Ethan Mollick is an Associate Professor at the Wharton School of the University of Pennsylvania, where he studies and teaches innovation and entrepreneurship. He is also the author of The Unicorn’s Shadow: Combating the Dangerous Myths that Hold Back Startups, Founders, and Investors. His papers have been published in top management journals and have won multiple awards. His work on crowdfunding is the most cited article in management published in the last seven years.

Prior to his time in academia, Ethan co-founded a startup company, and he currently advises a number of startups and organizations. As the Academic Director and cofounder of Wharton Interactive, he works to transform entrepreneurship education using games and simulations. He has long had interest in using games for teaching, and he co-authored a book on the intersection between video games and business that was named one of the American Library Association’s top 10 business books of the year. He has built numerous teaching games, which are used by tens of thousands of students around the world.

Episode Notes

Ethan’s UPenn Website
Ethan’s Personal Website
Ethan on Twitter

Dall-E Tweet
Google Drive folder with Ethan’s Dall-E images
Wharton Interactive
2022 Hugo Awards

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Jon Schwabish: Welcome back to the PolicyViz podcast. I’m your host, Jon Schwabish. On this week’s episode of the podcast, I chat with Ethan Mollick from the Wharton School at the University of Pennsylvania. And you’re thinking, why am I talking to a professor at the University of Pennsylvania? Well, you might recall from a few months ago, if you’re in the date of his world. From a few months ago, there are a bunch of really cool images created from the Dall-E artificial intelligence tool that replaced on data visualization created by famous artists. And those were created by Ethan. And so my instinct was to reach out to him and talk about how does Dall-E work? What does it take? What do you need to do? And he wrote back and said, I’d be happy to talk about it, but there’s really not much to talk about it. Just kind of throw it in there and you just see what it does. And so that was kind of fun to hear that. So we do talk about his experiments with Dall-E, and we talk about that work, but we also focus on what he does with Twitter. And of course, Twitter’s going through its own changes. And we’ll see what happens with Elon Musk taking it over. But I find Ethan’s Twitter feed really interesting because he so much time summarizing academic papers. And so he’ll take a screenshot of different parts of a paper, including graphs and the abstract or some text, and we’ll summarize it for folks really quickly.

And so it’s really interesting from someone like me coming from the economics field, you know, writing and working in the academic literature. But I wanted to pick his brain about how academics could do a better job with the data visualizations in their academic writing. And so we spend most of our time actually talking about his Twitter feed and talking about some of the solutions that maybe academics can take part in to improve how they communicate their work. And we also talk about some of his other work at Wharton, including Wharton Interactive, which is working on the entrepreneurship space using games and simulations. Well, of course, that has a direct link to the field of data visualization and data communication. Now, before we get into my conversation with Ethan, let me tell you a little bit about this week’s sponsor of the show Partner Hero. Partner Hero is a outsourcing firm that’s built to meet the needs of scaling high growth startups. They offer flexible terms, they offer fast onboarding and the ability to scale your teams quickly. They have quality assurance baked into all of their different programs. They have offices around the world, so you can work in a variety of different languages, and they’re aligned with positive, accessible, equitable values so that you can make sure that you are not exploiting or taking advantage of workers from around the world.

And that’s what I really like about it the most. It’s also super flexible. It’s built for the needs of startups in particular. So that allows you to scale up and scale down really quickly. It also has a really fast onboarding process, which of course is going to be helpful for those of us who don’t have the time to really be going through all these different processes with invoicing and contracts and all of those different things. So if you are a small business in particular, or a freelancer, if you’re ready to bring in outside customer support to help your startup and feel like those folks are a part of your team, check out Partner Hero, head on over to to book a free consultation with their solutions team. Mention you heard about Partner Hero from PolicyViz, and they’ll waive the setup fee. So that’s So here we go. On this week’s episode of the show, here’s my conversation with Ethan Mollick from the Wharton School at the University of Pennsylvania. Hey Ethan, good afternoon. How are you?

Ethan Mollick: Excellent. And thanks for having me. I’m excited to be here.

JS: Awesome. A beginning of the semester for you?

EM: Yes. I’ve got a couple weeks left till the next quarter kicks in and I start teaching, but it’s certainly on my mind.

JS: Wow. Quarters. Quarters must be hard. I feel like quarters, like once you, like, it’s like flying from like DC to Philly. Like you, you kind of don’t even get up to cruising altitude. You just kind of like…

EM: Oh, I kind of like it. Like, you get, you get, it’s like delivering like a, it’s like a short set right? For a college. I got, I got 12, 12 sessions, I got to deliver. Type 12.

JS: Type 12. Right, right. So I reached out because you did this really cool thing with this Dall-E artificial intelligence tool that came out with some data visualizations, which I have actually, by the way, a couple hanging on my wall. Because they’re pretty cool. But I thought maybe we’d start just by talking about what you’re working on. You’ve got some really cool initiatives going on at Wharton and Penn. So I thought maybe we’d start with that and then talk about some of the other things. So do you want to maybe give folks just like your quick, like bio little background and what you’re starting the semester with?

EM: Sure. Yeah. So I’m a professor of innovation entrepreneurship at Wharton at the University of Pennsylvania and trained as an economic sociologist. And I teach a lot of the intro courses, or at least I did in entrepreneurship. And I’ve been thinking a lot about how do we trade these kind of things at scale and how do we do teaching at scale. So I’ve been really super interested in teaching, especially how do we kind of teach in new ways, reach new people, teach the kind of lessons like data visualization lessons that are contractually hard to teach. And, you know, really been thinking about this a lot. I have, you know, a mass violin course of MOOCs, these kind of Coursera courses. 400,000 people have taken the MOOCs that I’m part of, but they’re still kind of watching videos of people talk, right?

JS: Yeah, yeah.

EM: So there’s something, that’s ultimately frustrating about. So a lot of my effort has been into launching something called Wharton Interactive, which is a game studio at Wharton, effectively that tries to teach using games and simulations and to try and do teaching at scale with all the instructional pedagogy built in from the beginning. So that’s been a lot of my time on that, although also as you’ve noted, a pretty avid Twitter user and somebody who’s dipping my feet into things like AI generated images and stuff. So having to discuss any of those things.

JS: So tell me a little bit about the Wharton Interactive. So is this for business school students getting them training that they’re not getting in the core courses? Or is it those core courses, but trying to develop a way to do it at scale?

EM: So it’s a little of both. There’s a phrase in, in Silicon Valley eating wood zone dog food, right? So I experiment on my students that tell them that, hopefully…

JS: Yeah, hopefully they won’t listen. Yeah.

EM: Like, I want your podcast succeed. So hopefully they listen, but then are tolerant.

JS: Right, right.

EM: But, no, I mean, I have been running experiments. I wrote a book on games and education. I’ve been doing it for over, wrote that like over 10 years ago. And so I have a class that’s basically by experimental, a 100% games class. So from a teaching perspective, it’s great because I just sit there, and my students play games, my games the whole time. So the intent is that there’s a few things that motivate this. One of them is like, we actually know a lot of pedagogical science just as professors. We don’t really, we’re not really taught in ourselves. But there’s actually a lot of like, we know how to make people remember stuff and do stuff. So part of its baking that in. And then part of it is like experiential learning is great, but has project based work has all these weird outcomes, right. And you probably see this yourself and certainly anyone who’s teaches those, like a team goes great. Like I’ve had, I think people have from my class and the class taught my colleagues at Wharton over the last 10 years, people have raised like the entrepreneurship classes, like $2 billion in venture capital. Great, right?

JS: Yeah.

EM: Except that those are the projects that have really succeeded, right?

JS: Yeah.

EM: And for every successful projects, like one, the team goes bad. So they like, how do we give people project based work where the projects are always going to be interesting and where failure is interesting and where they all have the same kind of experience rather than hope that the, you know, the gods of teams and projects work out on their behalf. So that’s another big motivating factor. And the third one is democratization, right? So there’s all this evidence, and I know the same stuff happens and, you know, in thinking about things like, you know, being a good statistical physical thinker, but just small amounts of statistical education, business education make huge difference in people’s lives. So, you know, there’s these great studies, one that really motivates me. There’s a study Uganda done by the World Bank that’s a randomized controlled trial. Oh, this is my Twitter feed by the way, of people want sites. But that took a randomized sample of high achieving high school students in Uganda and put them through a three week entrepreneurship course, sort of the equivalent of what we’re doing in the game. And afterwards, three years later, they were like 10% more likely to launch ventures, you know, 12% more likely to employ people, had 18% higher salaries, like little bits of intervention at the right time, do the right thing. And like, it’s great, I got really talented people coming to be Wharton, but how do we get blow up in the doors and do this around the world? So it’s those motivating factors of like, games teach in a way we can’t do otherwise. We could build pedagogy in a way we couldn’t do otherwise and we could democratize. So those three things are really motivating me. And anyone can play these things. Like some of them are free and you can play them down, play them online. Some of them have, you know, the standard kind of charges that we would charge much less than a textbook, but, you know, charges says doing and so on.

JS: Right. Yeah. So can you give folks a sense of what a game might be as part of this?

EM: Yeah. So it’s interesting. We’ve been playing a lot with the philosophy of this. So let me give you an example of the three quick examples. Okay. So one example is a mindset game. We want to give people an experience doing something they may not otherwise do. In this case, it’s actually data analysis and coding. So we actually partnered with Evite and you, in this game, it’s a light fix. You play as a consultant who has to help. There’s like an hour countdown, someone’s on a plane and has to do a big presentation, but you’re actually given 3 million lines of actual Evite data and you actually code in Python in the game and get all this kind of assistance to solve a bunch of problems, and do, you know, statistical analysis and things like that. A second game is a, is you, one where you actually run a startup in real time over the course of three weeks. And we filled the internet with fake information about the technology that doesn’t exist. But you do everything from negotiate with customers, develop prototypes, and again, it’s all simulated. Like we built fake Gmail, fake slack, fake Zoom calls. We have actors that appear on these Zoom calls and, you know, it’s a whole all at interactive. And then we’ve realized that there’s some value in completely fictionalizing the setting. So we have a game set in 2087 on a dub space mission to Saturn, where everything is going wrong. We’ve worked with the Disney imagineers escape room designers. I got help writing for the guy who won the Hugo Award this year for science fiction, which is like the Oscars of science fiction for the non-nerds out there. And so, but it’s really, it teaches you strategic, organizational, individual leadership because the lessons are exactly marketing lessons, you know, statistical lessons and things like that. So it is really attempt to try and do a lot of different things, not just my stuff, but we’re working with lots of other professors to teach these things. And try to come with a method of doing it as well.

JS: Got you. And do you foresee, or can you foresee how it might be used in other disciplines? I mean, I think the way you’ve described it seems very business, math, economics, you know, startup, that sort of thing. But have you started sort of pushing the boundaries and what it might look like for other disciplines?

EM: Very much so. I mean, we can tell any story, right? It’s interactive fiction engine. And the whole idea of it actually was to move away from the mathy piece because there’s lots of mathy simulations up there where it’s like, what spending do you want to spend? We’re making 4%, 4%, 5%, and then Excel spreadsheet or assist dynamic models chugging our number. That’s not how the world works. What happens if you increase our R&D spend by 4%? The head of R&D is going to email you and say, why not 6%? The head of sales is going to email you and say, well, you fool, you’re doing this. Like, that’s the interesting piece. So the whole idea is we built like this fake inbox so we can play all kinds of games where you literally are getting messages from people. We also have all the stuff, if you want to run a fully interactive picture game, we want to teach the Odyssey by actually putting you on board as one of Disney’s crew members trying to desperately convince him to not listen to the sirens. Whatever you want to do, we can build those kind of settings. So the intent is to build around that humid interaction rather than just the math piece.

JS: Right. That’s very, very cool. So let’s switch gears a little bit because a few weeks ago, months ago now, you put out this, I guess, collection of data visualizations rendered by the Dall-E artificial intelligence tool. And so I’m not going to ask you to go into all the gory guts of how Dall-E works. But I guess I’m interested in why you decided to do that, how it worked, from your perspective, just what seems to be kind of a more casual user and were you surprised at the reaction that you got on Twitter?

EM: Yeah. So I mean, there’s a lot of interesting things. I used Mid Journey, which is basically a Dall-E, a different Dall-E. They’re all kind of the same. I just, this one I got access to more easily. So I used that. You know, I study technology also, and there’s always these sort of false starts and advancement in fields, right? People get really excited, you know, self-driving cars are going to be there, whatever the new technology is, right, you know.

JS: I’m still waiting for my hoverboard, right? From Back to the Future, right? Yeah.

EM: But there are moments where things are accelerating and you really should be part of it, because what they’re doing is not just the technology. There’s no threshold we have to reach. It’s fundamentally changing, I think, how we get to interact in an interesting way. And the suite of sort of AI meets human technologies, right? So there’s a whole bunch of things that generate, I have a colleague at Harvard who demonstrated a couple of fake Harvard cases that he had a different system generate, and they’ve, like Harvard cases, they were reasonably sensical in the same way. You know, I, you know, I really enjoy art data visualization, you know, I’ve got graphics, you know, in my papers. I just am not that good at it, right. I’ve spent time over stata, desperately trying to tune, you know, something. So I get the right, I’ve read all the books, I’ve got books on fonts, I’ve read your stuff. Like I am, you know, I’ve, I’ve like, I’m like, oh, this is so clever. I don’t have the full chops to pull that off, right. But suddenly here I can, it’s a different thing. It’s a medium where I can write something and have it happen and tune it with words. Fundamentally expanding how something operates, right. Using a human vocabulary to kind generate things. And I think that, you know, it was interesting that it took off. I think that there is this hunger for seeing different ways of visualizing seeing the world, right. Its why, you know, I’ve got a, like you have a decent Twitter following, right? If you look at the tweet that go most viral or not the academic papers or anything else, those do fine. But it is any time there’s anything with a visualization, right? That is literally what makes a Twitter tweet go is a visualization. The more understandable the visualization is, the more likely it succeed. And of course, drives me crazy that academics refuse like myself, honestly. But we refuse to kind of put the good visualization there. We don’t have the money, the time, the stuff to do that. But now we’re, we’re on the cusp of something new. So I think the idea of seeing something visual and you could, the set of styles that I was able to, you know, do 24 styles or whatever in the course of, you know, playing with on and off over the course of a day. And they represent something that’s fundamentally different than what we’ve seen. You know, they’re aping the style of Mondrian (ph) or whatever, but it’s not, there is something that a human wouldn’t have necessarily come up with any of these, right.

JS: Right. And you don’t need to dive into Illustrator and do it pixel by pixel, just let it go.

EM: It takes seconds, right. Like I’m just literally saying, you know, chart, you play with a little to get the numbers working. And I’m not good at this. Like I’m a naive person writing this stuff down. Like there is a pseudo code language you can apply, but who cares. It works, right. And I think there is something so exciting about that, and I think anybody who is interested in the visual space at all, in the policy space, in the data space needs to spend an afternoon playing with these tools. I just can’t emphasize enough that there is something really transformational there. And even if you bounce off it, you won’t regret it, I think.

JS: Yeah. So that leads to the other part that you already sort of alluded to, which is your Twitter feed. You spend a lot of time summarizing academic papers, which can’t be easy, especially because you have to read some or most of them, which can’t be easy. But I guess I’m curious about, as you mentioned, like your thought about the graphic space in, in academia and is the reason why the graphs aren’t better is because there’s just not enough time, there’s not enough skill, it’s the editors, it’s like, is it just the whole system?

EM: So the short answer to all of your questions is yes, obviously, like it’s all these things, but I mean, I mean there, you know, look, as academics, there is a disdain for public, you know, interaction that is not actually like, there’s a purity argument. And my mentor, Ezra Zuckerman has talked extensively about this at MIT, you know, there is a desire for purity in our field, right. And there is something impure necessarily about talking to a general public that, you know, again, you could cross over that line. You could be one of the people who’s, it’s okay to do it. But there’s no doubt that as a junior faculty member, you’ll be warned away from doing that distraction. And the same way, right. There is a, you know, there’s this, there’s this theory I think about a lot middle status conformity, which is that if you’re competing with people, you’re better off if, if you want to maintain middle status to look like everybody else. Violating those norms is a way to get either elite or get punished, right. That’s what elites have punished. The elites who get away with it, they can violate a norm or not. So in the same way, like, you know, I want my paper accepted, so I’m going to use default data graph or autographs to do this. And maybe if I’m really fancy, I’ll change the background color, but like showing them any more time than that to do that or like, you know, is an indicator of a lack of seriousness or indication, right. So what ends up happening is the only good, really good graphics come out of, you know, some of the, you know, like science or a few other places seem to have graphic designers who help out with these things, you know, or graphical, you know, abstract. But the result of something on Twitter, I’m sure you’ve seen the same thing, is that if you want something graphical, that huge makes a huge difference. And the graphs that people tend to have that are most visible are scatter plots. And scatter plots are in many ways the worst graphs to show because amateur critics attack them the most. It lends itself to bad statistical analysis, right? Because a scatterplot is not the same thing as a controlled OS, right, regression analysis. So, you know, so I think that there’s some very simple ways to improve this and there’s some more complex ways, right. Simple ways, anything showing magnitudes, right. Any of the graphs that show confidence bands above and below zero for effects, you know, with a table of effects. But I just would beg people to do this. This stuff matters. Like, I now have, it’s been really funny, I went to the big academic conference for the Academy of Management this year and, you know, I’ve never been close to pseudo celebrity before, but people are like, oh, I read your Twitter feed. Like people clearly care about this. They send me articles they’d like to see, tweet it out, this little bit of extra work though they’re not willing to do. So that’s my feeling on the graphic side. It’s like it is way under counted the difference between a good one and a bad one. And when it gets noticed at a place like Twitter or somewhere else, they get more citations. They get press reach outs, it makes a difference.

JS: Right. So there’s definitely like a line of research there, right? Like just the way you said is like to actually quantify the impact of having better graphs. Of course you have to sort of define that in some way. But if you were the editor of some journal, say Ethan’s Journal of Management, what would your first step be to make the graphs in the articles in your journal better?

EM: So I think there’s a lot of halfhearted pushes to do some of this, right? I think first of all, you need one graph that communicates your, your key point, right? Like, you know, and I proposed this before, but like, you know, there’s a few, you know, heroic graphs that do that, right? There’s a famous study on the price of wholesale fish. I don’t know if you’ve seen this, the current nature of economics, again, I’ll put the link so people want to do this. But it shows the fish prices before and after cell phones were implemented in India, it’s really about, you know, coordination and pricing. But the chart is like up and down, up and down. And then suddenly the instant cell phones, the chart becomes completely flat, but all the fluctuations disappear. Instantly get like, oh my God, I got this, right. Like there these kind of graphs, you know, some of the graphs on income inequality, you’ve got them. So, you know, having something, spending the time to think what’s, you know, often it involves taking something attorney into an order of magnitude that matters to people or an impact. If I take, people are already using back of the envelope calculations, you know, this would cost $20 billion, this would save 2000 lives. There needs to be a graph of that. The so what moment as opposed to just a graphical check on what you’re doing, which is also important, but it’s important to recognize that these are persuasive arguments. We’re not wrong. We don’t feel better about persuading through our theory section. We don’t feel bad about persuading for evidence. We should not feel bad about having a persuasive graph and arguing, it’s a persuasive graph.

JS: Yeah. It’s always shocking to me when I argue to folks, you know, make your, the title and your graph active and tell people what the argument is in the graph. They’ll say, no, no, we can’t do that because of this, that, and the other. And I’ll say, okay, well let’s see what you’ve written in the text and maybe we can find like a middle ground between the descriptive title and the active title. And 99 times out of a 100, what’s in the paper, what’s in the report is, you know, that active statement that’s making an argument. And somehow there’s still this break between the visual piece and the text.

EM: People are scared of it in a way that it’s a real problem, right? This should be the moment that you are able to kind of show why this matters. And so what I think a lot of people know what that graph would be. And I think maybe having a special way of labeling it, right? Like this is my, you know, persuasive inclusion, right, in some way or another, because you know, they do that secretly through other graphs. You’re only showing the ones that are really showing what you want, what you want to show anyway, right? Like, it’s not like those are not selected out a set of graphics.

JS: There’s all bias on there somewhere at some point. Yeah.

EM: And then there’s the self-sabotaging stuff, the people like acronyms in your graph, like just the worst part like, you know, and this is CBR6 compared to CB4735. You’re like, you know, and then I end up. I mean, so there just is this, you know, and, and I think people get caught up a lot on visual niceness, which is I think, important, but I think you would do just a lot with like, what are the two things that matter? What are the dependent, what’s the dependent variable? What’s the variable that matters? You know, and you’re allowed to be straightforward about this, show me your 95% confidence interval. Like, do that, you know, all that’s great, but like, show me something that is interesting or shows change.

JS: Yeah. So let’s bring these two pieces together. So when you think about the Wharton Interactive and the simulator and the games, do you see, or maybe you’re doing it now, but do you at least see sort of training for future academics to help them think more? I don’t even want to say more visually, because it’s not just the visual piece, it’s how people write as well, right. But do you, but do you help them think about those sorts of pieces in their research?

EM: I mean, I think that the idea is thinking about how you apply stuff and what lessons people are really trying to learn outside of purely academic framework, what we call clear closing the theory practice gap, right? Like we do it in our classrooms who are often afraid to do it to the outside world. So part of what we do is help people tell stories, literal stories, right? So we’ll meet with, you know, an academic, it turns out that when they’re telling us something really important about the world, but they’re kind of afraid to close that gap. But if you put it into a story format or similar like a graphical format, suddenly this stuff becomes apparent, right? Like put people on the grounds of trying to, you know, and the great thing about games, just like graphics, is you could straight the ground wrong. Like I could set up a situation where your research matters and make it clear, these are boundary conditions where it matters. But now I’m in a world where I wish I knew that paper. I could put you in that world, right. Where it matters that, you know, that result or that answer. Where you can play with alternative outcomes, another thing that we do that actually we’ve done graphically in the game is like what, you know, actually letting people modify projections. And you can see the effect on a long term graphic. The world is advancing very quickly like that world of interactivity and graphics and, you know, we have so many other problems with how academic papers are formatted and published and KOLs and everything else, and, you know, just to refuse to take it the advance what’s happening here of storytelling and like, it’s a problem and it’s a growing one.

JS: So do you think, you had mentioned earlier the danger of junior faculty being that different person doing, you know, the better grasp, but do you think that junior faculty or, you know, people who are coming into the academic field in the next few years, that they will ultimately be behind if they’re not thinking in, in the ways that you’re arguing more visually, better writing, you know, thinking about broader audiences?

EM: I mean, I think they already are, right? Like I think the issue is it’s already a two-sided game, right? People may frown on, you know, on Twitter engagement or something else, right? And I dread the how do you have the time? It’s because I an academic who just gets easily bored during things and that reads a bunch of stuff. I actually find everything we do interest. Like there’s so much good work out there. Like that’s the thing I’ve learned so much good work, right? I mean, I could show you all the stats and now we’re drowning in science, but like I’m amazed, and that’s not even counting working, but like there’s so much good and important work out there that nobody will ever read or care about, right? And so it already is that, look, if you can get, you know, we may not like it, we may not agree with, you know, but like, you know, we may not tell people it’s true, but if you get a New York Times piece covering your research, it’s going to get cited more, people are going to pay attention. You might have to deal with some jealousy, but like, it matters, right? But we tell people it doesn’t matter, but it obviously matters. So now people have to play a two-sided game. Where on one hand they have to say, I don’t really care about what people think of this. I’m purely interested in the life of the mind. And then on the other hand, you know, they’re trying to, you know, you’re trying to putting this together in an honest way would make sense, right? I was just, you know, um, reading about the late 15th century scholarship and there were all these traveling scholars who would, you’d try and get hired by patrons, right? In Europe to, you know, teach their children. That’s how you’d make all the money. So you had to become prominent to do that. The only way to be prominent was to pick very public fights with other scholars. So that way you’d be noticed or be like, oh, he’s, you know, he is controversial, than they hire you. And I feel the same sort of stuff happens. Like there is advantage of being picked to being prominent and being noticed. And I think acknowledging them, and it starts with graphics, right? It honestly does, like graphs are the persuasive connection between the general public and academic work.

JS: Yeah. Love it. Love it. I’m with you. We’re fighting the same battles. I love it. Ethan, thanks so much for coming on the show. I feel like we covered a ton today. I really appreciate it.

EM: This is fun. I can’t wait to keep reading your stuff, which I always think is awesome. And, you know, and also by the way, some of your exercises are like, you know, on teaching the stuff is great and I just, everyone should check you out if they haven’t. It’s terrific. I’ve thought about it a lot, especially, you know, introducing these concepts is wonderful.

JS: These games. Yeah. Yeah. That’s great. All right. Well, thanks again. I really appreciate you coming on the show.

EM: All right. Thank you. Bye-bye.

JS: And thanks for tuning in to this week’s episode of the show. I hope you’ll check out Ethan’s website. Check out the simulation tool that he has Wharton Interactive, really interesting work there. Check out his Twitter feed, especially if you’re interested in academic research. And maybe there’s some ways that you can help folks improve how they communicate their data visually. So until next time, this has been the PolicyViz podcast. Thanks so much for listening. A whole team helps bring you the PolicyViz podcast, intro and outro music is provided by the NRIs, a band based here in Northern Virginia. Audio editing is provided by Audio editing is provided by Ken Skaggs. Design and Promotion is created with assistance from Sharon Sotsky Remirez. And each episode is transcribed by Jenny Transcription Services. If you’d like to help support the podcast, please share and review it on iTunes, Stitcher, Spotify, YouTube, or wherever you get your podcast. The PolicyViz podcast is ad free and supported by listeners. But if you would like to help support the show financially, please visit our Winno app, PayPal page or Patreon page, all linked and available at