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Episode #80: Alvin Chang
175 Plays8 years ago
I’m currently in Pamplona, Spain enjoying what is turning out to be a very rewarding and tiring week at the Malofiej Infographic World Summit (follow #malofiej25 on Twitter, if you like). If I can find the time, I’ll try to conduct...
The post Episode #80: Alvin Chang appeared first on PolicyViz.
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Transcript
Introduction and Sponsor
00:00:00
Speaker
This episode of the PolicyViz podcast is brought to you by JMP, Statistical Discovery Software from SAS. JMP, spelled J-M-P, is an easy to use tool that connects powerful analytics with interactive graphics. The drag and drop interface of JMP enables quick exploration of data to identify patterns, interactions, and outliers.
00:00:19
Speaker
JUMP has a scripting language for reproducibility and interfacing with R. Click on this episode's sponsored link to receive a free info kit that includes an interview with DataVis experts Kaiser Fung and Alberto Cairo. In the interview, they discuss information gathering, analysis, and communicating results.
Meet the Host and Guest
00:00:49
Speaker
Welcome back to the Policy Viz Podcast. I'm your host, John Schwabisch, still with a hoarse voice from a good week at the tapestry conference in St. Augustine a couple weeks ago, but making my way through what I'm calling my month of story. And I'm excited this week because I have a guest with me who tells stories and conveys data in a different sort of way than I think most of us are probably used to at least doing on our own. So I'm very excited to have with me Alvin Chang from Vox.
00:01:18
Speaker
Alvan, welcome to the show. Thanks for having me, John. Now you and I spoke probably a week or two ago at length about stories because I was sort of quizzing you as I was getting prepared to do my talks on stories. So I'm excited to dive in and get your take on it.
00:01:35
Speaker
I thought maybe we'd start by having you give us a little bit of a background, you know, where you came from and how you came to Vox and maybe talk a little bit about your
Innovative Storytelling with Comics
00:01:41
Speaker
approach. You do a lot of illustrations and a lot of animations. And so maybe you could talk about that approach to communicating data and communicating analysis at Vox. So a lot of what I do started when I was in grad school and I was studying a lot of how people learn, how people take in new information and
00:02:00
Speaker
That kind of led to my work at Vox where my approach is largely I'm trying to teach you something. It's using a completely different framework than you might assume. And let me teach this to you in the best way I know how. So the method that I've settled on and I've been experimenting with quite a bit now is comics.
00:02:24
Speaker
And so a lot of folks have probably seen these like blocky Lego-like comics on Vox.com. That's me making comics because I don't know how to make any other shapes other than squares. So we end up with blocky comics. But I'm using those comics to illustrate frameworks that readers can explore. So for example, I just made a comic showing why the Republican health care plan, the incentives aren't lining up when they're trying to replace the individual mandate.
00:02:54
Speaker
So I'm using these block figures, and I'm representing coverage as people who are under some kind of like awning, and I'm representing not coverage as people being outside. And eventually, I've created a little world where readers can play around with this scenario and think, oh, I wonder what happens if I move these sick people under and cover that, then the cost of coverage would go up. And I kind of create this world that
00:03:20
Speaker
that users can play around in. It's a sandbox. They can kind of do a thought experiment of their head and get an output. And I think ultimately that's my goal is helping readers understand, oh, if I change something like this, what would happen?
00:03:34
Speaker
But what's interesting about your approach is that you are using these illustrations and these block figures where lots of other people have tried doing these things where there's a kind of engagement.
The Power of Spatial Illustrations
00:03:46
Speaker
The New York Times has those draw a line sort of thing and other ones where you move a square around or something. But you're actually using illustrations of people and even though they're squares, we still sort of see those as people.
00:03:59
Speaker
As you are drawing those, do you sort of think that that connects with people in a better way than some sort of just abstract shape? Yes. And I think that's because humans are really good at orienting themselves in a space and internalizing a two dimensional grid. So, for example, we're really good at following instructions. If I told you go three blocks right and five blocks north, we're really good at
00:04:25
Speaker
thinking about how much we've traveled in that distance. We're not so good at looking at a line going up and a line going down and kind of figuring out what the slopes are. Those are things we're not really great at. So when I create these figures, I try to leverage this thing that we're really good at, this thing of, okay, you know,
00:04:46
Speaker
gravity exists in the world they create when or or rain exists, for example. So in the Obamacare example, I have people under some kind of some kind of awning and they're covered. So they're not going to get hit by, you know, whatever's coming down. It's just it's a silly thing. Yeah. A lot of people say things like, oh, now we need a comic to explain this to us. But I'm in my mind, I'm thinking, well, you didn't have to think about whether or not what that represented. You just internalize that automatically. So I'm trying to offload a lot of that information.
00:05:15
Speaker
so that we can get to the core concept. Right, right, right. And when you are trying to convey that information, what are the different mechanisms you're using in terms of sort of mentioned one of being able to move the figures around? We've seen lots of, you know, things like scrolly telling both vertical and horizontal, we have animations, are there certain approaches that you take that you think work better than than others?
00:05:39
Speaker
So I always try to introduce characters first. So when we always think about kind of human driven storytelling and having main characters and so on and so forth. And we struggle to do that when we use data, when we're talking about larger frameworks. Because we think how does a single person ever represent this bird's eye view that we're getting with data?
00:06:02
Speaker
And so I've just kind of short circuited all of that and said, you know what, like, I'm going to make this block figure represent the entire data set or this entire population. And I think the readers kind of follow along and understanding this blocky figure represents the average uninsured person, for example. And that helps me explain the both the journey of
00:06:23
Speaker
that average person, but also the incentives of that average person. It helps you kind of empathize with people who are in that position, as opposed to looking at data sets and trying to decide where the incentives are there. So I think the goal is how do you empathize with the data set? Yeah, the empathy I think is a key point.
00:06:46
Speaker
So when you think about telling stories or when you think about others who are saying, oh, we're going to tell stories with these data, do you sort of push back when people say, I'm going to tell stories with these data and they give you a table and they give you a chart? Whereas you're saying the chart isn't enough. I want to make this connection with people through the illustration, through, you know, this image of a person. I don't push back mostly because
Challenges in Data-Driven Journalism
00:07:08
Speaker
I've done that often. Yeah. Yeah. That's a very easy trap to fall into where you, you know, you,
00:07:14
Speaker
Go find your data or collect your data. You do the analysis, you make some charts and then you write around the charts and you weave it together. I don't think that's the right approach. You're trying to show off that you've done the work as opposed to trying to explain what the work is saying. And so I understand the purpose of people who put a whole bunch of charts in a story and then write around it. I get that purpose. I think for me, the purpose is more so
00:07:43
Speaker
This data seems to paint a picture that pushes you to think about this issue in a different way. And here's how that all fits together. So a lot of times these comics aren't actually showing any type of data set whatsoever. They're just showing you a new framework and eventually I'll come around and say, here's the data that backs up these frameworks.
00:08:09
Speaker
You know, what's interesting about your approach is I've been sort of thinking lately that one thing that, you know, economists or analysts like me and the folks that I usually work with, what we need to do better is pairing the in-depth sophisticated data work with actually talking to people the way, you know, your colleague Sarah Cliff, for example, does a really good job of going out and talking to people.
00:08:29
Speaker
But what I'm hearing from you is that it's not so much about talking to an individual person or people and getting them to tell you something. It's more about getting the reader to connect with the image or the personification of a person and not an individual per se. Yeah, I think I agree with that. I think a lot of times as reporters, we go out and talk to individuals
00:08:53
Speaker
and use those individuals as characters to help our readers connect to the story. But we often have this conversation in journalism where we say, oh, that person is an imperfect character, meaning they don't represent the data set in the way that we want them to. Or that's the most accurate, you know, they're an outlier in some way. And in my mind, I'm thinking, well, we have the data.
00:09:20
Speaker
And the reason we need this human being to play an intermediary between the data and the reader is why? Like, why can't we play that role? So I'll talk to people to get an idea of the nuances of their individual situations. But at the end of the day, I'd rather help people connect with what the data is saying. Because I think it's a more accurate way of thinking about issues versus saying,
00:09:47
Speaker
you know, like reporters will do this all the time, they'll cite a heart wrenching story and say, and here's the data to prove it. And of course, everyone's everyone knows, you know, that's really sad. But let's look at let's see what the bird's eye view is. So I think there's a way to merge that. And I'm trying to.
Addressing Race and Gender in Comics
00:10:04
Speaker
Yeah. But I think we're still we're still figuring it out. And I'm still figuring it out. Occasionally, I'll be writing about something that's, you know, incredibly sad.
00:10:15
Speaker
and be looking through data sets that researchers have put together. And I realize there's something missing, that there's kind of a soul missing there, a real human story. And I think there's power in those real human stories.
00:10:30
Speaker
But I think there's always this dissonance between humans don't always fit into larger data sets really well. Right. Right. Yeah. When you're working on a piece that might have this real emotional, even sad attachment to it, how do you approach that when you're doing the illustration? Do you feel
00:10:50
Speaker
Do you feel torn about making the illustration look like a sad person? And by extension, actually, how do you approach race and gender? I get this question a lot like, should my line for men be baby blue color and for women be baby pink? And I'm like, no, please don't do that. But how do you approach that when you have issues or characteristics of people that might be sensitive for readers?
00:11:15
Speaker
It's interesting you say that because I recently drew a cartoon of my family. I represent people through cartoons and sometimes they are real people and people happen to have different shades of skin. And that's a very important part of how we talk about the world. And so I colored my skin by using the eyedropper tool on one of the photos of myself, which is usually how I do real people.
00:11:44
Speaker
And one of my colleagues said, I think you made yourself too yellow. And I'm an Asian man, so I said, well, I just used the eyedropper tool. And I am hyper-conscious when I am illustrating other people, because I think there are traps you can fall into that you just don't understand. But when I was illustrating myself, I thought, I got this, right?
00:12:13
Speaker
And so I think there's my approach generally has been to this is going to sound vague, but to be as generous as possible and empathetic as possible in understanding how people would want to be represented. Because I think I think about myself a lot. I think a good example is like my cartoons have squares for eyes.
00:12:36
Speaker
one of the defining characteristics of Asian people is their eyes look different. We have more almond shaped eyes. And so like, do I change the, I call them wakas. So do I change their waka eyes to make, to be more Asian? Or is that, is that not the way that I would want to be represented? And that's something, you know, that's kind of a question that I, I had a rest with early on. And, and I think,
00:13:02
Speaker
kind of going a little bit further, if we're talking about like, for example, housing discrimination, or we're talking about health care. The question is, how do I represent that one person in the data set? Do I use a white male, a Hispanic woman? What is the length of hair? And it's something that I'm figuring out. But I've, this is the first time I've actually kind of told anyone this, but I've decided that
00:13:29
Speaker
we see enough representations of white men. Sorry, Don. I always go back to the Homer Simpson line of, I think the line was, I'm a white male between the age of 25 and 54. Everybody listens to me. So yeah, I think the white male representation is
00:13:47
Speaker
We were enough. Yeah. Yeah. I mean, it's funny because I've just said the default is going to be a woman of color and that and then we'll all on default out of that, which is right, which has gotten very interesting. A lot of readers have asked why I do this to me as an asset. You know, that's just if I made it a white male, you wouldn't ask a single question about this. But you know, let's move on here. That's right. I don't know if there's a I don't know. That's
00:14:13
Speaker
the right approach, but if there's a reason why it shouldn't be a woman of color, then I will change that. So I think that's been my approach. But it's been a big problem that a lot of people, a lot of journalists don't ever run into because we don't represent through illustration. No, that's right. That's right. I think that the closest most people come to is blue for men and pink for women. And I think most people sort of hate that color scheme anyways because it's
00:14:41
Speaker
It's sort of childlike anyway, so there's that. Does the block illustration, you think, sort of help get away from some of the racial or gender portrayals because it's a little more abstract?
The Role of Block Figures in Storytelling
00:14:54
Speaker
I mean, you still have to make all these other decisions about skin color and hair, but... Right. I mean, I think the reason that I settled on blocks, other than the fact that I couldn't really do anything else when I was starting out. And other that you have probably in an awesome Minecraft world is my guess.
00:15:10
Speaker
Yeah, it's so funny. I didn't actually play Minecraft until people started telling me that these are like, I had to start playing. Yeah, it's so one of the reasons why I decided, you know, these block figures should look the way the way they are is I didn't want to convey information inadvertently, you know, making decisions inadvertently without me purposely doing it. So I have this, like,
00:15:38
Speaker
I call it the waka morgue, which is, you know, it's kind of, you know, in the old school times, I used to have like a morgue of like assets that you drag onto a newspaper layout. And so I have a whole bunch of just default waka lined up in my in my Illustrator file. And they're just default, they don't, they don't, they have very default hair, they have a square for a hair, they have a square for eyes, they have gray shirts, gray pants and like, and they're
00:16:05
Speaker
like they have gray skin even and then from there that's I have to make decisions as opposed to defaulting into any decisions I'm making so that's that's been a really interesting process yeah making sure my process doesn't accidentally default into conveying information that I don't mean to convey which is something that we think about all the time with charts and we think about all the time with any type of visualization or infographic or interactive I don't know
00:16:35
Speaker
many journalists or data people are thinking about it with comics necessarily. But it's gotten me into the world of comic book artists who think about this regularly. And the overlap is astounding of how we represent stories and data through visuals. We just happen to not talk very much to people who make comics. People who make comics don't talk very much.
00:17:03
Speaker
And yet we all would probably get along really well would be my guess, right? I would think so. Yeah.
Creative Data Storytelling Advice
00:17:09
Speaker
If someone were to come to you and say, I'm really into data, I'm into data visualization, but I want to make things that are more engaging. I think you've carved out a space where things are engaging in kind of a different way.
00:17:23
Speaker
A big challenge for DataViz, like the 9 millionth bar chart, is not that exciting. But if someone were to come to you and say, I'm a D3 programmer, I'm a Stata programmer, but I want to make things more engaging and I want to try some of these illustrations, what would your advice be for people who want to try to do something
00:17:43
Speaker
I don't want to say more creative. That's not the right word. But try some illustrations. And I think whenever I talk to graphic designers, they're always like, anyone can do this. It's just learning and practice. It's just a skill. So what would you say to people who are like, I'm tired of making my 900th bar chart. I want to try something a little different. So I have two pieces of advice.
00:18:04
Speaker
One is know how your data gets where it gets to. So for example, a lot of research will have a very interesting data gathering process. Like for example, research systems standing out in the street and gathering this data. And a lot of times as people who report and tell stories on this data, we don't ever cover that data gathering process. But that narrative is actually incredibly important to the way we understand what the data is saying. So a lot of times in the comics, the comics kind of serve as like,
00:18:33
Speaker
okay, this is what the data gathering process looked like. And then you kind of peek this curiosity in the reader's mind of, oh, I get the question that we were asking when we were looking for this data. I wonder what the data says. Yeah, that's interesting. Yeah.
00:18:49
Speaker
And so I think that's the first step. And I think virtually anyone can do that. And in fact, when you ask people who work with data these types of questions at a cocktail party, they'll do an excellent job of making it an engaging process. They'll say, first we did this, and then we did this, and then guess what we found? That's great. They're not going to pull out a bar chart from their back pocket.
00:19:13
Speaker
I mean, but those are the people who usually don't get reinvented. I think the second piece of advice I've been trying to tell this to my colleagues is there are many ways that you can try to do this without knowing how to draw. And I know it's terrifying. And I know it's terrifying because I've done it. And it was terrifying for me to think
00:19:40
Speaker
Oh, this is going to be published. Yeah, we're gonna see this. Yeah. But I think the goal is, if it takes you drawing on the back of a napkin to explain a concept better, then why not drop on the back of a napkin, take a picture of it and upload it. And the next time you'll say, well, napkins are terrible to draw. And I don't know why I did that. Let me try a piece of paper or let me try a whiteboard and
00:20:05
Speaker
or let me try Google Draw or something which is a very easy tool to use. And at the end of the day, you'll get something that helps explain a concept better. And if you can get over your ego being bruised of people saying, well, that was terrible, which people say to me all the time and I think, well, OK, that's fine.
00:20:23
Speaker
then I think we'll be able to move forward a little bit. I think there's a huge fear of this is going to be bad. And you see it all the time in like research papers and reports where you have these terrible flowcharts with, you know they want to do something more, but they're just going to use squares, lines and words in the squares.
00:20:46
Speaker
without actually exploring the concept further. At the end of the day, a flowchart is concept. At the end of the day, a line chart is a concept. They're just accepted concepts. So I think we have to be brave in that world a little bit and be terrible for a little bit. And to be honest, there are times I'll finish a story and I'll think, oh, god, that was bad. I didn't do a good job.
00:21:10
Speaker
But otherwise I wouldn't have the stuff that I think has done a good job of explaining the concept. Right. That's great. I think Be Brave and Be Terrible is a good mantra to kick people off. Alvin, this is great. I want to thank you a lot for coming on the show and letting me pick your brain now a few times on story and your approach to telling stories and communicating information. So thanks so much for coming on. It's been great.
00:21:33
Speaker
Yeah, it's been great. Thanks, John. And thanks to everyone for tuning into this week's episode. The month of story continues for another couple of weeks. So until next time, this has been the policy of this podcast. Thanks so much for listening.
00:21:56
Speaker
This episode of the PolicyViz podcast is brought to you by JMP, Statistical Discovery Software from SAS. JMP, spelled J-M-P, is an easy to use tool that connects powerful analytics with interactive graphics. The drag and drop interface of JMP enables quick exploration of data to identify patterns, interactions, and outliers.
00:22:15
Speaker
JUMP has a scripting language for reproducibility and interfacing with R. Click on this episode's sponsored link to receive a free info kit that includes an interview with DataVis experts Kaiser Fung and Alberto Cairo. In the interview, they discuss information gathering, analysis, and communicating results.