries to lots of attention. Because of its goal, which is, as you can see that it brought. These are some of the core research questions that we looked at. There are many, many of these, but these are perhaps the most important ones. First of all, how can we help news consumers determine the trustworthiness of information and sources? What rule could machine-learning plea and bad? How does the intercalated cognitive social network and algorithmic biases affect the vulnerability of information consumers on social media. Then finally, what are the structural aspects of the media ecosystem that incentivize the viral spread of misinformation. And of course, these are all things that my colleagues at the Media School. I researching. This all comes into play in our discussion and our work. Alright, frozen, just give me one moment. There we go. Okay, so here's just a couple of examples of publications that have come out recently. Are the leader of our research center is Professor for Mintzer, who's over in the wealthy school. And these are some of the work, this is some of the work that he has been focused on. His work has also won a taste of time Award, which is hardly surprising given the long timeline of these problems that we're examining. This is an example of a more detailed kind of zooming in on one particular paper that was published in September. And Nature Communications, which as you can see, find evidence of political bias on Twitter, which was conservative rather than liberal, on resulted from user interactions rather than platform algorithms. So we spent a lot of our time looking at boards and also looking at what human beings are doing and the work that we can do, that you can do, using the tools, can allow you to do some of that same Research, which we'll look at a little bit shortly. Here are some additional publications just to give you a sense of the breadth of the work that is going on. So as you can see, there's work that's being done into looking at both Twitter and Facebook. Audience diversity and mutual liability. I think this is an interesting one as well. For other day, sticky, a game intervention to improve. Newsletter this in social media, which is one of the tools that you can access through our website, allows players to educate themselves on how to support the information online. You'll see there are many names on here that should be familiar to us as so many of these people are Media School faculty. The second part of our areas of focus, first of all, research. Secondly, as I mentioned, tools. So the big idea here is to use social media to allow journalists and citizens to understand information diffusion, detect misinformation, and evaluate the trustworthiness of news and influentials. This includes more than 130 billion tweets. Several public data visualization and machine learning and literacy tools, as you'll see. So these are the tools. Some of the fun ones are. For example, bought a meter. You can find that how bought like your Twitter handle is, I am very unbaked like I'm happy to report or at least I was the last time I checked. You can also check how bought your friends armies using brought to me, sir. But obviously that's not the real intent. The intent is to allow people to look at Twitter and understand how individual handles are behaving works. It allows you to see how misinformation and disinformation spread online. It gives you a visual representation of what that looks like. It allows you to see ecosystems within the ecosystem that buildup around false information, including fact-checkers and people congregating around false information. And it shows you how the system is mutually dependent in a very quick way. One of our more recent initiatives is something called cool vaccine, which allows you to visualize vaccination uptake. Seen against a backdrop of visualization of information online or does it? Here's an example of us vaccine uptake. And you can study it by state and thereby get yourself a quick picture of how vaccination uptake is fluctuating. This is Hooke's see, this is what happens when you go into hook see. It immediately gives you a search interface that allows you to visualize the spread of information around certain tweets or stories, publications. And then finally, this is the part that I'm most important. The third leg, our research center is of course, the education leg. This is the part that I'm excited about. What's all that exciting club, particularly focused on the education side of it. I don't ambition, as it says here, is to position future reporters to uncover newsworthy information that is otherwise invisible to public scrutiny and empower citizens to navigate their weight and formed participatively behavior. As part of this, we have launched, as I mentioned before, a data journalism program with the goal of developing competency and storytelling. Two-minute. A strong emphasis on writing and visual communication is still there. But also adding onto that data science tools and technology. Now of course, this is something we're all interested in, but we're trying to have a very sharp focus on in addition to storytelling, writing and visual communication skills like coding data visualization with, but not forgetting about the importance of ethics. And so on. The way it's organized is that students will work with both Media School faculty and faculty in the school who have expertise in computational linguistics, network science, data science. And there is an additional advantage in the media school because our students will be able to publish their work or at least collaborate with our new Arnold Center front desk. It's journalism. As each student will produce a capstone project. And also will be expected to participate in one high-level industry internship. And that is that is absolutely amazing, Elaine, thank you so much for this fabulous presentation. I have a knack for bonds, so I'm going to just say it, awesome is really awesome. I have a lot of questions, but I'm not going to hold up the floor. So I will transfer it across to Jason. Jason who will be talking about today, pronounce the trade to feel free to correct me. This. He'll be presenting on a cross-national study of perceived news media importance. Social media important for fulfilling citizens needs. Over to you, Jason. Alright, well, good morning, good evening. Thank you for that introduction. I trust you can see my slides okay, In terms of the full screen. Excellent. Thank you. So this was described to me as kind of a meet and greet seminar. So I'm going to approach it in that way with with, without necessarily going deep into research methods and some statistical findings and so forth. Rather, I'm going to talk in broad terms about a key facet of my research agenda over the past ten years or so and outline different aspects of it and where I see it going. And hopefully maybe that spark some ideas and comments and maybe even some interest in collaboration. I would love to hear some of your thoughts in that regard. For its just a few things about myself to get some context. My eye, I am course in the Midwest right now. Chile, Indiana. My roots are in the East Coast of the United States, Philadelphia region, and that's where I lived and worked for time. I actually worked in terms of my journalism background in local public radio. So there's a couple of public radio stations in Philadelphia that most notably I worked with W RTI, but also did some stuff with them, another one, and these are both NPR affiliate. So if you know much about the public radio broadcast, that structure. So that's, that's my background and some of my passions lie both in terms of media, but also, I certainly have a lot of fondness for Philadelphia, but I have been here at IU for six plus years. I'm in my seventh year here in the Media School. And my research predominantly looks at the degree to which citizens have uncertain. And it's certainly relates to questions of trust in public institutions. Now, that doesn't strictly pertain to journalism, but that's where a lot of my focus has gravitated. Journalism as a social institution, but certainly I'm also interested in uncertainty about other institutions. Political trust and so forth. But today I'm going to, I'm going to highlight that facet of my research that really looks on public perceptions and their uncertainty with in some ways, journalism's, journalism's value. So I'll talk a little bit about the origins of it because it informs my research orientation in some respects, even now, the origins of it, they didn't necessarily start in journalism per se. And then I'll highlight some basic insights and talk about future directions. So the concepts that I'm talking about, the idea as what I call perceived news media importance. And so it's certainly, there's a way that I measure this and I'm glad to talk about that. But I'm not stuck on a particular measure. It's more of a research orientation for me, a way of thinking about issues of attitude importance. And so my entry point for this was, was, as I said, not so much journalism, but it was actually, I would say comedy in the vein of Saturday Night Live. When I was kind of waiting into the graduate school seen more than ten years ago. Now, I was really captivated by SNL's parody of then Governor Sarah Palin. And of course, she was the running mate of John McCain in 2008, running against Barack Obama. And so there were parodies and SNL did of paling with Tina Fey, a comedian. And they got a lot of attention. And so I started to do some research and political parody. I was really intrigued by how these, these representations in this form of parody, of imitating but offering commentary in that. What were the implications of how to think about that? And I did some qualitative work on this, but also on this topic of political parody, have done some experimental work and looking at how that may be impacts political trust. But I really kept returning to this idea of parody and political parody. And if you start thinking about that lends itself to thinking about news parody, right? So not just parody of politicians, but parodies of the news format,