How to Be a Better Human
How to answer your biggest questions—with data (w/ Mona Chalabi)
November 28, 2022
[00:00:00] Chris Duffy:
This is How to Be a Better Human. I'm your host, Chris Duffy, and this podcast has been fact-checked by professionals. That's important to note because, sometimes as a comedian, I can get a little squishy with my facts. I care a lot about making sure that anything that I say is a good, entertaining, funny story, and I care maybe a little bit more about that than that it is exactly accurate.
In fact, at my wedding, my mother-in-law gave this hilarious toast that was a huge hit where she just took one of the jokes that I told on stage, a story that involved her, and she broke down all of the ways in which I had exaggerated or compressed things for comedic value. As she said, “When you hear Chris say something on stage, you gotta just remember five little words: didn’t really happen that way.” Perfect toast. Perfect roast. She nailed me.
Now, Mona Chalabi, today's guest, is all about making sure that we look at reality accurately. She uses her artwork, her data visualizations, and her journalism to make sure that we dig into the data, we check our sources, and we end up with stories where it did happen exactly like that.
Mona is also a good friend of mine. We met when she interviewed me in New York City years ago for one of the stories, and since then I have always been so impressed with her take on the world and how she uses data to always leave me with so much to think about. I am so excited for you to hear from her today. I think she is just the best. Here's a clip from Mona to get us started:
[00:01:25] Mona Chalabi:
So I really wanted to show people the way that data relates to their everyday lives. So I started this advice column called Dear Mona, where people would write to me with questions and concerns and I would try to answer them with data.
People really ask me anything, questions like: is it normal to sleep in a separate bed to my wife? Uh, do people regret their tattoos? What does it mean to die of natural causes? And all of these questions are great because they really make you think about ways to find and communicate these numbers. If someone asks you how much pee is a lot of pee, which is a question that I got asked, uh, you really wanna make sure that the visualization makes sense to as many people as possible.
[00:01:59] Chris Duffy:
Mona has dug into questions like those and so much more in her art and in her TED podcast, Am I Normal? Now, if you wanna know the answer to that question, are you normal? Well, you're just gonna have to stick around. We'll be right back with more from Mona after this break.
[00:02:18] Chris Duffy:
Okay, we're back. Today, we’re talking about data, we’re talking about art, and how to think critically about the information we see in front of us with Mona Chalabi.
[00:02:28] Mona Chalabi:
Hi, I'm Mona Chalabi. I'm a data journalist and an artist.
[00:02:32] Chris Duffy:
That's kind of a unique combination. We don't often think about artists as having an interest in numbers. In fact, often the stereotype is that artists are like completely useless when it comes to numbers. So how did you combine those two worlds?
[00:02:43] Mona Chalabi:
When I moved to the US, I moved to work for a company that shall not be named. It's the Voldemort of data journalism companies.
[00:02:54] Chris Duffy:
[00:02:54] Mona Chalabi:
I just, I moved to the US and I very quickly realized that I despised the job and it wasn't a good fit. And so I kind of just, like, knuckled down in my little cubby-hole and would draw. Um, I was never that kid in class that, like, doodled in the margins, I think. ‘Cause I wasn't ever bored in class, but I was very bored in America in my first job. So I started to draw and then started to post them online and, yeah, it kind of went from there.
[00:03:21] Chris Duffy:
I wonder if you had a similar thing to me too, where, you know, when I was working as a teacher, I was doing comedy. It seemed fun, but it just never seemed like a job. Like I was like, how do you—
[00:03:29] Mona Chalabi:
[00:03:30] Chris Duffy:
—how do you pay the bills as a comedian? That’s just not a real job. Like you can't apply for it. No one takes your resume. I wonder if you thought similarly about the title like artist?
[00:03:37] Mona Chalabi:
A hundred percent. Like when I was a kid, I would draw all the time, and I think I very quickly understood, also from some parental nudges, that that was not a serious career. I remember my mum saying, “You know what's really, really artistic?” And I was like, “What?” And she was like, “Becoming a plastic surgeon.” Hello.
[00:03:58] Chris Duffy:
The most artistic of doctors.
[00:03:59] Mona Chalabi:
So yeah, I just understood that wasn't serious. And actually from a really, really young age, I was quite concerned with making money, which I know sounds really, really gross. But I was always worried about financial stability and believing that something wasn't really a viable career kind of took it off the table for me.
[00:04:15] Chris Duffy:
Well, in some ways, that also is the place where art and numbers really do intersect, right? Like every artist, even the ones who hate data and don't think of themselves as numbers people at all, everyone has to figure out, like, how do you make it come together at the end of the month?
And some people do that with success and less stress, and some people do it with not as much success and a lot more stress, but certainly, that is, uh, one place where numbers and art have always intersected.
[00:04:38] Mona Chalabi:
Yeah, definitely. And again, I think it’s, like, widely understood that there is a fundamental tension between those two things. Like if you are interested in going into investment banking and you know, earning enough money to live, there's no tension between those two objectives, you know?
[00:04:53] Chris Duffy:
No one's ever like, “How am I gonna make ends meet? I just wanna be an investment banker. That's my passion.”
[00:04:57] Mona Chalabi:
Exactly. Exactly. Poor little guys. Um, I'm saying that sarcastically, obviously. Yeah.
[00:05:04] Chris Duffy:
Of course, yes. Was there a moment where things changed and you thought like, “Oh, actually this could be a career?” Or was it more of a, a kind of a gradual shift?
[00:05:13] Mona Chalabi:
It was definitely gradual. But you, you know what was a bit of a game changer? Jerry Saltz at New York Magazine, this is when I had like, I don’t know, like 120 Instagram followers.
Somehow he found a chart that I had posted on my Instagram account and reposted on his, and I got, like, an instant bump of a thousand followers. And it was that thing of like a) understanding. I know there's so much critique of social media, and rightly so, but I understood that those little followers that I could, I, I had kind of accrued, would translate into an audience and that, that was a really, really powerful thing. But also it was like, it was really validating to have someone who was an actual legitimate art critic—
[00:05:50] Chris Duffy:
A Pulitzer Prize-winning art critic.
[00:05:51] Mona Chalabi:
Yeah, exactly. I, I dunno if he'd won it at that point. Probably? Maybe?
[00:05:56] Chris Duffy:
He won it for sharing your post.
[00:05:58] Mona Chalabi:
But yeah, to have him share my little chart on male circumcision rates by US region made me really happy.
[00:06:04] Chris Duffy:
So, okay. This is again, another thing, right, that makes you unique is your, your topic choices. So like male circumcision rates across the US, that’s in, a subject of an art piece for you. That’s also data journalism.
How do you think about like, what makes a Mona piece versus something that you wouldn't cover? Is there a rule to the types of topics that you, you're interested in?
[00:06:27] Mona Chalabi:
I’d say there's no rule, but they tend to all be, like, quite political, very often framed around social justice, or else they're kind of like slightly taboo topics or things that people might not necessarily talk about. So I think the male circumcision rate one came about after like I got drinks with colleagues and the male colleagues were telling each other, like, who was circumcised and who wasn't. But only at my, after me kind of asking and starting that conversation, it didn't come naturally, and I was like, ah!
[00:06:55] Chris Duffy:
That feels like something that you initiate, knowing you. Otherwise, I was like, “Wow, you just happened to walk into your absolute ideal conversation to have wandered into that.”
[00:07:05] Mona Chalabi:
No, no. I started it. And again, you, you really do get away with so much by having a British accent in America. Like, it’s obscene. Look at what these late-night show hosts have achieved just from having a British accent.
[00:07:19] Chris Duffy:
It's also true though, something that I noticed with you, even just in conversation as friends is much more so than other people, if I say something and I'm just kind of saying it and it doesn't seem true, other people will kind of be like, “Uhhuh, Uhhuh.” And you're always like, “Wait a second. Is that what…is that true that that's actually the case?”
Like, if I say something of like, “I always just help my parents out with, uh, with their computer stuff.” And then you'll be like, “Is that… How often do you do that?” You know, like you are, you drill down into the, the questions and, and I think that leads to, to me being like, “You know, actually it’s true. I don't always help them. Sometimes they figure it out on their own.”
That's not an actual example, but I think you know what I'm saying, which is that you're very interested in kind of like fact-checking and what, where our, our evidence comes from and what, what, we're actually backing up what we say with.
[00:08:04] Mona Chalabi:
We kind of like build up these narratives of who we are and what the world is like around us. And I think when data is, is handled really, really well, it allows us to kind of challenge those hypotheses. Right? So in some ways, kind of what I'm asking you for there is data. Like I'm not asking you to literally look through your phone and look at, at like some kind of weird catalog that you've kept of every time that you helped your parents.
But I'm asking you to, like, critically examine that narrative that you tell yourself that has characters, a beginning, a middle, and end, and ask yourself to kind of reexamine the evidence to see whether or not that's true. And I think what you very often end up with is like a “Yes and…” or a “Yes, but…”
And that, what comes after that little caveat is normally really interesting and fruitful for like further exploration. So, like, to give the hypothetical example that you just gave, maybe it's true that you help out your parents, but maybe it’s, like, only in periods where you’re, you have less work, right? And then, and then it's an interesting conversation about like, how do we manage our responsibilities professionally with our responsibilities towards friends and family? And is it possible to do both at once?
[00:09:15] Chris Duffy:
I'm curious also: how would you—even just starting at the most basic thing—how do you define data?
[00:09:18] Mona Chalabi:
Ooh. Data to me is more than one voice in the room. So, like, a spreadsheet when you open it up is lots of different… I don't know, like most of the data sets I'm looking at are about people, but obviously there are data sets about animals. You know, all of these kinds of different things. But the data sets that typically interest me most are about people.
[00:09:41] Chris Duffy:
In your podcast, Am I Normal, you have an episode called Should I Move Home? Right? And in that you're deciding, “Should I stay in New York City? Should I move back to London?” And you're using data that I think anyone would typically think of as data, right? Like spreadsheets and numbers about livability and social indicators. But then you're also using factors like cues from nature and your mother's health and your feelings, and those I think sometimes we don't necessarily think of as data, but it seems like you do.
[00:10:07] Mona Chalabi:
Yeah, they are right? Like even if you're like thinking about whether or not to end a relationship and you grab a piece of paper and draw two columns that say like, stay and go. Each point that you have bulleted under those two columns is data, right? Like it's just evidence. It’s, it's information that you are using to guide you through, like, the chaos that lies ahead.
[00:10:31] Chris Duffy:
That's pretty beautiful definition of data, actually: information to guide you through the chaos that lies ahead. So if you were talking directly to one of the people who's listening to this show, who doesn't know you personally, what do you think are ways that a regular person should change the way that they think about or change their relationship to data to have it be healthier or more ac—more accurate?
[00:10:54] Mona Chalabi:
I think a lot of people approach data with fear or anxiety. These kind of like self-perceptions: “I'm not good at math. Um, this is too complicated for me.” And that's the thing that I really, really want people to set aside. And the great thing about data, right, is that there are stories in it. Like the methodology is inherently a story.
You have a group of people who set out with a question. This is how they tried to answer that question, you know, whether it's like having 20 college students track their diet for a week, you know, it's all storytelling. So if you can, if you can get your head around how the data was collected, then by the time you open up the spreadsheet, hopefully, you won't feel so disoriented.
So, I think that's the biggest thing to lose. And unfortunately, I actually think a lot of people that work in data, it kind of benefits them to have this arrogance and to uphold this myth that what they do is incredibly complex and only they are qualified to do it. And I just kind of think that's bullshit. Yeah.
[00:11:49] Chris Duffy:
Yeah. I, I feel like I have, over the course of my career, interviewed many, many scientists, and one thing that I always hear, and that's interesting is that the people who are the absolute best at explaining their work and making it so that everyone understands it, they're like, “This is actually not considered a strength. It's kind of considered a liability. Right?”
[00:12:06] Mona Chalabi:
[00:12:07] Chris Duffy:
Because if you can have a dense paper that only your peers can understand, people are like, “Whoa, she really gets it.” But when you talk about it in a way that a 10-year-old can understand, people are like, “It can't be that complicated. A 10-year-old understands.”
[00:12:17] Mona Chalabi:
Yeah. Yeah, yeah.
[00:12:18] Chris Duffy:
In my opinion, it's actually the opposite, right? Like, the people who really understand it can communicate clearly, but there are benefits to, to being a little more obtuse in, in a lot of these worlds.
[00:12:27] Mona Chalabi:
I totally agree, and I also think I, I can understand why people get worried that when you simplify it, when you leave the caveats behind to create a clear story, sometimes that obscures reality.
But what I would say is that, like, when you simplify, you give audiences the opportunity to ask those follow-up questions and understand the caveats. And if you don't do that first step of simplification, all of that information just remains behind a wall that's kind of completely inaccessible.
[00:12:57] Chris Duffy:
Okay, we're gonna keep things accessible and hopefully exciting, but we've also gotta keep the lights on. So we're gonna take a short ad break, and then we will be right back. Don't go anywhere.
[00:13:11] Chris Duffy:
And we are back. We're talking with data journalist and artist Mona Chalabi about her work. And if you've never seen Mona's drawings and visualizations, stop what you're doing and go check them out. Mona has such a cool, distinctive visual style. It's, it's beautiful, but it's also very approachable. There are drawings that feel very clearly made by a human, not like slick or pretentious in any way. And, and that is a style that Mona has very consciously cultivated over the years. Here's her talking more about that in a clip from her TED Talk.
[00:13:41] Mona Chalabi:
See a lot of data visualizations will overstate certainty, and it works. These charts can numb our brains to criticism. When you hear a statistic, you might feel skeptical. As soon as it's buried in a chart, it feels like some kind of objective science, and it's not. So I was trying to find ways to better communicate this to people, to show people the uncertainty in our numbers. And what I did was I started taking real data sets and turning them into hand-drawn visualizations so that people can see how imprecise the data is. So people can see that a human did this, that human found, its a and visualized it.
[00:14:13] Chris Duffy:
One way to demystify stuff is to keep it really simple or to find the way to say it really simply. But then it seems like another way is to change the form or change how people experience it. And, in my opinion, a lot of what you've done has been to bring people in through the visual art piece of it, where it just feels, it doesn't feel like they're looking at a deep spreadsheet.
It doesn't feel like they're looking at a 20-page research paper. Instead, they’re seeing something that you have an immediate emotional connection to. So, how do you think about that piece of it? How do you use art in this?
[00:14:43] Mona Chalabi:
Yeah, I feel like… So one of, one of the things that I learned quite quickly in journalism is this idea of a bounce rate. Do you know what a bounce rate is?
[00:14:50] Chris Duffy:
I actually don't know.
[00:14:51] Mona Chalabi:
Okay. A bounce rate is figuring out the percentage of readers that come to a, an article, like they've clicked on it, and then they immediately exit. Right? And you don't really count them as readers because they came to the page and they either suddenly got overwhelmed or suddenly got bored or lost interest and left.
And I think that the definition is that you was on the page for like less than three seconds. Something like that. And an enormous proportion of readers just bounce, right? And I think that says so much. You know, people always put it down to like, “Oh, we've lost our attention span. We've become like goldfish.” All of those things.
And I'm like, “No, no, no.” It's on us as journalists to retain people, like we are the ones who have messed up. If I've written a headline that doesn't engage you, then I've done something wrong. So, I think that was a big part of it for me, is like figuring out how to retain people. And one of the things that I realized quite quickly is, is kind of the power of a bait and switch, right? Which is a really subtle thing to do. Like, I don't wanna do a bait and switch of saying to people, “COVID is X. No, wait, it's Y.” That's really, really dangerous. Right?
[00:15:58] Chris Duffy:
[00:15:59] Mona Chalabi:
But if I can kind of make you think, “Oh, here's a nice illustration. Oh wait. It's actually a piece of information”, then that to me is actually a really, really powerful bait and switch.
This podcast is in some ways a bait and switch. Like you think it's gonna be this super, like from the title of it, it's gonna be maybe really, really heavy, and then you're like, “Oh no, it's actually just a really like, easy conversation about things that matter.” You know? Is that, is that a bad way to describe it?
[00:16:22] Chris Duffy:
No, I, I was wondering, I was curious where you're going, but I agreed that it's a bait and switch in, in the way that you're saying it. Yes. I always, I always feel like that about the title, where it's like, in some ways, it is extremely explicitly what we're gonna talk about, but in other ways, it comes with all these connotations that I think that we subvert, or I hope that we subvert.
[00:16:38] Mona Chalabi:
[00:16:39] Chris Duffy:
What you're saying makes me think about how lot of times design is undervalued or disrespected, right? It's like, thought of as like not serious, right? Like if you're a serious journalist, you shouldn't care about design. But if someone clicks on your headline and then the page is so overwhelming that they close it—
[00:16:54] Mona Chalabi:
[00:16:55] Chris Duffy:
—it doesn't matter how great your journalism is, right?Like in some ways we have to design things and we have to think about the visual piece because otherwise, the information does not get across.
[00:17:04] Mona Chalabi:
I mean, to me the word design just means accessibility. And every journalist, I don't care how much, you know, there are some journalists that, that say they, they live to, like, kind of higher ideals.
But I just, I just think everyone cares about audience. Who wants to just be writing in a cave with, like, no one hearing or seeing the things that you're doing? And if you want an audience, you need to care about the barriers that affect people being able to read your work.
And by the way, this can mean all kinds of things. It can mean the amount of ads that are on the page. It can mean the font size. It can mean your linguistic choices. Are you using verbs and nouns that people who speak English as a second language might not be able to grasp? And by the way, the beautiful thing about good design, about accessibility is that once you let one group through, You automatically let other groups through.
So if you write in a way that is accessible to people who speak English as a second language, guess what? People who maybe have a different educational background might also be able to understand your work in a different way. And that goes for our physical spaces too, right? Like, we know that if you manage to make a building accessible to somebody with a pushchair, someone who has a wheelchair will also be able to get in through the front door.
And it's funny that we think of that when it comes to architecture, but we don't have the same set of tools, necessarily, when it comes to information design.
[00:18:23] Chris Duffy:
I know that that's something you think about. I mean, you designed an audio chart for the visually impaired, right? This, these are pieces that you have thought about when you're taking data and artwork and trying to make that accessible. How does that play out in your life right now?
[00:18:35] Mona Chalabi:
Yeah, because most of the data journalism I create are data visualization. So, I'm thinking about people who are either blind or visually impaired, and how can you either write out full image descriptions that ensure that people will be able to understand what is embedded in that chart, or can you actually use sound/pitch tone frequency to communicate that same data?
But it's funny, just as you are asking me this, I'm actually working on an animated TV show right now, and just last night we were designing a character who is visually impaired, right? And I'm thinking about the design. This has got nothing to do with information design. It's just sim—like straight-up design.
How can I draw this character in a way that a) doesn't stigmatize visual impairment, but also feels, uh, I don't know, he’s like a good representation of vi—like it's not just about avoiding bad representations. It's like, “How can this be a great representation of visual impairment?” So, just to actually be super explicit, one of the things that people threw out was the idea that like the character has mismatched socks, which is how you know they're blind.
And I was just like, “I'm not into it.” I'm just not into it as a depiction of visual impairment. And yeah, the hope is that by creating a better character, people who are visually impaired will be able to better relate to that character.
[00:19:50] Chris Duffy:
Well, thinking about representation, and I know that other times you do it a little bit more subtly or maybe even just at this point unconsciously, where you're drawing people who look like you, who look like people in your family who don't fit the kind of like, classic white illustration of a human being when we're having a data illustration. I wonder if you can talk about how that matters to you and how that process has evolved for you in, in terms of like drawing representation in where it's not explicitly the, the focus of the illustration, if that make sense.
[00:20:21] Mona Chalabi:
So one of the goals of the data visualizations is to use as few words as possible, right? Because it makes the information easier to digest, it makes it more aesthetically pleasing. So let's say I wanna show a chart on, like, podcast host salaries, right? And I wanna show it for men and women. If I don't want the little labels down there that say men and women, how can I represent gender in the chart itself?
Back when I first, first started out, I don't know, I did things like bananas and oranges. Or by the way, there's obviously completely sidestep the fact that there is so little data that is collected about all kinds of different minority groups. So in this specific example, I highly doubt that any data is collected on podcasting salaries for trans or non-binary people.
You know? So, it's a real challenge, I think, to, to figure out visual depictions that don't reinforce stereotypes. You mentioned race, and that's another great one, right? So if I, instead, I'm trying to show podcasting salaries by race or ethnicity, maybe I'm drawing, you know, hands holding microphones in. The height of the microphone indicates salary.
Exactly which skin tone am I gonna use in the chart to indicate Black, Hispanic, white, Asian? Because again, we know there are, there are people who identify as Black who might have lighter skin than someone who identifies as Hispanic. But if I play with that in the chart, maybe suddenly the information is actually quite hard to understand.
[00:21:44] Chris Duffy:
Understandable to who?
[00:21:45] Mona Chalabi:
I mean, I don't really think I'm answering a question except say like, these are really, really tough questions, and one of the things that I hope that I do is I, I treat it as a conversation, right? So I invite in the comments. I respond to feedback in the comments of someone saying, “Hey, this was confusing on me” explaining, “But I did it this way in order to like break down stereotypes about this thing.”
And I also hope that to a certain extent, I don't really think you can bank on this, so it's a bit naive, but sometimes I do hope that your work is kind of treated more holistically rather than these individual pieces. So yes, I might have drawn Black, Hispanic, white, and Asian stereotypically the color tones in this chart.
But here's this other chart that I also made about colorism, which is, like, specifically discrimination based on specific skin tones among people of color. And like, let me point you to that, to show how I have thought about that thing.
[00:22:38] Chris Duffy:
Yeah, I think that makes a lot of sense. Say you've decided that you're gonna make, and maybe you could even give us a recent one that you did, but you're gonna make one of these charts. How do you start? How do you start to evaluate the data to find that? Where do you find it, and then how do you actually do the, the visuals? Like, what is the first steps in, in drawing the actual art?
[00:22:55] Mona Chalabi:
As one example, the New York Times approached me and said, “Hey, we'd love to do a data visualization from you, and the theme of it is about summer.” So it's super broad, right? And I responded to the editor saying, “Summer makes me think of sweat. I was sweaty. Everyone that I knew was sweaty, everyone was complaining about sweat. How's that as a subject?” And they said, “Yes, that sounds great.”
So my next step is to kind of do like almost what you call a literature review, where you're kind of understanding like what is the research that exists around this huge subject. So, there's research about why our bodies smell. It’s so funny as well, the things that you run up against when you're doing this research. So, so much of that data is just based on heterosexual couples and this idea that women are, like, hunting down male males to mates with based on body odor.
Like it’s… I personally find it quite problematic. Anyway, there's that research. There's research about which parts of our bodies sweat the most. There's research about, um, sweating rates by like body type, by BMI. So basically I sent over to the editors, “Here’s the research that I found.” They said, “This is what we are really, really gravitating towards.”
And then I start kind of pencil sketches of the character and then I move on to ink sketches and then very often, I would color it digitally. I'm kind of hesitant to talk it through that way though, ‘cause the truth is, it like totally depends, like, you know, sometimes I'm not working with an editor. Sometimes I'm just working by myself.
[00:24:19] Chris Duffy:
You obviously have so many years of experience now I, I imagine that you sometimes come across some sort of paper or some sort of statistic and it immediately smells fishy to you. You're like, “That's not, That doesn't seem plausible.”
[00:24:29] Mona Chalabi:
[00:24:30] Chris Duffy:
What are some of the hints that make you think like, “I need to look twice at this”?
[00:24:36] Mona Chalabi:
So I'm gonna give two pieces of advice that seem to completely contradict each other, right?
[00:24:40] Chris Duffy:
[00:24:41] Mona Chalabi:
So the, the first piece is avoid statistics that feel overly precise, right? So if you hear something like “22.46% of Americans believe X”, how is it possible to know to two decimal places what an entire country thinks?
Like, that is just fundamentally suspect. There's no way that every single person in the country was polled for their opinion on this thing. So, I would say there are very few things, with the exception of, like, some phenomena in the, in the natural world, like some scientific phenomena that can be measured to decimal places at all. So kind of like, if someone is over-saying accuracy, ignore it.
And similarly, if it's like so vague, like “One in two Americans believe X.” Well, that also feels like a kind of nothing piece of research, like one in two. What do you mean? What do you mean? What is that really telling me? And yeah, when it's that, that vague, very often I have a series of follow-up questions, which is like, “one in which two?”
So, a really important thing is to kind of question the denominator. So the denominator is, you know, in the fraction, it's the thing that lies beneath the line. If we're saying, I don’t know, “One in two Americans eat a ham sandwich every day”, who was polled? And sometimes what you find is that the denominator, the people who constitute that research all come from one specific demographic group.
So, like, it will only be Midwestern lorry drivers that were asked. I don’t know if this sounds really offensive now that I just think Midwestern lorry drivers eat ham sandwiches, but you get the idea.
[00:26:13] Chris Duffy:
That feels probably true that there's a per—a high percentage who have eaten a ham sandwich if you drive a truck and live in the Midwest.
[00:26:20] Mona Chalabi:
[00:26:20] Chris Duffy:
My uncle is a Midwestern truck driver, and I've definitely seen him eat a ham sandwich.
[00:26:24] Mona Chalabi:
There you go. See? Perfect, perfect research.
[00:26:27] Chris Duffy:
Yeah. That’s my… The denominator there is one. Of the people that I know who are Midwestern truck drivers, one, a hundred percent of them eat ham sandwiches.
[00:26:35] Mona Chalabi:
My hunches are perfect, are perfect. And I mean obviously, that's a really, really silly example, right? But the stakes of some of this are, are much higher.
So, you know, there was a piece o f research that said, um, some unbelievably high percentage of American Muslims when they were asked believed in, uh, Sharia Law. First of all, turns out that research was conducted by Kellyanne Conway's polling company, so, interesting source.
Second of all, it was an online poll, so absolutely any, absolutely anyone on the internet could go and fill that out. And thirdly, there was a question further down that same survey that said, “How do you define Sharia law?” And something like 80% of people described it as your individual personal struggle to be closer to God. So it's like, oh, well then it becomes a lot less scary that people are interested in pursuing Sharia law. You know?
[00:27:29] Chris Duffy:
Do you think that in an ideal world that all of the rest of us would dig in to data that… every time or how often would we be doing this?
[00:27:38] Mona Chalabi:
[00:27:38] Chris Duffy:
‘Cause it does seem a little overwhelming to like, every time I see a statistic go into the background of it.
[00:27:43] Mona Chalabi:
A hundred percent, I understand that that can be a really, really exhausting endeavor. All I would say is, like, maybe put that effort in to understand which sources you trust and fact-check sources, and then like, maybe you can become a little bit lazy, right? Like I know that when I've checked out New York Times articles, I know that the standard of journalism is so high that honestly, the fact-checking is pretty rigorous.
And I know that when I've fact-checked, for example, articles from the Daily Mail, that standard of journalism is very, very different. So that allows me to be a slightly more lazy reader where I can just consume an article from the Daily Mail and kind of dismiss it out of mind and consume an article from the New York Times without then spending one hour checking every single claim within it.
[00:28:28] Chris Duffy:
That seems to me to be like one of the main, or a large issue of our time, is the kind of lack of context that we get where, you know, you see something online. The, the two links look exactly the same size. They're in the same font, and one of them is, you know, some person who is completely making it up and they're writing it because they have a huge bias.
And the other is, you know, a process of a journalist, a fact checker, an editor, and all of that. And that those are presented on the same level, often creates so much of the issue for us that they seem equivalent and they're really not.
[00:28:59] Mona Chalabi:
Can I give an embarrassing example of where I've messed up in that?
[00:29:02] Chris Duffy:
[00:29:02] Mona Chalabi:
Because I think, you know, I don't wanna give the impression that I’m, like, such a pro. I was reading an article about a guy that attempted to have sex with… He was, he was on quite strong hallucinogenics, attempted to have sex with a crocodile and was killed.
[00:29:17] Chris Duffy:
I'm so sorry to his family to laugh, but that framing of it is funny to me.
[00:29:21] Mona Chalabi:
Well, that prompted me to write an article about all of the different animals that people have attempted to have sex with. I would say this is quite a few years ago when my style of journalism was slightly trashier, let's say. Anyway, wrote the article, and then someone was like, “No, no, no. That article that you cited at the start about the man who attempted to have sex with the crocodile, it's Australia's version of The Onion.”
And I had like landed on this page and was like, you know, and honestly, like the Onion, if you come from a whole other country and you land on that website, you might not necessarily get it.
[00:29:56] Chris Duffy:
You would not necessarily know that it is a satirical newspaper that is all jokes.
[00:30:01] Mona Chalabi:
But also, also in defense of me back when I wrote this article, there are Onion articles that have in fact turned out to be true.
[00:30:09] Chris Duffy:
[00:30:10] Mona Chalabi:
Because the world that we are living in now is so farcical in terms of extremities. Right?
[00:30:15] Chris Duffy:
Yeah. And also, you know, I think with the importance of, of fact-checking, you know, one thing that is, is unique for me is that this podcast is fact-checked, right? TED and PRX take, take fact-checking very seriously.
And so I often, in a way that actually my wife, Molly thinks is hilarious, and she wishes that I had these fact-checkers, that Erica and Julia followed me around all the time because they will very frequently be like, “Can you back that up? Or if you can't, we're gonna need to cut it.” And then I'm like, “Oh, I guess I can't back that up at all. I just said that. It seemed like a fact.”
And so what the listeners hear is a polished, much more fact-based version of me than you would hear if you were just having a conversation with me.
[00:30:53] Mona Chalabi:
But what's interesting is I wonder if naturally, your verbal mannerisms have changed. Right? So I will say “about”, or “roughly”, or “I think” instead of “I know.”
[00:31:07] Chris Duffy:
I know I now say “It felt like…” ‘cause I used to say “And then I got hundreds of angry emails”. And now I'll say like, “I felt like I was getting a lot of angry emails.” Because that has happened a few times where they've been like, can you forward us just some examples? And I'm like, it turns out it was two people and they were, like, mildly a little tiffed.
Well, thinking about your, your artwork too, something that's amazing and, and I think makes total sense once you see your art, but is you have people who have… many people who have framed in their homes your data visualizations, right?
Like people buy those, they frame them, they view them, and perceive them as a work of art. And I believe right now, if not very recently, you had a, a, big installation outside the Brooklyn Museum of your visual art. So, how do you think about the artistic value versus the informative value? Is one more important to you than the other? And how do you balance those?
[00:31:59] Mona Chalabi:
I really think of them as having completely equal value. I think that when you kind of sacrifice the aesthetics, you just lose people. And, and the problem with that is that you also lose the retrievability of the information, right? So like, let's say I'm creating a chart on the importance of wearing masks during a pandemic.
If I can make the chart look nice, not only will you be more likely to read it, but I think you will be more likely to remember it, and being able to recall information is just as important as that first instance of consumption. So I think beauty is very often overlooked, and it's something that I'm constantly striving towards, but obviously, I'm still a journalist, right? Like, if the chart is wrong, that's a disaster. It really is. Yeah.
[00:32:49] Chris Duffy:
Well, the show's called How to Be a Better Human. What is something—it can be a book, a movie, a piece of music, a podcast, it can be anything, it can even be a person—that has helped you to be a better human in your life?
[00:33:02] Mona Chalabi:
I have been thinking a lot about the ways that my mom has really, really like imparted a set of principles that I think have been really, really valuable.
This is so silly, but I recently found a home video and I think it's the only home video that we have of us as children, and my dad had just bought, like, a camcorder. It’s me and my sister's joint McDonald's birthday party. We come running down the stairs in these ornate dresses, and I say, “Hi, my name is Nadia.” And my sister giggles and say hi and says “Hi, my name is Mona.”
Like it's really dumb slapstick. And my mom, you just hear her on the video camera being like, “You don't tell lies.” And it sounds really, really intense, but actually like it was the only rule in our household pretty much. There was like so much freedom but, like, “never lie” was so clearly imparted to us and I really think it's like it's quite a good basic moral principle, you know?
[00:33:58] Chris Duffy:
Yeah, absolutely. And it's the thread of so much of what you do, right, is to try and find the truth and to not lie. Well, Mona, it's been such a pleasure talking to you. Thanks so much for being on the show.
[00:34:09] Mona Chalabi:
Oh you too, Chris. Thank you. Honestly, you're such a good show.
[00:34:15] Chris Duffy:
That's our show for today. This has been How to Be a Better Human. I am your unreliable narrator, Chris Duffy. The facts in this episode have been checked, but you know what? Don't trust me. Dig into that data for yourself. Today's guest was the one, the only Mona Chalabi. You can hear her podcast, Am I Normal, wherever you’re listening to this.
And you can follow her online at @MonaChalabi. That’s M-O-N-A-C-H-A-L-A-B-I. You can put a .com after that and it'll take you to her website. Incredible. You can also put that into any social media site, and you will almost certainly find her, and I really recommend following her because she's a great follow.
From TED, our show is brought to you by Jimmy Gutierrez, who never mixes hallucinogens and crocodiles; Anna Phelan, who is eating a ham sandwich in her truck right now; Rithu Jagannath, who has also been researching why our bodies smell and come to some very different conclusions than what Mona came to; and then, Erica Yuen and Julia Dickerson, they fact-checked the rest of the show but then let me say whatever I want during the credits, which is a loophole that I love. I love a good loophole.
And from PRX, Jocelyn Gonzales and Patrick Grant, who are putting the finishing touches on a hand-drawn sketch of me, which will be on display at the Brooklyn Museum soon if I have anything to say about it.
Thanks, most of all, to you for listening to our show. Thank you for letting us be the source of even a tiny amount of the data in your life. This is the last episode of season two of How to Be a Better Human, but great news! We will be back with a season three right at the beginning of 2023. We're gonna start off January strong with some new episodes for you.
Please share this show with a friend. Leave us a positive rating or review. Thanks again for listening, and have a great couple weeks.