Okay, here we are. I'm Johnny looky says, Welcome everybody. I'm an associate professor of digital media in the School of Literature, Media and Communication, also part of GPU. And I'm, I'm very excited to introduce you to share Thorpe, who's going to be our speaker today. I'm going to say a little bit about Jarrod before we get started. Is an artist, writer and teacher living in New York City. He's probably best known for designing the algorithm to place nearly 3000 names on the 9 11 Memorial in Manhattan that some of you might have visited. Care has a long list of accolades. He was the New York Times first data artist in residence. He's a National Geographic Explorer. In 20172018, He served as the innovator in residence at the Library of Congress. Very cool position. T has been named one of Canada's greatest explorers by Canadian geographic. It's really no exaggeration to say that chair is one of the world's foremost data artists. And N a vital voice or the ethical use of big data. When he is at home in New York City, he teaches at the Interactive Telecommunications program that some of you might be familiar with that NYU. And Jerry's book, living in data was published recently in 2020. I'm just going to tell us a bit about it. I've known Jair for at at least and six years. I think. I remember us meeting just before each of us was about to have our first child? Honestly, I don't remember much before that, so apologies for that somewhere previously. But since since we met, I've really been following his career enthusiastically. I, you know, I really never know what he's gonna do next, including writing writing a book. And it's, it's certainly not what I would expect from a book about data. It's intimate, it's moving. It's funny, it's poignant. It has chapter titles like drunk on Zemo, the right show, and paradox walnuts. The book has, has been lovingly reviewed by many people. You know, i'll, I'll, I'll, I'll read it. One of these off the back cover of the book from Stewart Butterfield, CEO of slack. Rights, if any, Dillard wrote about data, it might sound something like this. In turns, insightful, hilarious, techie, inhumane. Living in data is an essential book for anyone who's wondering how exactly we got into this data mess. And thinking about how we might dig ourselves. I would then thinking about, you know, what to say about Jared today, it occurred to me that I could call chair the Indiana Jones of data. But Indiana Jones is a terribly outdated notion of what a true Explorer can and should be. Chair is not only brilliant, an adventurous and of course charismatic like Indiana, but he's also one of the, really one of the most compassionate, ethical, and thoughtful artists I've ever met. So I hope in his next movie, Yes, I've heard there's another Indiana Jones shot. That Jones is something more like the chair Thorpe of archaeologists, action heroes. So with that, I'm going to turn it over to share. Please put any questions you have in the Q&A. You can also use the chat. And I will be monitoring that. We'll finish up at 120 today. Thanks so much for being a, hey, thanks for that introduction. Johnny and I are, are indeed old friends that, that is, we are both 0, then we are friends. And when I, when I wrote this book, I was really looking forward to, to doing these types of talks. And we kinda gotta make do with the fact that we're not in a room together. I don't think I've seen the ID and a couple years and it feels like a particularly long distance even though we're not too far away. At the moment, I am going to share my screen here. There's, there's yeah, you know, it's, it's, it's interesting. I always want to start these talks by saying, it's nice to be here. But of course like this here that we are in is. This is a constructed here. We are island in quite different places right now. But we're going to try over the next little while to make a here for the next I don't have I mean, how many minutes we have an end because it's like a temporary thing we're making. If you have questions that you didn't get to ask or comments that you didn't feel like it was appropriate to, to spit into the chat window. Please feel free to reach out. I'd love to talk to you. And then hopefully at some point all of us will get to be in a room together. And these come over and tell me where I'm one of these virtual things and I can that I don't know. We can like high-five or or whatever that the conditions of contagiousness at that point allow us. I'm in Brooklyn. I a live right under the Manhattan Bridge. Nice place to live, particularly on day like this. It's really a super beautiful day. I just came back from birding in the park. And I wanted to start with an acknowledgment that where I am right now is the ancestral homeland of the RCN months. He'll unhappy people. If you have a minute to go to native VLAN dot ca and, and just kinda check out some of the indigenous histories of the place that you are right now. That would be wonderful. Then. You, when you were doing these types of talks. And in real life, I think it's always hard to even consider the idea of introductions, because if you started introductions, then by the time you are down the hall, talk would be finished. But if you want to just chime in, in the chat and say who you are and where you're coming from. And be nice chance for us to get a sense of who all is here in this weird here together today. I am I had this this this kind of GEF delivered to me in, in 2013 that I wasn't expecting it in. Yanni mentioned it a little bit, was named a National Geographic Explorer. And that's a blind process. You don't know that it's going to happen. And it was such a surprise for a data artists to be, to be named a National Geographic Explorer. But one of the things I'm most grateful, or is that I sort of decided to take that opportunity and jump in with both feet. And it started getting out into the wilderness and doing work that involve data and, and kind of real wild places. And as a kid, I had been really into nature, but that for whatever reason kinda went out of my life in my late teens and early 20s. And so for nearly 20 years I was, I think the word the word is nature blind. I was not good at at, at seeing what was around me. But now, thanks to that and thanks to this kind of new pandemic practice that I have a birding, I've been able to get out into the world more and, and my park has this plant, which is a plant that I, I grew up with his well, it's because these hitchhiker plants, their seeds are specifically made to stick to you. And I would come home. And I still come home with my, with these things stuck in my socks. And I've come to think about these things bound really closely to the books that I wrote. Because the book is very much about things that have been stuck in my brain for the last 10 years that I've had a hard time working, working out. And then also, the book is designed to kinda take you through a story and to leave these things on your socks as well. These, these things that are going to be up to you to kind of carry with you for a while, take to new places. And that's really what I hope you get out of the book if you read it. It is in bookstores right now, but I should say that it's also available in libraries. So if you want to go grab it from your school library or you public library, please, please do. So. I thought I would share a few projects. The first ones are not projects of my own, but there are projects that are featured in the book. And these are very, very, very much for me Bert projects. These are things that stuck to me. Or in the case of these next two per decade. And I would I would teach them and talk about them. But I think I didn't really have a good understanding of why I was so obsessed with them. And so what I want to talk a little bit about today is like, I want to share with you these projects and then I want to talk about what that real thing was that I that I was interested in picking apart and getting at. This is James Yorker. He's the director of a theater company in Birmingham in the UK. And the theater companies called stands calf. It's pronounced calf, but it's spelt as you might spell the word Cafe. There are really wild company that does all kinds of really seriously experimental theater projects. And actually the first theater, the project that they did, which was this really amazing. I'm performance for one person. That it was really successful, touring it all around the world. But he had grown up in this really small English town and was certainly didn't consider himself to be a cosmopolitan person. Rarely kinda been outside of the town, let alone outside of England. And he, when he came home, just kinda blown away as many of us as first-time travellers did by the size of the world. And specifically he became obsessed with this number, which was the population of the world at the time. That was around 7 billion. And so he was teaching at university to time and he assigned his students this job to try to find a way through, sort of perform a sort of sculpture or something physical to represent that huge number, which was the world's population. And they all came back to him and said it was more or less impossible. Because anything that we can kinda recognized as an object, if we did 7 billion of them, it would be too big. And if we try to aggregate, like make one object equal 1000 people or something like that, then we lose track of what that number actually means. So James is not a person to give up. In a few months later, he was at the grocery store buying a bag of rice and he thought, aha, they went home and he did some back of the envelope calculations and the numbers in the bucket. I can't remember exactly what it was, but it came out that it would cost like somewhere in the Euro, a 100 thousand British pounds to, to Beida for ice to represent the world. But again, sort of not taken aback by that. He started out with his theater company on this performance which is called love all the people and all the world. And the root of this performance is that there are piles of rice which are being counted and assembled in this, this big public space by these actors wearing these bureaucratic uniforms. And so it's a space for counting and it's a space for people to understand the scale of numbers. And so each one of these rice piles that's being constructed in this, in this space are a statistic represented with these tiny individual grains of rice. And, and it's just this wonderful show that of comedy there. Some of these are really, really funny, but all the others, The them are really poignant. And what it really is is, you know, if you can imagine if the city had a bureau of counting and you could kind of visit it and, and get a chance to understand the numbers that you were reading in the newspaper. This is kind of what it would look like. And in, during COVID, I've been thinking about this project even more because every day we're faced with these numbers, we know, for example, that the more than 700 thousand Americans have died of COVID. It's very hard for you and I to grasp that number. Our brains aren't built to grass numbers of that scale. Yet we're expected to make decisions based upon them. In the same thing goes with our municipal, federal budgets. The is that that Yeah. So beyond our human capacity that it's hard for us to understand. And yet, what this project does is it allows you to understand numbers at sort of smaller and larger scales and get an understanding of how they compare. And a feeling of, of these data points. Not as, as a series of digits written on a piece of paper, but, but as real and definable quantity. A few years after James had this idea, he did have the chance to, to finally answer his question, which is, what does the world's population look like? And this is the pile of rice that represents, at the time I just under 8 billion humans. One of the things that, that I was really interested in a fluid it to Birmingham to interview James for the book because I was, remained to be a little bit obsessed with it. But why it really resonates with me and why it resonates with people that have visited it so deeply. And James thought about it for a second. It answered that he really thought it had something to do with the shape of these rice grains. The grains are oblong, so they do, they're like little humans. You, everything about this piece is wonderful, but I would suggest a few things to keep in our head. And that is that it occurs in a space that it allows a kind of social understanding of data. That you're not there alone. You're not standing in front of a screen. There are these actors there that are both facilitating and giving you some sense of the process of counting as well as the result. And then finally, this is something that it curves over a period of time that we don't usually associate with, with the telling of data. The performance lasts for weeks. And during that whole thing, it's this kind of construction and even your own visited this thing is not the kind of 1020 seconds it will webpage, but the kind of multiple hours of a gallery performance. Well before James bought his first bags of rice in Birmingham, the artist and engineer and in provocateur Natalie Gemma Ginko cloned several 100 pairs of a type of tree called a paradox walnut. And these little saplings, each pair of which are all of which were genetically identical, were then planted around the Bay Area in San Francisco. They were planted by school groups and by community groups and by artists in, and in. Various There were there I don't I cannot find a number of how many were planted, but certainly many dozens of these trees were planted around the Bay Area. And the idea of the project was quite elegant. Because these trees which are genetically identical, any change in the way they kind of grow and thrive or don't thrive would be to do with the built environment and the natural environment around them. To a tree that was planted in a park where it's watered often is going to grow like kinda well and Hardy. A tree that might be plant or an industrial area might be this little kind of stunted tree. And of course, there are events that happen to these things. There are areas that get redevelop, these trees get cut down. And Natalie, Natalie understood these trees and she described them as social registers. And the idea was that over a period of years and decades and even centuries, these, these trees would be recording data about the conditions of the city. And they will be presenting them not through some type of graphical visualization, but through their leaves and their branches in their trunks. And that to read these things, you wouldn't be visiting a website, but you would be walking around the city and you would be touring this kind of path of from tree to tree. It's a beautiful idea. Like a lot of ideas that were part of somewhat on the web and the 990s, it more or less had disappeared by the time I got interested in it. The website actually was alive when I started writing the book, but by now it is, is not live anymore. And even when it was live, you could find only these 150 by a 100 and 50 pixel images of the trees. And there was no real map. And so it's actually quite hard to go and find these things. But I did spend a day walking around the city. Looking, looking for some pairs of trees. I found 484 pairs of these trees. Her now these kinda much grander specimens in there. Well, there were some disappointment to me that the project didn't unfold in the way that it, that it was imagined. There was also this kind of exhilaration that came from understanding and reading data through my body and through this act of walking through the city. If it's seal, the information that I learned in the sourness have my legs, which was something that I found to be really captivating. There's a pair of the trees in the fall. And specifically for Natalie, This project was about really stretching the ideas of of how data can be told over time. How a slow telling of data and my mesh better with the kinds of faster than we want them to be, but slow changes that we're seeing in natural systems. And so, so these two projects really carried through to a series of work that I did with my studio that I ran for a while in Brooklyn called the Office for Creative Research. And I'm, so I'm showing this slide really intentionally remind you that, you know, there's, there's really no such thing as like the solo artists, like everybody has support. In this case, these projects that were not done by me with these people supporting me. They were like these real collaborative projects. Different people lead different projects and I'll try to mention people by name where I can. This, this, all of this stuff is, is built by teams. So the first one that I'll show you is this project that we put in the middle of Times Square in the spring of 2017. It's called we were strangers once too. And it was designed by noaa yachts and Genevieve Hoffman. This sculpture from the front looks like a heart. It was placed in the middle of Times Square for Valentine's Day. But as you come around the back of it, you realize that it is indeed a data sculpture. The data that is encoded in this sculpture are these, These numbers of the foreign born population in New York City. So New York City is actually the largest, has the largest population of foreign-born citizens, both by number and percentage of anywhere in the world. And so, so we kind of trick people. It's like I'll look at that beautiful, beautiful heart. I'm going to go take an Instagram and then as soon as they get closer into it, they're like, Oh my God, I'm in a bar chart. Like, how did that happen? And I love, I love that idea that you could surprise people with data in a way that's probably pretty hard to do in any other context. And what I love most about this project is the way that people would, would interact with it. And they would interact with it by taking a selfie. This is like millions of people did this, did this during the run of the project. And they did it. They would find a country that either they themselves or somebody they love had a connection to when they would take a selfie in front of it. And there's something beautiful hear about these types of connections that are being made from person to person through a data point. And, and this is this particular experience that's in this photograph right now, I, I think holds a huge amount of promise and a huge amount of potential for the ways we might think about getting people to care about data. That can we get people to care about data? It's hard to get people to care about data when we're expecting them to digest it through a chart or graph. But it's maybe a little bit easier when we allow them to facilitate these types of personal interactions. Right around the same time, we staged a series of performances at the Museum of Modern Art. Where, where this group of actors that we work with are called the elevator repair service would, would perform these 40 minute performances. There were eight of them in which everything they spoke was verbatim from the database. So they were really in a real and true sense, reading the database in a gallery and we would write, we wrote a series of algorithms and wrote some handmade scripts that would present these, these data points in ways that would peak to the materiality of the artwork, the politics of the institution, the way that things had changed over time. And, and what I love most about this particular project is that there's this really direct circularity where we're taking the artwork and about the institution and we're putting it back in that place where we're bringing it to people in a way that that is not what they expect, that nobody expects when you hear that, you're gonna be exposed to some data for people to be performing or singing that data to you. And by disarming people in that way, I think we were allowing people to engage with the data that's in much deeper ways than we might otherwise expect them to rate around the same time we climb we climbed up that Glace here in Banff National Park outside of Calgary. And we installed a seismic observatory. Though this is a set of sensors that sit on the rock bed next to this glacier, which is called the bot Glace here, and they record its movement. So glaciers do they melt and they crack and they pop. Ice, ice blocks will shift in, the whole thing will slide down the hill. There are actually these much more noisy and alive things than we might picture. And so we take that noise and aliveness of the Glace here, 247 and, and, and we bring it to a plaza in the middle of downtown Calgary, where it's represented on a 30 foot by 30 foot tall LED light sculpture and then brought into the plasma. Hello there as a 16 channel surround sound system that exists in this gigantic Plaza, which we've decorated in stone with our allies. And the idea of this piece is that you can kinda see these people walking through the plaza like these are not people attending an art opening. More going for, people going for the train, going to the bank, going to work. And the intent of the project is people a little piece of communication with the Glace here during those times. And to have those small sections of interactivity stretch over years and decades and over careers, over childhoods and such that people can kind of help, but to build a bond with this, this natural thing to the Glace here is of crucial importance to the city. More than 40% of the city's drinking water comes from the place here and its watershed. And yet most people either haven't visited or at least it's not something that they hold in their mind. Definitely not an a daily basis. So as we're approaching this challenge, this particular challenge about how do we get people sick? More about natural systems? I would suggest that one of the problems with the way that we've approached this up to now was that we, we expect people to make those kinds of deep and meaningful relationships. Very, very, very short pieces of time. Like I meant to kind of read a chart or, or look at a scrolling website and come out with that with some feeling of connectedness. But I think we know as anybody who's kind of struck up a friendship or fallen in love, that these things do not often happen in those short periods of time, but they take repetition and persistence. The other way this piece exists, as well as of course, as a kind of living wake for this Glace here, it's receding dramatically and chances are that I, 50 years from now, the glacier will have receded well past our seismic station. And, and while you might get the occasional popper from that station, that plaza, the light sculpture itself will be silent. The forcing the city as well to reckon with their own role in that silence. I'm going to, I'm going to end the talk with a project that Yannis certainly knows a whole, whole lot about. And maybe some of you have also heard about, which is the St. Louis Map Room. 2017 was a busy year. We did this project then as well. In 2018, I started writing the book, so, so I haven't done these types of projects little while, but the idea of the map room was to build a space where people could come and explore data about their own city through their lived experience. And so you'll see some things borrowed here from the right show that I started the talk with me. This is a large open space. It, it, it, it kind of feels like a surprising institution that you've walked into. We had facilitators as well. They weren't in costumes, what people, people were who in this space, it's a very large space. And the idea was that people would come in off of these ten foot by ten foot maps about about their lived experience in the city. And then. We had, were so lucky to have a really talented facilitator named Kata draw, who, who would lead people through the experience of kind of using their drawings. They're there, they're hand-drawn maps to understand pattern in data. The truth is if I show you some data on a map, you're going to do exactly one thing. You're going to find yourself in that, in that place, and you're going to look at what the conditions are for your particular household. What's hard to do is to consider the data lives of others. And so you're doing these social environments, these, these maps were made in groups of ten to 12 or sometimes lastly, things around six. You would be forced to kind of understand that other people's experience at these data sets was different than yours. And not only that, when you are finished doing your map, you could take down a map that another group made. And then you'll start to see that the, the city through that lens. And so we ended up with about 30 of these maps made by different students and community groups and organizations you each with, each with their own personal story to tell about the geography of the city. That this library which now lives in the cities official archives. Is this, This Citizen made that of, of instruments that are meant to, to, to be able to tell very specific stories about the condition of St. Louis in 2017. I want to just take a moment to talk about this group. This is a group of girls, mostly girls from a school called Brittany Woods, which is in St. Louis, West side. And they came down to the map room. They'd worked with their teacher and advanced says all the school groups did with the curriculum that we developed. And they come up with this map, which was of what they consider to be the safe and unsafe spaces in there. And they're kind of ten by ten block chunk of the city. And the facilitator, it's kind of walk them through all the different map layers, historical maps, census maps, et cetera, et cetera. And what it turned out that they ended up being most interested in was this map which is projected onto theirs. This is 930 one map. These is called redlining maps. These were maps that, that gave financial, government, financial institutions guidance about, about loan forgiveness in the wake of the Great Depression. And so green areas where places that they might forgive people's defaults on their, on their home loans. Whereas red, red, and yellow glaze, where that was more unlikely to happen. And what was really amazing to the students was the idea that the boundaries that were drawn back then were still visible in the map as it existed today. And, and what they quickly realized is that they also knew these boundaries in their everyday lives. And I specifically remember one girl telling me that in once you cross the street in one particular block on the way to school, there was like really well kept sidewalks on one side of the street and really kind of cracked and broken sidewalks on the other. And she could see that boundary not only in that red lining that but in the census maps from 2016 in indeed in almost every map that we put into the, into the context of this. So there was something really wonderful in this. And, and, you know, the idea that we could get a group of ninth graders engaged in civic data. And, and in about systemic racism and historical segregation through data was really astounding. And, and I think the reason that it works is because we allowed them to start with, with methodologies that we're really comfortable with that to them. So drawing and painting and stickers and, and color and then prove that we brought them in. And two, that the understanding of, of data and they went back to their school and ended up doing this half-year long project about red lining and really learned a lot about the process and their neighborhood. Do you know all of these things revolve around a central question that I've always had, or maybe a central suspicion that I've always had that the ways in which we communicate data are insufficient with the things that are happening with theta and r lies. And when I started to write the book, I, I was really interested in what was happening with the word data itself and how its relationship to other words was changing. And so I felt I had downloaded 400 million words from the New York Times over four decades. And I created this system that allowed me to investigate out certain words. We're moving closer. The word data, that is, they were more often being used in context of data and how certain words where we're going further apart. And so the words that are there, moving further away are words that we normally actually would, would think aren't very close. The data. Things like information in digital and software and network, which maybe tells us about the fact that data is becoming less of a computational thing and more of a social thing. And indeed, if we look at a set of words that are coming close to data, yeah. 20, because you could pick any three of these that have a headline from the New York Times today or any given day. You know, these things that are much more about our own lives, our own sort of existence as people who do live in data. Along with these and a dark words, there was this set of words which really, you know, these words stick with me, lives and deserve and place and ethics and friends and play. And you know what that really suggested to me. And the reason why I think I wrote the book was that there is a chance for us to, to move data in, in a much different direction. And one of my heroes, bads, who was American labor activist and a writer and all kinds of different things. And they're not last book she wrote before she died was called The Next American Revolution. And it was about how we might find a future in this country and elsewhere that might feel a lot different than the one that we, we may be careening towards right now. In this quote in particular, became a real core of the book because of her call for more participatory and place-based concept of citizenship and democracy. And, and, and that, that is really what it's all about. And what all of this work that I've shown you today has been about. And the reason why I'm here to talk to you is that I think there's an urgent need for us capital, U, capital asked to imagine these things in what they look like and how we can bring more people into the data conversation who were not involved right now with a specific focus on people who are being marginalized from these systems as they exist today. And so I'll leave you with a question that, that, that is really the central question of the book, which is a question you can ask yourself. And I want you to ask yourself this question in the present. And I also want you to ask this question in the future, though, for you in, in 30 years or for your children and 30 years or 50 years? What would we like the answer to this question to look like? All right, I'm going to stop there and we can take some questions if there are any questions. That was great. Thank you. Chair. I'm going to I'm going to take this opportunity to ask the first question. And I encourage others to put put their questions in the in the Q and a. But, you know, I want to ask you a somewhat selfish question. You know, as somebody who's, who's a teacher. And as I said, I have long admired your work and, and I, I've never had the opportunity to be your students. And I've always wondered what it's like to, you know, what you're like as a teacher and what your students get from working with you and I, and I, I bet a bunch of other students who are on the here with us are also wondering that. And I wonder if you could tell us, what do you, what do you feel is the most important lesson that you impart to your students? Based on, I start with this great stuff to share. And crucially, what do they need to do to learn that lesson? Wow, that's a great question you should be asking my students discussions and not me. Anything. Ways he E is for me, teaching has always been a real part of my practice. And I always, I, I do this thing. I make it really hard for myself because I mean, it's like I comfortable teaching a class and I kind of know I just, I move on to something else. And the reason for that is because they learn by teaching. And I like to actually teach things that I don't have a full understanding of. And I, so I, I taught a class called data art for many years. Then I got, I taught a class called data publics. And, and actually while I was writing this book, I taught a class called living in data. And it was like, like, can we collectively start work together on these questions that, and pick apart those sticky things that I was talking about. I end the book with this, with almost end the book with this JM klutzy but cozy quote which is about an M and a paraphrase the quote, but it says, let's not think about how we got to the other side of the river, but let's imagine that we're already there. But let's not think about the trials of bridge-building and how hard it was and how we solved all of these questions. But let's, let's think for a second about how we're already there. And those types of imaginaries can be very difficult. And I think when you're investigating things like data and ethics and data and fairness and data and equity. It for, for, for many very good reasons. It seems inevitable to be kind of caught in like our terrible things are right now. And, and what we don't do enough of is we don't do enough of imagining what those futures could look like. And then, then, you know, maybe I hope one of the most important messages in the book is that let's say we're in a tough place. And one of the reasons we're in a tough places because all of the language about data. All of the metaphors about data, all of the technologies about data were all made by the same people. And so even when we want to talk about these things were kind of bound into, there are ways of thinking into their language. And so one of the real difficult things for us to do is to untangle those things. And and so those are, those are like the core lessons that I always tried to paint to my students is to, is to, you know, I know that you, you, Jati are involved a lot in meditation and it is in some ways a kind of similar practice where you need to be able to remove yourself like now, come out of your thinking about technology is such that you can look at how you're thinking about technology and the types of words you're using and so on and so on. And so that, that, that to me is a real crucial point. And that's, that said, I think I, you know, I like my teaching to be engaging and fun. And the class that I taught last year, it's called how to count birds. And I'm teaching again in the spring. And it's, it's about how you build an observational practice around birding, but also how we can engage with birding datasets in the context of climate change, it, and conservation and so on and so on. So like that, That's a class that I'm really excited about because I don't know that much about, about about what those ideas are going to end up as. Perfect. Thank you for that answer. Ok. There are a couple of other questions that I want to get to Anthony asked in the Q&A. Let's the this is from from during the talk. She writes, I feel the same stickiness on the idea of visualizing the number of people on earth, kind of referring to the, the nice project. Is this the same as trying to understand at a greater scale the vastness of space, the eons of time is the attraction just to numbers. So what is it now data that, that has this stickiness? Yeah. Well, uh, hey, you didn't when I started working with data, I was I always felt like I always tell people that there were three things that would get me interested in a dataset. And it was like if it was big, if it was time-based and if it was networks. So if there were like connections within it. And so there's no question that in my mind, and this is me speaking personally. There's something I'm attracted to about like these very large datasets. And I think it is because it, it, it challenges our tools that we have to represent quantity, right? We, we represent quantity in very specific ways. And getting, getting out of those spaces. Can, you know, it's hard, but it is also fun. In the Anthony's sort of asked about whether it's the same thing about all these other metrics like how big the universe as such, I, I would suggest that it's not. And the reason why it's not is because those rice grains, her people. And so that specific number, it feels challenging for us in, in an extra way, in an emotional way because we understand that those are other souls, right? Those are, those are other people who were all living their own, like their own individual realities. And so one of the reasons why I think the ratio works so well rather than kind of visualization on a screen or something like that, is because of the human involvement. It does feel like a very human thing. So that will always be a magic number. It will always be a kind of mysterious one because of the fact that it is us, that, that number is, is humanity. And, and, and you know, I wrote, I wrote a few months ago about, about the kind of long challenge we're going to have about memorializing COVID. And I think there's a, there's a stain, There's a similarity. There were, were, were, were not only do we have the task of representing these gigantic numbers, but we have a task that's kinda solemn task of giving them that kind of grace that they need. And and I don't know what that looks like, but it's something that that we're all going to need to think about. And yeah, it is. So so that's a long answer to the question that I do think there is something special when we're talking about people. We have another question from Ajay. Who asks, what's the most impactful live data display? You see? O live data. Move, maybe real time. Yeah. Oh gosh. I wish I had a I wish I had an immediate answer to that. But I but I don't think that I do off the top of my head and I think part of the reason is that all that stuff can feel. So dashboard dashboards are always hard for me to kind of got to get out of out of a kind of analytical frame of mind it into something. Here's one that just popped into my head and I just loved. I don't think it exists anymore, but it was, I think it was called emoji map. And it was this real-time popularity list of emojis on Twitter. And so you would literally just see like every time someone tweeted an emoji would see these like rankings change. And I just don't remember watching that. And, and, and like just getting the sense of you could watch it over time and see like when it was lunchtime, that would be more sandwiches coming in and like, kind of dirty emoji. I like drinking emojis. Say it was this really kind of it. This amazing window into this social media that, that kinda got rid of almost all of it and the left, like this, this one little part. And I think when Twitter changed their API access rules, that no longer works. But it was, yeah, I thought it was really special. It was something that I like. I bring a real meaningful answer to that question, but sometimes they can just pick a fun one, right? That was something that I really loved. That for me. That brings up this problem of the memorability of visualizations. I'm always ask my students, how can you make your work memorable? And you know, what are the things that really struck me when you were first talking about your book and texts. But your book launch was that you said you were probably most affected or impacted by novels that you've read rather than, you know, data studies, theory or technical, you know, theories. And makes me wonder and I love that you use, you know, use some of those elements like historical fiction, I guess I could call it took to write about some, you know, some, some parts of the book. And I wonder, what would it take for a data to display a representation to feel more like a novel and that we could remember in that way. That would have that kind of that would hold. Yeah. Yeah. Yeah. And I talked about that, I think a little bit about the idea of persistence. We, we, we have this kind of dream that we can land, we can land a job in that and that in this very small time we have of somebody's attention. We can, we can, we can imprint in a deep way. And so much of that as this goes back to what we were talking about before, but understanding the kind of structures that in which that the browser is an ad delivery platform. That's like websites are ad delivery platforms. That's what they're therefore. And, and you know, the advertising believes PR writer for Ron and the idea that you have to capture people's attention very quickly. And so, because we've been forced, most of us still to work in this medium. We also can't help but pick that straight, right? That, that like we have to, we gotta go quick and we gotta get people fast. Your question about novel, a novel or like do you think about serialization? Like how do we, how do we get to people over periods of time? Is something that that your project that I showed you and is a question that I have. I don't know that I'm have a good answer for. And I think one of the reasons why I wrote this book and was was that that the book, which is a 300 page thing, give us the capacity to tell stories that, that visualization does not. And so though, a lot of the things that I really wanted to talk about, this was a medium that I, that I, that I wanted to, to explore because it's has its own very unique strengths. It has a lot of weaknesses as well. But, you know, and I do, I come from a really strong fiction background in that. That's like more or less all that I read that the three years of writing this book I wrote, I read more non-fiction that any of the rest of my life combined because I was reading a lot of references in tiny. But now I'm getting right back in to, to, to fiction. And I think now that I've written this book, I'm paying even more attention to the way that narratives or construction, or narratives are constructed and how we might borrow some of those techniques to, to engage people with data. So I've been thinking about this a lot over the last couple of weeks. And that is that we put this incredible burden on the audience, right? We expect them to be able to be literate enough to understand our graphics, but we also expect them to care and the way that we care like this may be news to you. But for most people, a graph is not very engaging. Like, I don't care how pretty the graph is or whatever for most people it's not. And yet I find what we do is we make these beautiful things and then in some way, shape or form, we blame the audience for not, for not getting excited about them. Yes, Someone asked about climate changes. Like what can we do better? Like we we keep on making these. Really clear graphs are people and there's still no changing their behavior. Like people don't care about graphs and we need to like, we need to get that in our heads. They're probably better, better and more difficult ways than we need to engage with people. And, and, and I'm not suggesting that all of us kinda go out and build data sculptures or, or you know, to data performance is. But what I am, what I am suggesting is that those things maybe give us glimpses of what methods of engaging with people that aren't going to be much, much more effective. Particularly outside of communities where way, where people might actually get really excited about graphs and charts. You and I, we work in tech. Most people on this call are probably in a university. We're in rarefied spaces. And so like when you're out in, if you're in a church community in, in, in, in a poor area, the city, how am I going to speak to that congregation about data? Like wonder with the ways in which we can engage. The answer is not to expect those people to get better at reading charts. The answer is for us to get better at, at like understanding the already successful ways to communicate root in those community center, those types to those types of people. You know. Yeah, That's such a great point and I think brings my mind back to this. You know, that the skill of storytelling that you know, and, and I think that's something that you do so well, you really bring that to your work. You know, you're, you know, I would hardly call you just like a data visualization person. You tell stories with data and about data. And I think that's, that's what sticks for people. The story. We do have to wrap up, unfortunately, just because people need to get to class and I want to let them go, but I just want to thank you so much for taking the time to spend the afternoon with us and tell us about your thoughts and projects. And I hope everyone will come pick up the book. It's terrific, It's beautiful. It's really quite an amazing object and it has all kinds of incredible visualizations in it that were, that were custom made for the book. I think one of the things I was or I expected to see like, you know, some of your past work in here, but you made all these new visualizations for the book. And you really took it seriously as its own project and, and, and its own medium. So just wondering, Yeah, maybe I'll say it again that it's available in libraries everywhere. And I think some people maybe aren't aware of this, but like every library will also learn you an e-book though, and an audio book. So it's an audio book as well. And so you can go to your public library wherever that is and, and, and sign up for the e-book or the audio book, which are also ways that you can, you can enjoy the bucket. They will never, I always tell people, but some people sometimes feel bad about like not buying the book and getting it from the library. But every author in the world. When you sign out there from a library, like go, go get it from the library. That said, you know, holiday gift giving season is coming up soon. I went for something that they don't ask us. Yeah. Library doesn't have it. Ask them to purchase it. Yeah, exactly. Okay. I see. Thanks. Thanks everyone for coming to care.