Short Wave - Confessions Of A Math Convert

Episode Date: December 20, 2022

Math is a complex, beautiful language that can help people understand the world. And sometimes math is hard! Science communicator Sadie Witkowski says the key to making math your friend is to foster your own curiosity and shed the fear of sounding dumb. That's the guiding principle behind her podcast, Carry the Two and it's today's show: Embracing all math has to offer without the fear of failure. We encore this episode in between Carry the Two's seasons - their second one starts on January 3, 2023!This episode was produced by Berly McCoy, edited by Rebecca Ramirez and fact checked by Rachel Carlson. The audio engineer was Josh Newell. See pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences.NPR Privacy Policy

Hey there, shortwavers. Back in August, we talked with Sadie Wachowski about her math podcast, Carrie the Two. It's all about exploring the math that sneaks into our everyday lives. And she's launching season two on January 3rd with a NASA-centered story. So today, we're going to listen back to our original episode in preparation for liftoff. T-minus 10 and counting. You're listening to Shortwave. from NPR. Growing up, Sadie Wikowski did not consider herself a math kid.

In high school, I was sat between like a 12-year-old kid who was in calculus and a kid who was a couple years behind me, and they'd compare quiz grades on my desk. And they were always like, would you get, Sadie? And I had to hide my grade because it was a B-plus that I felt so bad about it. And even though a B-plus is a fine grade, she chose, as many people do, to avoid it. math. And so I was like, I'll go into neuroscience. They don't need math. Turns out it's all statistics. But even with the statistics, she loved her research on sleep and memory. And it also

led her to another passion that would eventually steer her even closer to a numerical niche. A lot of that research requires sitting in a dark room, waiting for an undergraduate to fall asleep. And so it's just like a lot of sitting in a dark room, watching brainwaves on a computer screen, twiddling your thumbs. And so I got really into podcasts. And that got her thinking about pursuing a career in science communication. So while finishing her PhD, she was looking for a job that would keep her in Chicago. And the Institute for Mathematical and Statistical Innovation was hiring. Her job? And this is our math podcast, Carrie the two. Uh-huh, creating a podcast dedicated to all things math. And I was just like, yes, please,

Let me be as creative as I want, trying to explain a thing that used to stress me out and see if I can make it less stressful for other people. Yeah. Turns out everything behind 5G and cell towers is a bunch of math and not the fun conspiracies about all the birds being fake robots or something. So these days, Sadie is all in on integers with the podcast Carrie the two. My co-host is Ian Martin, and he's a high school choir teacher. Maybe you should be the one taking the lead. Oh, no. Oh, I teach choir and, like, the most math we do is counting.

And even then, it's usually only to four. And then you've got to repeat again. One, and two, and three, and four, and one, and two. He really loved math in high school, but he totally didn't take any math classes in college. I knew that he would be a really fun co-host because he has that innate curiosity. And he has no fear about sounding dumb. He's just like, what's that? Explain this to me. So today on the show, we talk to Sadie about learning to love math.

and all the ways it can illuminate the world. I'm Aaron Scott, and you're listening to Shortwave, the Daily Science Podcasts from NPR. Okay, Sadie, so you've got to forgive me, but it seems like starting a math podcast is a, I don't know, tough equation. I mean, math is so visual, it's theoretical, there's all the A plus B equals C, and then complex symbols. How do you approach math in a podcast?

We definitely treat this as putting cheese on broccoli. We're trying to give you something healthy and good and interesting, but like, yeah, we're going to put some tasty treats on top that make for funny stories or interesting anecdotes. And we really try to make sure in every episode we're getting across an idea of kind of a subfield in math, but we're not trying to read aloud equations because people think of math as just being the equations and this memorization. And I think it gives people a lot of anxiety.

they're like, surely this is too complicated for me. But when you actually speak to the mathematicians and researchers doing this work, they have really clear and interesting ideas and problems they're trying to solve. But you have to get there and then work your way back down and figure out, okay, what level of detail is appropriate to explain this really cool big idea and how they're tackling it. And so, I mean, you aren't, as you say, focusing on the equations or the theory side so much is focusing on real-world applications. Can you talk to us a little bit about why,

math is important to real life? Secretly, anything that you're trying to figure out, it's going to come back to math, to these really interesting math theories and models and ways of understanding the world. And you really need that math to get to that basic level. But it all also scales back up into how do self-driving cars work and how do they interact with human drivers? Or what the heck is 5G? I mean, how does all that work? I mean, it is electrical engineering, but ultimately, it's all math.

I'd love to talk a little bit about how you put that into practice with your first episode, which is with the mathematician and computational biologist, Carrie Diaz Eaton. Would you introduce us to her and the research you're focusing on and how it gets it, that idea of it's all math? So Carrie was our first guest. I had interviewed her earlier because she had given this great talk all about diversity, equity, inclusion, and justice, and using mathematical tools to reflect on. kind of the scientific and mathematical community at large. And so our first episode was focusing on this report titled Data Science for Undergraduates,

Opportunities and Options. The interim report came out in February, and then the final report was released six months later in August. And basically, she read the interim report and thought it was really great at covering diversity and equity and inclusion, but then the final report seemed to be missing those aspects. And opened to the table of contents and said, well, where the heck is the chapter on broadening participation? And the authors explained that they had infused it throughout the document, but she went through and used actual mathematical techniques. So step one, pick keywords.

Okay, so in this case, since we're talking about diversity, equity, and inclusion, I'm assuming those would be good words to look for? Exactly. The second step is to just look at the change in frequency of use between the interim and final report. She found, unfortunately, but a little bit to no one's surprise. The second most dropped word from the interim to final report was diverse. No. She found that just discussions of broadening participation were totally dropped, or they were reframed in this way of not it's important to include students in these fields and that it will benefit the fields, but that the field would be a benefit for these students. And so it became not about actually including people, but saying you should want to be a part of this.

And she mentions that it's a field that is so new, it hasn't even settled on a name yet, although there's a couple options, things like quantitative justice. So I'm curious, you all have put out a few episodes now, and the second one is all about honeybee swarms and group decision making, which is definitely on the lighter side. Why do you choose Carrie in her research as your opening episode? We really wanted to make a point that mathematics impacts the world all around us and can make big structural changes, even policy changes. So we're seeing these kinds of techniques being used by all sorts of really important policymakers that are going to make changes in lots of people's lives. For example, this kind of textual analysis is being used by NOAA, the National Oceanic and Atmospheric Administration, to look at their own internal policy documents and think about ways that they can change that moving forward. I'd love to zoom out from that to something that you mentioned a little bit earlier. and that's that a lot of people, you know, at best or maybe ambivalent to math or think it doesn't really apply to their lives, or at worst, you know, actively dislike it or are afraid of it. Why do you think that is? I think, unfortunately, part of it is the way that we're taught math.

So unlike, you know, an English class where you can get an 87 on your essay or 100 on your essay and you feel like, oh, that's a little bit of the teacher's opinion on how I structured my sentences, math class is often taught like, you're right or your right. wrong. There is a correct answer and you got it or you didn't. And I think people get intimidated the first time that they kind of have that gut feeling of failure and then they don't ever want to approach it again and they get skittish almost. And so I know that definitely happened to me and it took a long time of realizing that most of those math classes, the way they were taught is not actually how math is used in the real world. Math can sometimes be about ballparking and understanding this process and then going back and refining it. It's not. this binary, you're right or you're not.

It's really interesting. I haven't thought about that. People aren't so much encouraged to be curious and come up with questions and solve them that you're often just tested on memorizing and can you remember this equation without really diving into why is this equation going to be used in your life and why should you remember it? I had a few teachers that were like, we're going to show you how to derive the equation. And I thought, oh, this is going to be terrible and boring. and they would explain both the like social cultural history of like this is how we got here

because someone was trying to solve this particular issue with understanding, you know, how to run this dyke system or something. And I was like, oh, oh, there's like there's actually bickering going on by scientists that leads to deriving this equation that now we just all reference whenever we're doing work. Like there's so much interesting cultural history behind it and that it applies to so much of our lives now. I don't know. Now I'm a total math convert.

Now I get really excited about it. Yes. Totally, totally. And that gets at this bigger idea around curiosity and learning that we wanted to ask you about. Because it seems like a lot of people probably avoid math because they're afraid that, you know, they're going to not sound smart as they go about learning it. And it's hard a lot of the time. And yet when we let that get in our way, it's really hard to learn new things. So it seems like something that you do on the podcast and in your work is just foster this persistent curiosity. and I wanted to ask if you have any advice for how all of us can cultivate a little bit of that sadie energy. I have definitely stopped being scared of sounding dumb. I will say I think part of that does come from my scientific background. My experience getting a PhD, most of the time when people find out of a doctor, they think, oh, wow, you're really smart. And I'm like, no, I was really dumb for six years.

Like, I just asked really basic questions, and it turned out we didn't have an answer to some of them. And so then I did research to try to find an answer. And so I've just kind of taken that with me everywhere. Like I've just, I've accepted it's okay if people think I'm the dumb blonde because I'm going to figure out some stuff and I'm going to have cool stories to share and tell. And my co-host, Ian, is also great about that where he just, he just wants to know. He's just curious. And it makes it really fun. And I'm curious if you could say a little bit more on how that's changed, how you think about math or even how you feel about math kind of emotionally.

There's something to be said for letting your own curiosity guide you to where you end up reading more or learning more. Creating this podcast, it's been really fun to be like, oh, I don't totally understand that. Wait, I'm very good at Google and I can figure out how to know this answer. And so it becomes kind of a fun treasure hunt rather than a test. Speaking of treasure hunts, can you give us a little tease for what else is coming up in your inaugural season? Yeah, so we have an episode about 5G. We get a little bit into 5G conspiracy theories. And I'm really excited for our final episode. I'm interviewing a researcher at Duolingo and we're talking about how the brain is a statistical learning machine and how it's in the background, it's computing all these probabilities, even though it's not something that we're actually doing consciously. It's really all about the biology and learning sciences, but secretly, when we're, Once again, it's all math.

Sadie, thank you so much for helping us see math in a new light and approach it with just a heaping dose of curiosity. It's been a joy. Absolutely. It's truly been a joy. This episode was produced by Burley McCoy, edited by Rebecca Ramirez, and fact-checked by Rachel Carlson. The audio engineer was Josh Newell.

Giselle Grayson is our senior supervising editor. Beth Donovan is our senior director, and Anya Grunman is our senior vice president. of programming. I'm Aaron Scott. Thanks as always for listening to Shortwave from NPR.