Join us for a special bonus episode of So Curious! as we explore the intersection of science, technology, and health in celebration of The Franklin Institute’s new Body Odyssey exhibit.

Host The Bul Bey dives into thought-provoking conversations with three incredible guests. Dr. Harvey Rubin sheds light on how artificial intelligence is transforming medicine, from diagnosing rare diseases to designing digital twins of cities. Dr. Tonia Hsieh takes us into the fascinating world of biomechanics, explaining how the movements of lizards and other animals inspire breakthroughs in robotics and prosthetics. And Dr. Jayatri Das, chief bioscientist at The Franklin Institute, connects the dots, offering insights into how emerging technologies like AI are shaping the future of health and healthcare.

Packed with curiosity, big questions, and inspiring ideas, this episode is your invitation to think differently about the world around—and within—you.

Learn more about the Body Odyssey exhibit and get tickets at FI.edu.

The Bul Bey: Welcome back to the So Curious! Podcast. My name is The Bul Bey. You can just call me Bey. And this is a special edition of the So Curious! Podcast, where we're going to have important conversations with people in the field of medicine and science, as we connect it to the new Body Odyssey exhibit opening at The Franklin Institute.

And trust me when I say that this will be an epic throwback to some of the funniest and insightful conversations that we've had throughout season one and throughout all the rest of the seasons. Today, we'll be talking to Dr. Harvey Rubin about how artificial intelligence is changing medicine.

And Dr. Tonia Hsieh, who studies animal locomotion, with fascinating insights into how we humans move and adapt. And we'll be closing out the episode with an amazing conversation with Dr. Jayatri Das. So come with me, come along as we have these incredible conversations. Our next guest is Dr. Harvey Rubin, who's a professor at University of Pennsylvania.

So introduce yourself. What is it that you do? Who are you? What's your favorite color? All that stuff.

And then in '83, came back here to Penn as an assistant professor in the department of medicine and specializing in infectious diseases. And because my background was in physics and mathematics and computation, I was able to talk them into giving me a secondary appointment in computer science.

And so since '83, I've been here, worked my way up through the academic ranks, and now I'm professor of medicine with a secondary appointment in engineering and computer science. And I work on, clinically, only with patients who have infectious diseases. In my lab, we do basic biochemistry, and we've migrated into doing modeling of complex issues in the biological sciences and that's what led me to what we'll talk about today. This notion of can you model, can you actually computationalize, if I can coin a phrase, issues in medicine.

The Bul Bey: Let me ask you about like, what's driving you and what's inspiring you to find this work and to dive into it.

Dr. Harvey Rubin: So when I started my career, it was all about data and computation.

The Bul Bey: And what's computation?

Dr. Harvey Rubin: So when we think about computation, it's like, can you figure out a way to put a mathematical model or a model that represents a real life situation that you can work with to analyze that real life situation, without complicating it and making it very difficult by doing in the real life.

So if I wanted to model a disease, I may not have a lot of patients that have that disease. And I would say, well, what are the characteristics of that disease? What are the character, you know, fever, chills, cough, sputum, that's a characteristic of pneumonia. So we can actually bring an abstract notion of a lot of biomedical and sort of medical issues, if we learn how to, what we call, abstract the fundamental issues, pull out the fundamental issues, and, just to jump ahead a little bit, if we try and do a model of a cat. What are the fundamental issues of a cat? Well, it's sort of this big and this tall, has four legs, it has whiskers. And you see, those are the fundamental properties of a cat.

Are they different from the fundamental properties of a dog? And if I can pull out those different fundamental properties, I may be able to write a mathematical or a computational program that would look at a zillion cats, and I present you with something and say, is this a dog or a cat? And since we've been able to pull that out, all those characteristics, I can now make a mathematical or a computational model of what a cat might look like.

It models as best that it can to the real life world. And so you start off asking the motivational issues. So as a, when I was a grad student in physics and math, it was all about data and computation. And what is the structure of a molecule look like? Or what is the structure of deep space look like?

And then for some reason, and I think this happens to a lot of people, um, migrated from, what motivates you is trying to understand the real world is to try and understand an individual in the real world. And that's what led me to be really concerned about human health. Then, fortunately, I've been able in my own research to combine this notion of computation and the individual in its own space, its own health and wellbeing space. And so the motivation became more, can I get you better? And now I've gone back to that computational approach. So it's, it's kind of a full circle.

The Bul Bey: All right. Well, we live in a world today where we have all these tech giants and they are stepping into the space of AI.

What is AI?

Dr. Harvey Rubin: Right. So AI is, the big umbrella of can you use computation and computer science to look at issues that you have to make a decision upon. So should I buy a timeshare? Well, how do you figure that out? Well, you get all the data you can about timeshares and say, does it make sense to me? So you surf the web, you ask a large language model, which is a kind of AI, and AI helps you answer that. So a large language model is part of AI that looks at all the data, all the documents out there ever published that's available, and it can actually look at not only the next word, but the next sentence, the next paragraph.

We'll get back to generative AI, which is really where a lot of the excitement is. So we have AI, then we have machine learning. And we have machine learning, which says, can I get a machine, a computer, to learn from certain statistical data that whenever I have the word 'but' the next word will be something else.

And you can use machine learning to analyze. Natural languages, for example, because there's a lot of data out there. And then underneath machine learning, you have what's called deep learning. And deep learning is something where the actual model of the human brain, and the brain makes certain associations, and the computer learns how to make those associations as well.

So deep learning uses the neural networks that people talk about. So we have AI as the big umbrella, then we have machine learning, which is more based on, on rules and statistics. And then we have deep learning, which is based on the ability for the computer to sort of learn from itself and other data.

And then well below that, we have something called generative AI. And generative AI is saying, okay, I know this, can I make something new out of it? So I know what a poem looks like, but can I use the computer to make a new poem?

The Bul Bey: And how does any of this become applicable to, I guess, treating illnesses, limitations in our health?

Dr. Harvey Rubin: Great question.

So, if I have one patient that has a really rare disease, in other words, I have no data, I'm kind of stuck. Right. I gotta, I gotta sort of really figure out what this is. But, if, you know, I'm 76 and I've seen 50,000 cases of whatever pneumonia, I kind of have a great database of what pneumonia looks like. So in our experience, we build up this database. But because now we have large computers that can store tons and tons of data, you can characterize all these medical issues, for the most part, and say, does this patient fit in with this characteristic? And you can use that as saying, is this pneumonia or is this cancer? So we have the same idea in medicine of collecting enormous, enormous amounts of data. And then we use that for different purposes.

We can use it for surveillance, for example. So, you know, all of a sudden we're seeing a blip in a certain pattern of disease, cough, sputum, early death. What's going on here? Well, maybe it's something like a new pandemic popping up. So we can use it for surveillance because it's an outlier. And the beautiful thing about having a large database is that you can now pick something out that doesn't really fit into that database.

It's something new. Is that a new disease? And guess what? It can be.

The Bul Bey: And what are the different types of data?

Dr. Harvey Rubin: So what is data? Great question. So that's really the beginning of our new adventure. So we have data science. What is data? Data could be a string of words. Data could be, for example, hey doc, I feel really badly today.

I have this rash over the right side of my chest and it's really painful. So the data is that string of words. And I'll be able to say, well, maybe you have shingles. Then he could say, or the patient could say, and here's a picture of it. And the data now is an actual photograph of what that rash looks like.

So that data is visual data, but it's important data. I can look at that, I will look at it and say, that's consistent with shingles. I can also put that into a program, just upload it onto, onto my medical record, have AI say, is that shingles or is that ringworm? And guess what? That study has been done and the algorithms are pretty darn good to say, that's not ringworm, that's not a staph infection. That's shingles. So that's another piece of data. Another data is a series of numbers. Your hemoglobin, or your temperature. And you can look at the data over time. You call that time series data, and we can interpret that. But guess what?

Machines are a lot better at looking over vast arrays. So I have my cholesterol over the past 10 years, and I started taking a statin halfway through. How does that data change? Beautiful example of what AI can do is analyze that data and analyze it for a million other people, my age, my gender, my daily living.

The Bul Bey: And in some hypothetical future, could doctors be AI? Like, could there be an AI doctor?

Dr. Harvey Rubin: So that goes from data science to information science.

The Bul Bey: Okay.

Dr. Harvey Rubin: And so the question you asked is exactly the right question. Because now it's ramping up what we think we can do using so-called AI and all the things under it, all the way down to deep learning, and generative AI.

So, in some sense, yeah, we can start thinking about what new information do I need to help make a diagnosis or help understand surveillance or help design a new drug. And so that's information science.

The Bul Bey: And is that limited too? Because, you know, there's a patient relationship context to medicine that's really, really important.

Some people have the same doctors for many, many, many years. And you know, but maybe there's a future where, I don't know, you'll just stick your finger in a port and it'll give you your medical history and maybe some suggestions.

Dr. Harvey Rubin: So we didn't talk about this before, but you are leading me exactly along the trajectory of where we're going, where I think the future of AI and medicine will be.

So we started from data. We went to information. Now you're asking me about wisdom. Now you're asking me about medical decision making. You're asking me about, can there be what we call decision support? And that is really where people are worried about. Can we do this without getting hallucinatory answers using the computer?

You've read about AI and it, you, you give it a question and it starts hallucinating relationships that aren't there because it's not perfect.

The Bul Bey: Right.

Dr. Harvey Rubin: And so, the concern, but the excitement is converting data science, to information science, to wisdom science. And we think about how can you computationalize wisdom, right?

It's contextual. Where did you grow up? What's your cultural background? Uh, it, it has to do with uncertainty. It has to do with the ability to assimilate all kinds of noise and irrelevant data that may not be part of making a wise decision. So we think, my colleagues at Penn and a couple of really smart grad students, are saying we can computationalize that.

The Bul Bey: What does it mean to treat and what does it mean to cure?

Dr. Harvey Rubin: So, to treat means you have to have something that you're treating. And so, you have to determine what is the problem, what is the disease that we're trying to treat? And, you know, if I look at a chest x-ray and I say, gee, that looks like pneumonia, but somebody else says, no, I'm not so sure, maybe that's a cancer, maybe that's a lung tumor.

Can I make that decision on my own? I go to the expert, the radiologist. Radiologist looks at it and says, you know, in my experience, you have to treat pneumonia. Maybe another radiologist will say, in my experience, that looks more like something else. But those experiences are based on maybe 20 years of looking at x-rays.

What if we had the ability to look at 20 million x-rays and have a computer say these are the characteristics of bacterial pneumonia and these are the characteristics of invasive cancer. You can use that and people have done that looking, using AI to analyze x-rays and mammograms and you know what, guess what, it does as well as if not better than professional radiologists. And that study has been done and it's ongoing and the algorithms are getting better and better. So, yeah, I mean, I think we figure out what to treat by looking at all the data. And then we say, how do I know I'm cured? And that's another great question. Sometimes we know because the characteristics change.

You don't have a fever, you're not coughing, the x-ray clears up, you're cured. But. Is that a long-term thing or is that just a short term thing? If it comes back,

The Bul Bey: which always confuses me about the word cure because cure in my mind means like it's done, it's over, it's gone.

Dr. Harvey Rubin: And we do, we cure a lot of diseases.

We do cure a lot of the people say, ah, I have this disease. I'm never going to be cured. We do cure diseases. Some diseases we haven't yet figured that out. But, I tell the students this, in 50 years, so I started maybe 50 years ago, in another 50 years, there will be diseases that we used to try and cure that don't exist anymore.

The Bul Bey: And where does your curiosity lie? Where's the gray space? Where's the, “I'm not sure about that.”

Dr. Harvey Rubin: Well, for me, I think it's really, can we develop a decision support algorithm that does what we were talking about before. Instead of calling my old friend down the block who's seen a billion of these cases, can I go to a computer and say, what is the wise way to do this?

Because my friend may say, she may say, you know, I've taken care of 30 patients like this. And even though it says this in the guidelines, it really doesn't work for that individual patient. So this notion of personalized medicine is where this is going to really fit in. Because where does the individual person fit into the vast array of people who have similar, but not exact diseases.

And that's where clinical trials are going to be impacted as well. And we're going to get DNA sequences. We're going to get lived experiences. We're going to get social constructs. We got to fit that into a wise decision.

The Bul Bey: So how do we use the artificial wisdom that you mentioned, how does that play into planning for the future?

Dr. Harvey Rubin: You know, I love this conversation because the dots are connected. You know, clearly we have an issue of, of extreme climate events. It's been the hottest it's been in, in decades and people are dying. More people die of heat related illness than any other natural disaster. And most people now are living in urban centers. The world has become urbanized.

And so in terms of human health, we have to figure out how can cities and urban development help mitigate and prevent heat-related illnesses or, in fact, any climate catastrophe. And so what we're doing now is building what we call a digital twin. And you can build a digital twin of a city, just like we can almost build a digital twin of the human body.

Well, that's much harder than building a digital twin. Building a digital twin means where are all the buildings? What streets are they on? There's construction on 21st Street and I'm 20 minutes late. How do we understand the impact of urbanization on human health?

So you got to figure out, and there are ways to do that by actually modeling the city, where are the streets? Where are the transportation hubs? Where are the big buildings? Where are the heat islands? And then put that all into a computer model. And then add what we call nature-based solutions. So we can build buildings, but we know that if you put a, plant a bunch of trees, it lowers the local temperature. How do you plan where those trees go?

You've got to figure out what the problem is, you've got to treat it, and then you've got to know will it cure this issue? Can't do that in 20-year timeframes of cities. So let's model it and simulate it. And that's exactly what we're doing in, around the world, with my colleagues and building a digital twin of a city, and then you can start modeling interactions. Between the people and the city and the built infrastructure and the nature, nature-based structure. And you can say, what if I build, you know, a cooling shelter here? Is that the right place? Do I get enough traffic through it? And you could say the same thing. What if I get myself a statin and I change my cholesterol?

So it's these questions of modeling interventions and then simulating the effect and finding out predictive, that's the key word here in all this AI stuff is, what can we predict from the model? And how do we know that our prediction is right?

The Bul Bey: Thank you Harvey. That was an incredible conversation and stay tuned. We have more to come. Our next guest is Tonia Hsieh who's an associate professor and runs the Hsieh lab that's over at Temple University. We're excited to have her. Tonia, how are you?

Dr. Tonia Hsieh: I'm doing well, thanks for having me.

The Bul Bey: All right. So we're going to cover a lot of different things, uh, the work, the research, science in general, right.

And how it relates to human beings, our behaviors and how we adjust to our environments. But before all that stuff, please tell the audience that's listening, what it is that you do and what's inspired your work.

Dr. Tonia Hsieh: I am a faculty member over at Temple University where I study biomechanics. I'm really interested in animal locomotion.

I'm really interested actually in basically why it is that we can run around and not trip and fall and hurt ourselves all the time.

Dr. Tonia Hsieh: Oh, my God.

The Bul Bey: Have you heard it?

Dr. Tonia Hsieh: Yes.

The Bul Bey: Do you like it? Is it a classic?

Dr. Tonia Hsieh: Uh, yeah. It's the one that we should all have all the time playing constantly.

The Bul Bey: Do you know how to do it?

Dr. Tonia Hsieh: No.

The Bul Bey: Me either. We'll move on. But tell us about what you're currently working on and, I guess how you got to that point.

Dr. Tonia Hsieh: Well, so what we're working on now is basically looking to see how foot shape, because it turns out that—some animals are actually really good at running on sand. I don't know if you've ever tried running on a beach.

The Bul Bey: I have, I have.

Dr. Tonia Hsieh: It's pretty awful.

The Bul Bey: Yeah, it's not the, the best place to, to, I mean, a lot of people do train on, on sand, but I digress.

Dr. Tonia Hsieh: Yeah, those are the people who really like pain. Um, but if I have to run on a beach, I'll be running, you know, next to the water where it's nice and packed, but the, the really soft, loose, sandy stuff is really hard to run on. And for us, you know, it really, it makes it really hard for us to run. Whereas a lot of other animals, they can run just as fast on the really soft, dry sand as they can on hard ground. And the thing about movement is it's, it's really, it's a combination of a bunch of various different systems in the body, right?

So it's not just, it's not just unfortunately left, right, left, right, left, right, right. So we've got all this sort of feedback we're getting from the environment. We've got, you know, how we sense the world, how our body is sensing our position in the world. Um, and then you've got the gazillion muscles that you also have to activate. Everything from including your core, even when you're walking, you know, your entire body is playing a role in that. And then sort of the entire physics of it, you know, how when you're swinging various different parts of your body, how it changes your balance and how you go about responding to that and correcting for it so you can get smooth motion. And that's only on hard flat ground. So the minute you go and you do something crazy, like have somebody walk across carpet, God forbid, or, you know, a piece of slippery tile or go out and, I don't know, run a trail or say, walk on a tight wire, um, suddenly now you're really beginning to ask for a lot.

And now you've got to really pull in all these other systems to really kind of tune the system and make you be able to do what you want to do.

The Bul Bey: Okay. So there's multiple systems.

Dr. Tonia Hsieh: Yes.

The Bul Bey: Working in unison so we can just walk on flat, sturdy surface in a straight line.

Dr. Tonia Hsieh: Oh yeah.

The Bul Bey: Can you talk about animals and how they move?

Do they have the same kind of systems or, and are we learning from those systems? I'm getting ahead of myself, but tell me about how animals move.

Dr. Tonia Hsieh: Yeah, they've got very similar systems. I think the basic game plan is the same. Right, in the sense of you've still got the sensory feedback, you've got, you know, different systems reacting to different things, you've got the muscles that need to be activated to move things across joints and things like that.

All of that, I think, is still the same. What you do get with animals that's really cool is you get a lot of other body plans, so body shapes, right? So you have, um, if we just talk about, you know, limbs and not even actually get into the shapes of the bodies themselves, you've got the ones without legs, you've got the ones with two legs like we do, you've got the ones with four legs, six legs, eight legs, you've got, you know, the centipedes, the millipedes.

Um, you've got the ones with wings who don't really like to use their legs at all, right. And then you've got everything underwater, everything up in the air. You've got, I mean, it's, they're, they're all over the place, right? So they have way greater diversity in the things that they do.

The Bul Bey: That's amazing. And, you know, we were talking before we started recording, you and I both recently in our lives came into being a pet parent to bearded dragons.

Dr. Tonia Hsieh: Yes.

The Bul Bey: Bearded dragons exist in the desert, on sand, but they also like to climb and they interact with different surfaces. How does that shape the behaviors?

Dr. Tonia Hsieh: I think one of the really cool things to think about is not even so much the changes as what stays static, right? So, what stays the same is we are using the same limbs, the same feet, the same hands, you know, all these same structures, like an individual is, for moving across all these different types of environments.

So if we go back to your bearded dragon, for example, right, your bearded dragon can in a day, you know, scurry around across a bunch of sand. And it can move pretty quickly. It can climb up, you know, scurry up over a bunch of rocks. It can move across that very quickly. It can climb very well, and it can hang off these branches. Right? I mean, really, bearded dragons don’t really move that much. They kind of like to sit around, but, you know, when they’re little they’ll jump around. And they’re using, when they jump, and that's a very different locomotor mode than running across sand or hanging off a branch, whatever else, even then they're still using the same body structures, right? So there's this sort of adaptability, this generalization of our bodies, where we have specialized for certain things that we really need to be very, very good at to survive, but we also generalize to be able to move across all these other types of situations and survive across all these different situations.

The Bul Bey: How many foot shapes are there? Is that just like an unreasonable question to ask? Because I'm thinking about, you know, paws, I guess.

Dr. Tonia Hsieh: Right. Yeah, we got paws and there's lots of different types of paws, um, furry or less furry, webbed, unwebbed. We've got all of our foot shapes, right? And then you've got like birds where, man, you got perching birds who like, I mean, have you ever thought about why it is a bird doesn't fall off a branch when it falls asleep?

I mean, I would fall off a branch. I fall off, I fall off branches when I'm awake.

The Bul Bey: And that's because of their foot shape? Are we talking about like, uh, parakeets or something like that?

Dr. Tonia Hsieh: Well, so, so yeah, so perching birds, I'm not sure so much so sure about parakeets, but you know, if we talk about songbirds and things, they actually have, their, their feet, the anatomy is such that, that they don't need to use muscles to have their feet closed. So that means that—

The Bul Bey: I don't know why, but that just blew my mind,

Dr. Tonia Hsieh: right?

The Bul Bey: Wait, what?

Dr. Tonia Hsieh: Well, I mean, that's the thing about sort of the animal kingdom, right? Like there, there's so many amazing solutions that animals have evolved for their different needs. I mean, stomatopods are one of my favorites, right?

The mantis shrimp. That they can hit a shell hard enough that they actually cavitate the water. So, um—

The Bul Bey: What?

Dr. Tonia Hsieh: Right, it's crazy. One of, one of my friends over at Duke filmed this video years ago, this woman, Sheila Paddock, she's a genius, um, where basically she showed with extraordinarily high speed video, I can't remember how many tens of thousands of frames per second speed it was that she was taking, of this stomatopod hitting a force transducer that had a bit of shrimp paste on it because they like to eat shrimp.

It was hitting it with its bludgeoning claw and as it peeled away what you saw was this big flash of light and the flash of light is from the collapse of the bubble and energy release as it collapses. You get this big old flash of light and that is actually how they break these, these shells is not by actually the impact, but the force and the energy release of the cavitation following that point is what actually cracks the shells.

The Bul Bey: That is amazing.

Tonia Hsieh: Right?

The Bul Bey: Well, so let me ask you. How do you engage with animals that have particular functionalities and human beings that we don't. And how do you get anything from that? How does that inform? Like, how is that of any value, knowing that they have completely different mechanisms?

Dr. Tonia Hsieh: Right. Yeah. So, so that, I mean, that's a great question, right?

It's, and it's a question I get a lot of the times, which is like, okay, so you study feet on sand. How does that really, you know, lizard feet on sand.

The Bul Bey: Yeah, I can't hang in a tree. I don't, like, what?

Dr. Tonia Hsieh: Right? Exactly. But, you know, along these lines, so let's just take sort of what I'm doing, for example, you know, the, the feet on sand.

So I'm looking at these big, long, crazy sort of lizard toes running on sand of these little tiny animals that are running across and we've got these big old humans, right? But what that can tell me is, for example, by looking at what they do, by watching the animal itself, by then building models and, you know, looking to see the forces I get out of these foot shape models of making these computational models where we actually simulate what the, what the particles are actually doing. I can say, okay, well, I see that when this part of the foot hits and it hits in this type of way, and it stretches in these ways, this is how the surface responds.

And because of this, I know, for example, that they can really plant their toes really deeply and interact with the sand as if it's a solid. Um, at these points, they're fluidizing it. And I can take this information and I can say, okay, so if I now extrapolate this out to, not the lizards but in general, they are able to run across sand because they can solidify at these points, they can fluidize at these points. The solidification helps with this, the fluidization helps with that. That then can allow me to think about, well, prosthetic development.

How can I develop a prosthetic, for example, for somebody, um, to be able to move across these types of shifting surfaces, how we can build in control mechanisms in the prosthetics that actually can make it easier for them to walk across these types of surfaces. You know, how can we look at therapeutic sort of regimens for people who are recovering from injuries in terms of helping them think about how to actually interact with shifting surfaces and unstable surfaces. Because sand is incredibly, incredibly challenging to move over. It's incredibly unstable, right? So if we can work with, with a surface such as that, and we can understand how animals are, you know, maintaining stability on those types of surfaces, we can then extrapolate back to humans and robotics and prosthetics and all these other sorts of things.

The Bul Bey: And that's really cool because that comes from watching a lizard skirt across sand.

Dr. Tonia Hsieh: Right?

The Bul Bey: Yeah, yeah.

Dr. Tonia Hsieh: Totally crazy. Or run across water or hang off a branch.

The Bul Bey: Right, right. Let me ask you, uh, what equipment are you excited about that you're working with now? And what pieces of equipment can we find in our houses that we can use to just do little small experiments.

Dr. Tonia Hsieh: Oh my gosh. There is so much cool equipment. You wouldn't even believe it. Especially with all the technology now. I mean, it used to be, that it would be like, well, my high speed camera is really cool.

The Bul Bey: Yeah.

Dr. Tonia Hsieh: And my high speed camera is still really cool.

The Bul Bey: High speed cameras are the best.

Dr. Tonia Hsieh: They really are, especially when they can film at 32,000 frames per second.

The Bul Bey: That's amazing.

Dr. Tonia Hsieh: It's incredible. I used it once on a spider, at 16,000 frames per second, that basically throws spit wads.

The Bul Bey: That sounds scary, but keep going.

Dr. Tonia Hsieh: It was awesome.

The Bul Bey: Keep going.

Dr. Tonia Hsieh: We were out in the Florida swamp filming at mosquito hour. Mosquitoes love me. So I was donating blood to the Florida swamps in exchange for footage of trying to get this spider to fling a spit wad at a moth that was supposed to be flying in. And we sat out there for hours.

The Bul Bey: And you got it.

Dr. Tonia Hsieh: Never did. So we ended up taking,

The Bul Bey: No!

Dr. Tonia Hsieh: Yeah, I donated a lot of blood.

The Bul Bey: Oh wow.

Dr. Tonia Hsieh: So we ended up taking these spiders back into a greenhouse where we then took moths, unfairly glued to, um, the ends of fishing lines, and would get them to fling their spit wads at the moths that way. And then we discover that apparently they respond to jake brakes.

The Bul Bey: Excuse me?

Dr. Tonia Hsieh: So, yeah. So, we would play the sound of a jake brake on our phone and it would cause them to fling their spit wad.

The Bul Bey: And really quickly, what is a jake brake?

Dr. Tonia Hsieh: A jake brake is the brakes that are being used on the big sort of trucks, the big, what are they called? The semis? Is that what they're called? The multiple wheels?

The Bul Bey: And they will respond to it?

Dr. Tonia Hsieh: They will respond to that. The "kutchshh" sound.

The Bul Bey: Is there any equipment that I can look out for, like, at home where I can do, like, some experiments? It sounds like maybe a fishing rod.

Dr. Tonia Hsieh: Fishing, actually fishing rods. I use those for catching lizards. So you joke, but yes, we fishing rods are the best for those.

Um, your phones right now, you can use them for, they're not high speed, high speed, but they, they do film at higher rates now, which is nice. And so that's fun. They usually call it the slow motion sort of setting. There's also these like—and I haven't used them yet, but I did buy one for my kids. So don't let them listen to this before Christmas, um, or cut this out—um, where you can 3D print draw things, right?

Like you can draw in 3D and it will extrude the, uh, filament, right? So we use 3D printers as well. I mean, they're, they're not ones that you hand draw. They're much higher quality than that. And they can print a lot of different materials, but you can build things. You can build models with those, right, that you can test.

3D scanners? Oh, we've gotten way into using sort of 3D scanners, like handheld scanners. It turns out that there are apps that you can install on your phone, which this last summer I was doing some studies looking at isopods digging. It was just like a little sort of side project to see cause I thought it'd be kind of fun.

And cause also, cause roly polies are really cute. We all love roly polies. I wanted to play with them, but it turns out that you can either go and take like this 3,000 dollar 3D handheld scanner and try to scan a pile of dirt and get basically, a pile of dirt, or you can go and take your camera on your phone and do the whole same thing, and you can get almost the same good results.

So, I actually ended up scanning one of our isopods with it and I got a nice little 3D model, um, that I'm going to try to see at some point if I can actually clean it up enough to be able to print it out on our printer. And then I get like a little 3D model of my little isopod.

The Bul Bey: And you saved yourself 3,000 dollars, look at that.

Dr. Tonia Hsieh: Exactly.

The Bul Bey: And, uh, now that we're talking about like, you know, uh, equipment and, and technology, where does AI come into play with any of this?

Dr. Tonia Hsieh: Whew. Everywhere, eventually. But you know, it's all really cool computational stuff that we can do now, which I think it's all along sort of this, this general trajectory. One of the biggest challenges we have is that, as we've been saying, right, motion is incredibly complicated and pose estimation. It's really going and looking and quantifying what an animal itself is actually doing in 3D.

Right? But with AI. You know, we can potentially feed this stuff in, and there have been groups that have already started developing algorithms for them, and they work to various different degrees. Because with AI being artificial intelligence, you have to train it, and you have to train it with the right data.

And we have tried implementing some of these algorithms in the lab, and it has been incredibly hard. So we're not quite there yet, but I think we're getting close, and that's super exciting, because the thousands of hours that we spend doing this type of thing. And the numbers of pairs of glasses that we go through with increasing thicknesses of lenses.

The Bul Bey: Oof.

Dr. Tonia Hsieh: Right? It's, it's time to get AI to step in.

The Bul Bey: Sounds like a day off for you.

Dr. Tonia Hsieh: Like, oh, I could take a day off. Right?

The Bul Bey: Awesome. Awesome. Let me ask you, we can go back to, I guess, human movements. Where do you think the human body is like most limited in, in, in how it moves and interacts with the environment? Like, where can we improve?

Should I just, like, do some push ups and get stronger so I can move better through the space? Or, like, is there any space where you think the human body can, like, kind of improve?

Dr. Tonia Hsieh: For what we need to do to be good enough humans, I think we do pretty well.

The Bul Bey: We do pretty well?

Dr. Tonia Hsieh: We do pretty well, I think.

The Bul Bey: All right.

Dr. Tonia Hsieh: I mean.

The Bul Bey: I know our thumbs are important and things like that.

Dr. Tonia Hsieh: Oh, our thumbs are critical.

The Bul Bey: You know, but, I don't know. Maybe we can use a sixth finger or something.

Dr. Tonia Hsieh: I could use a couple more legs.

The Bul Bey: Yeah.

Dr. Tonia Hsieh: A couple more arms.

The Bul Bey: Yeah.

Dr. Tonia Hsieh: Yeah. I mean, I would say that really the, one of the most amazing things about bodies in general, whether it's human or animal, is its adaptability.

You know, we, we—spoken generally, you know, writ large as humans, and I'm speaking on behalf of all the animals out there—is that, we sort of make the best of what we've got. And the things that we can do when we make the best of what we've got is pretty spectacular. So, yeah, I mean, I, and I think that's really what largely drives sort of my research is this amazement with the ability of animals to be able to adapt to so many different conditions, you know, whether it's physical conditions, whether it's environmental conditions and whether it's, you know, movement through air, water, on land, you know, up in trees, there, there's just such a huge diversity of options out there and animals do it.

And they don't just kind of do it. They like really do it and they do it really, really well. Um, and so, yeah, so I think that's really the big takeaway of all of this.

The Bul Bey: Copy that.

Thank you so much, Dr. Tonia Hsieh. That was a fascinating conversation and stay tuned. We have more to come.

And we are back at The Franklin Institute, and I'm joined by the chief bioscientist, Dr. Jayatri Das. How are you?

Dr. Jayatri Das: Good. It's great to be back with you, Bey.

The Bul Bey: All right, cool. And we, we're not new to this, right? So, you know, we've done four seasons of the So Curious! podcast, and each one of those seasons, you've been so kind enough to come on with your time and share your knowledge.

And it was the segment called Body of Knowledge. And so this is kind of like an interesting little extension of that time that we spent together on those, uh, those seasons.

Dr. Jayatri Das: Absolutely. And, you know, I'm thinking about the two guests that we've heard on our episode today. And it's really fascinating to me how they talked about such different angles about how we understand our body and our health.

And yet there are some themes between them that I think really help us imagine what the future of health and healthcare might look like.

The Bul Bey: Yeah, yeah. And so we, we spoke with Tonia Hsieh and we spoke with Harvey Rubin. And they have a lot of experiences that they brought into the conversation, but let's talk about your experience for a second, like, you know, just to refresh the audience on like what it is you do and what it is you've studied.

Dr. Jayatri Das: Yeah. So I work on developing science content around all kinds of topics here at The Franklin Institute, for exhibits, for programs, for digital content like this. And so I like to think I'm just a perpetually curious learner, but I think what really fascinates me is trying to find connections between all of these different fields of science and how that inspires us to continually be curious.

The Bul Bey: All right. So how do they all connect? Right? So Tonia Hsieh, we spoke with her about movement, essentially how the body moves, how the natural world moves and how we can learn about those things. Are there any particular insights that you gained from that?

Dr. Jayatri Das: What really fascinated me about your conversation with Tonia was thinking about the interaction between the biological system of the body and the environment around us and all of the variables that you have to factor into to think about how you can model and predict how those interactions happen.

So it's not just—

The Bul Bey: Yeah, we talked about sand and that was interesting.

Dr. Jayatri Das: Yeah. So it's not just about what's happening in the body, but that interface with the environment around us and that those physical forces and, you know, how that changes over time and, and scale, that's really interesting. And trying to think about how do you capture all of those different variables into these models to better understand how our bodies work.

The Bul Bey: And so how does that connect to the conversation that we had with Harvey Rubin?

Dr. Jayatri Das: In some ways, they're both really trying to capture the systems that we exist in as, you know, whether humans or animals, as biological organisms. We don't exist in a vacuum. So, you know, Tonia was really looking at the physical interactions, uh, of the environment, of how the muscles work, things like that.

And Harvey's work with, you know, looking at different types of data that are informing AI algorithms really goes even beyond that, into thinking about, you know, modeling social dynamics.

The Bul Bey: A city, apparently.

Dr. Jayatri Das: A city, right? That's, how cool is that?

The Bul Bey: Yeah, yeah.

Dr. Jayatri Das: So the built environment and how all of that interacts with our biological systems.

The Bul Bey: And one of the episodes in season one, right? We talked about designer babies, right? Like how does that connect to your digital twin?

Dr. Jayatri Das: Yeah, you think about you know, these ideas of the future and how are they all gonna come manifest? With talking about gene editing and designer babies, in some ways that's taking a very isolated type of data, looking at genetic data in particular, and how we can manipulate that genetic data to, you know, in an ideal world, really focus on improving health and curing disease, um, with, you know, ethically questionable implications.

The Bul Bey: Absolutely. And you know for the listeners, in season one we talked about designer babies. I think in summary, you can help me out if I'm wrong, but it's like, if you wanted your child to have like, you know, specific traits, like they're good at tennis or they're good at riding bikes, and you know, get into the DNA of, of our genes and, and really start to shape that.

And you talked about the ethics around that.

Dr. Jayatri Das: Right. So when you look at gene editing right now, we're at a place where we can change the, the gene sequence of particular disease-causing genes to cure things, hopefully, we're still in the early days of it, um, but to cure things like, uh, potentially cystic fibrosis or sickle cell disease.

Um, but the potential for that technology could be to eventually use it for, you know, more biohacking purposes or gene enhancement purposes where we're increasing strength. And that kind of ties into elements of what both Tonia and Harvey talked about.

So understanding the genetic component as one piece of the puzzle of how we move and how we work, um, but also thinking about one piece of a much larger puzzle is how does genetic data interface with, you know, how our bodies function on a daily basis and the choices we make. And so when we think about a digital twin, the genetic piece is just one element of that digital twin that's going to take a lot more work to figure out how all of those types of data work together.

Again, I think as we develop new technologies, one of the questions that everyone should keep in mind is, to what purpose do we use them? And for a digital twin, I think Harvey raised some of these questions that, you know, about trust and responsibility, and that's going to be tied to the vision that we develop as a society about the purposes of, of creating this technology, similar to what we're doing with gene editing.

The Bul Bey: Yeah, and are there any questions or a specific question that's kind of like driving you and your curiosity at the moment?

Dr. Jayatri Das: For me, it's the question of how do our bodies balance their own systems with what's happening in the world around us? So this is a theme that really drives our new exhibit at The Franklin Institute called Body Odyssey.

And thinking about how our own choices, how our genes, how our, you know, our family history, our culture, how all of those forces and, and technology, you know, so much emerging technology as well, um, how those are going to shift the balance, and how we think about our bodies in the environment that we're living in as we move into the future.

The Bul Bey: All right. And let's start like, you know, moving into the harder stuff, I guess the more, uh, controversial things like artificial intelligence. How does artificial intelligence begin to kind of like push us forward into better understanding our own bodies, our own systems? And is there any areas that worry you?

Dr. Jayatri Das: Sure. I mean, when I think about artificial intelligence, it actually, you know, I, I listened back to one of our earlier episodes about really big ideas. There's so much power in it. You know, we heard from both Harvey and Tonia about how they're using AI in their work, everything from, you know, just making some of the repetitive or, just, ginormous data set processing tasks, just to create a bigger database to find patterns in, and that scale of information can yield incredible insights. So there's plenty that we can learn about it and, and think about how that brings us new insights to solve problems that we couldn't do on our own.

And at the same time, there's that human element of it, too, that Harvey talked about. That, you know, we're not replacing doctors yet. I think, you know, you had that great conversation about empathy and how that's important in, in terms of, you know, taking care of ourselves and each other. And I think that's something that we'll have to, you know, put at the forefront as we continue to think about how AI continues to evolve in medicine and health.

The Bul Bey: Right. When artificial intelligence comes up in conversation, it's very basic. Are you scared or are you not scared? Tell me how you can help us, you know, regular folk move past that barrier of a fear and really start to dig into this with more curiosity and talk about how Franklin Institute kind of helps us all move into these conversations past the point of like, are you scared or are you not scared?

Dr. Jayatri Das: Yeah, I mean, there's no technology that is inherently good or bad. It's all about how humans decide to use it. Uh, and that's something that we really try to foster at the Franklin Institute is to think about the relationship between science and society and, you know, how we can have conversations that go beyond just the field of science and include everybody in thinking about what does the future hold and how can we ensure that it benefits, you know, all of us.

The Bul Bey: And how would you describe the relationship between science and society? How would you frame it?

Dr. Jayatri Das: I would say first and foremost that embracing science is part of our identity, that we're all natural scientists as kids, uh, and, and to really continue that curiosity as we look around. And I think that's why having folks like Tonia and Harvey who can help all of us understand, um, kind of peel back the layers of this technology in ways that help us understand what's going on so that we can ask the right questions and be involved in the conversation.

The Bul Bey: Now, the one thing about artificial intelligence is it's developing so quickly, how do we make sense of all this?

Dr. Jayatri Das: That's a real challenge. Uh, I mean, I think the pro and con of living in the world that we do is that while these kinds of technologies like AI are advancing so quickly, we also have a lot more tools to have conversations that, you know, that can try to give context to that.

The Bul Bey: Like a podcast.

Dr. Jayatri Das: For instance. But we also need to think about, you know, who has access to these resources and technologies and where are they being deployed. And certainly I think there's a greater awareness of those broader issues in the field of science and technology than we used to see.

The Bul Bey: So if we were to make a basics, 101, best practice, in terms of engaging with AI past the steps of, are you scared, is one, it's a tool. Embrace nuance, it's not just blanketed, and really step into the conversation. And I guess like, you know, if there's like a small practical thing that we can do again from a citizen science level, like, you know, what can we do to put our thumbprints on the development of AI and, and really start to find questions.

Dr. Jayatri Das: And that idea of finding questions, like, to me, that, that really comes out of Tonia's work, too, um, of just looking around and how do we better understand the world around us, uh, and ourselves as well, and then, you know, putting those questions in first, then we can apply AI as a tool to answer those questions and be thoughtful about how we move forward with that rather than, you know, letting the tool develop on its own.

What I hope that we take away from the conversations, like the ones we've had today is the opportunity that's presented to us in bringing together perspectives from so many more people, um, making sure that our predictions and our assumptions are, are really inclusive of many more people, um, in ways that will drive science and medicine forward in ways that are beneficial.

Along the way, of course, we're going to have to pause and reflect and maybe step backwards sometimes.

The Bul Bey: So you can learn more about the new Body Odyssey exhibit at Franklin Institute and buy tickets at www.FI.edu. Again, that's www.FI.edu. Thanks for joining us for this bonus episode of So Curious! produced by The Franklin Institute.

You can also check out all the episodes from season one to learn more about cool ideas and about the human body and how technologies are pushing our boundaries. You can find So Curious! wherever you listen to podcasts. This podcast is made in partnership with RADIOKISMET. It's produced by Christopher Plant, additional production and mixing by Justin Berger.

The Franklin Institute's chief bioscientist is Dr. Jayatri Das, and Erin Armstrong runs marketing, communication, and digital media. And I'm The Bul Bey. See you next time.