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Q4 - AI in Engineering, Science and Discovery: Mysteries at Every Scale with Daniel Whiteson, PhD · Paths of Curiosity in an AI World

• 0:51
  SPEAKER_01: He's a fellow of the American Physical Society and also an author and podcaster.
• 0:57
  SPEAKER_01: What's Cartoonist?
• 0:59
  SPEAKER_01: George Kim.
• 1:00
  SPEAKER_01: He wrote We Have No Idea.
• 1:02
  SPEAKER_01: Um is Cartoonus Andy Warner.
• 1:04
  SPEAKER_01: He wrote his newest book, Do Aliens Speak Physics?
• 1:08
  SPEAKER_01: Dr.
• 1:09
  SPEAKER_01: Whiteson, thank you so much for joining us today.
• 1:13
  SPEAKER_00: Thanks so much for the invitation.
• 1:14
  SPEAKER_00: Always happy to talk to people about the mysteries of the universe.
• 1:18
  SPEAKER_01: Your first book is called We Have No Idea.
• 1:22
  SPEAKER_01: What inspired that title?
• 1:25
  SPEAKER_00: That title was suggested to me by a friend who was reading early drafts.
• 1:29
  SPEAKER_00: The first title I think we had was something like What the Heck?
• 1:34
  SPEAKER_00: Or Mysteries of the Universe or something.
• 1:37
  SPEAKER_00: And in the book we kept talking about all the things we didn't understand about the universe.
• 1:42
  SPEAKER_00: The book is about the open mysteries.
• 1:44
  SPEAKER_00: And I often wrote in there, how does this work?
• 1:47
  SPEAKER_00: We have no idea.
• 1:48
  SPEAKER_00: What's this?
• 1:49
  SPEAKER_00: We don't know.
• 1:50
  SPEAKER_00: And so a friend of mine underlined that and said, This should be the title of your book.
• 1:54
  SPEAKER_00: And so that's how we ended up there.
• 1:56
  SPEAKER_00: But the the inspiration was to write a book about the open mysteries, because we have lots of books out there about everything physics has figured out, which is awesome, and I love it.
• 2:07
  SPEAKER_00: Physics is very cool.
• 2:08
  SPEAKER_00: But I think it gives people the impression that physics is mostly done, or that we have a big fraction of the universe figured out.
• 2:16
  SPEAKER_00: And you know, it's true that when you walk around in the world, most of the things that happen to you are not mysterious the way they used to be.
• 2:23
  SPEAKER_00: Like in our macroscopic world, you know, there used to be lightning and magnets and all sorts of weird phenomena you couldn't explain.
• 2:31
  SPEAKER_00: And now we've explained all of those.
• 2:33
  SPEAKER_00: So a lot of the mystery of the day-to-day life is gone, but that doesn't mean that there aren't mysteries still to be figured out.
• 2:39
  SPEAKER_00: And so the book is about all the big questions in physics because I sincerely believe that most of the answers to how the universe works are in our future, that the bigger fraction of human knowledge is yet to be discovered.
• 2:55
  SPEAKER_01: I can't wait to dive into that.
• 2:57
  SPEAKER_01: But first, how would you describe what you do today to your student self?
• 3:03
  SPEAKER_00: Hmm, wow.
• 3:05
  SPEAKER_00: If I could talk to myself from like 30 years ago, um, you know, I think I would it's interesting.
• 3:13
  SPEAKER_00: I actually am on the path that the Daniel 30 years ago wanted to be on.
• 3:18
  SPEAKER_00: Um, you know, I would say that I I'm mostly doing research.
• 3:22
  SPEAKER_00: Um, I've spent a lot of time also on teaching and writing, but that basically I spend my time following my curiosity, you know, what's interesting about the universe, what don't we know, and what can we figure out?
• 3:36
  SPEAKER_00: You know, science is so much more, the job of like actually being a scientist is so much more than just wondering about the universe, it's looking for opportunities to make progress, which means figuring out like what question can we answer in a reasonable amount of time with our resources.
• 3:53
  SPEAKER_00: Not just, you know, smoking banana peels and lying on the roof and and looking at the stars.
• 3:58
  SPEAKER_00: It's wondering like what's a practical way forward.
• 4:02
  SPEAKER_00: So a lot of my job is trying to identify new ideas that can tell us something interesting in a few years, you know, not uh 50-year projects or totally impractical stuff.
• 4:13
  SPEAKER_00: Uh I have some of those also, but you know, you gotta uh actually produce something.
• 4:18
  SPEAKER_00: So I think maybe that's the biggest surprise to uh the student version of me from 30 years ago.
• 4:23
  SPEAKER_01: And there is so much out there to be questioned.
• 4:26
  SPEAKER_01: Walk us through your path.
• 4:28
  SPEAKER_01: How did the physicist and a computer science degree lead you to searching for new particles?
• 4:35
  SPEAKER_00: Sure.
• 4:36
  SPEAKER_00: So I grew up in Los Alamos, and my parents worked for the lab, and so physics was sort of in the air.
• 4:42
  SPEAKER_00: And I took AP physics from a physicist, Antonio Redondo, who taught at the at the high school in the morning before he went to the lab for his full-time job as a physicist.
• 4:53
  SPEAKER_00: And he was great, he was so enthusiastic, and I could see that he was having fun teaching and also in his job.
• 4:59
  SPEAKER_00: And so, like many people, you know, my story starts with I had a great teacher in high school on this subject, and I did.
• 5:06
  SPEAKER_00: And then I was looking for a way to get involved in physics, and I tried plasma physics because I thought, hey, um, fusion is important, and that's gonna like solve the energy crisis, and seems really valuable, and it's around the corner, and this is the 90s, and I spent two summers working in plasma physics labs before I realized I don't like this at all.
• 5:31
  SPEAKER_00: Like, it's just not my thing, like it's all vacuum tubes or it's magneto hydrodynamics calculations, and like no shade on the people doing it, it's great for them, but you know, research is very personal.
• 5:44
  SPEAKER_00: Like, do you find this fun or not?
• 5:47
  SPEAKER_00: It's not a judgment of the subject, it's just a reflection of who you are, and some people like you know, chocolate, dark chocolate, some people like white chocolate, you know.
• 5:56
  SPEAKER_00: Um, and I just discovered I didn't like it very much, and um that was weird because I thought I was supposed to like it, and so then I tried a different kind of physics.
• 6:05
  SPEAKER_00: I tried condensed matter physics, spent a summer at Texas Tech shooting um lasers at different kinds of goo and you know seeing what it did.
• 6:14
  SPEAKER_00: But the problem was that the laser is like made of a hundred components, each of which work 99% of the time, which means the laser never works because there's always something broken.
• 6:25
  SPEAKER_00: So I spent the whole summer fixing the laser and I didn't really like it.
• 6:29
  SPEAKER_00: It wasn't fun for me, it was frustrating.
• 6:31
  SPEAKER_00: Kid next to me in the same lab, he loved it.
• 6:33
  SPEAKER_00: He was like, This is the best thing ever, debugging the laser, yay! Um, and so it's just you know, it's personal, so I just kept hunting, and then I took a class in particle physics, and I was like, wow, this is the stuff.
• 6:46
  SPEAKER_00: This is like zoomed down to the lowest layer of reality.
• 6:50
  SPEAKER_00: Uh the math of it was fascinating to me and really fun.
• 6:54
  SPEAKER_00: So I really liked it.
• 6:56
  SPEAKER_00: And then I did research in that area the next summer, and five minutes in I could tell this is my thing because the big picture questions were fascinating, the math was fun, and the day-to-day work was actually enjoyable.
• 7:08
  SPEAKER_00: It was like writing programs and analyzing data, and so that's how I got hooked on particle physics.
• 7:14
  SPEAKER_00: And I was always a computer science person, also.
• 7:16
  SPEAKER_00: Uh, writing programs was you know a fun thing to do.
• 7:19
  SPEAKER_00: So particle physics was a great combination because the questions were fascinating from a scientific point of view, and the day-to-day work was really fun and satisfying from like an algorithmic craft point of view.
• 7:32
  SPEAKER_00: Um, so it really was a good combination for me.
• 7:35
  SPEAKER_00: And then when I graduated, I I thought about like going to grad school in computer science or in physics or getting a job, and um I looked around pretty broadly, but I decided I wanted to be a tool user instead of a tool builder.
• 7:48
  SPEAKER_00: I wanted to use things to answer questions about the universe rather than build tools for other people to use.
• 7:53
  SPEAKER_00: So I ended up uh taking the physics route instead of computer science route.
• 7:58
  SPEAKER_00: And um in grad school it was still particle physics for me, and uh, I worked on an experiment at Fermi Lab smashing protons and antiprotons to make top corks and study those, and then I got that was in the um era of uh big collider physics, and so that was the biggest collider in the world, and so ever since then I've just followed the biggest collider in the world around the world.
• 8:21
  SPEAKER_00: Um, so my son was born in Chicago near the big collider, and then we moved to Geneva to be near the other collider, and my daughter was born there.
• 8:30
  SPEAKER_00: So I've had one kid born near each of the big colliders.
• 8:34
  SPEAKER_01: To help our audience better understand your work, can you describe dark matter for us?
• 8:41
  SPEAKER_00: Yeah, so most of the stuff around us is made of a particular kind of matter, atoms, you know, oxygen, carbon, etc.
• 8:50
  SPEAKER_00: And that's great, and we're studying it and we're trying to understand what it's made out of, etc.
• 8:54
  SPEAKER_00: But it turns out that most of the stuff in the universe is not dark matter.
• 8:58
  SPEAKER_00: Sorry, it's not atomic matter, it's made of something different.
• 9:01
  SPEAKER_00: And when we look out of the universe, we can't account for all the gravity that's out there.
• 9:06
  SPEAKER_00: Like we see galaxies spinning, and something has to be holding them together so they don't throw them their stars into intergalactic space, but there isn't enough mass in the stars and the gas and the dust to hold them together, not by a little bit, not by a lot.
• 9:22
  SPEAKER_00: So we thought maybe there's some other kind of invisible matter out there.
• 9:25
  SPEAKER_00: It's not made of atoms, that is that has mass and provides gravity and holding the universe together.
• 9:31
  SPEAKER_00: And that's a big idea, but then we saw it in other areas.
• 9:34
  SPEAKER_00: We saw it bending the path of light as it goes through space, we saw it um um changing how things slosh around in the early universe, we saw it affecting this the formation of structure, like why we have galaxies at all.
• 9:49
  SPEAKER_00: And now basically, everywhere we look, you can't avoid seeing the evidence of dark matter.
• 9:54
  SPEAKER_00: We see dark matter's gravity in like ten different independent ways that really tell us that dark matter is matter.
• 10:02
  SPEAKER_00: It's some kind of stuff out there.
• 10:04
  SPEAKER_00: It's not made of quarks and leptons and atoms like our stuff is, it's something else.
• 10:10
  SPEAKER_00: And it's most of the stuff in the universe.
• 10:11
  SPEAKER_00: It's like 80 something percent of the matter in the universe is dark matter.
• 10:16
  SPEAKER_01: So how do we know it exists if no one has ever seen it?
• 10:21
  SPEAKER_00: Yeah, it's a great question.
• 10:24
  SPEAKER_00: And you know, it depends on what you mean by C.
• 10:27
  SPEAKER_00: Like, you know, we know that it's there because we detect it gravitationally, and the same way that you could detect things that are visible, like, have you ever seen the wind?
• 10:37
  SPEAKER_00: No, but you know it's there.
• 10:38
  SPEAKER_00: You feel it, it presses on you, right?
• 10:41
  SPEAKER_00: So in the same way that we can't shine light on dark matter, it doesn't absorb light, doesn't reflect light, doesn't give off light, we can tell that it's there because it does interact with us gravitationally.
• 10:53
  SPEAKER_00: We hope it also interacts in other ways, you know, that there are some other forces that it uses to interact with us that we can use to identify its particle nature, but so far we've only been able to see it through gravity.
• 11:08
  SPEAKER_00: And so that feels confusing because on one hand you say, well, we know it's there, we've detected it, on the other hand, you say, well, we can't see it, um, and we have no forces to interact with it in a particle level.
• 11:19
  SPEAKER_00: How does that make sense?
• 11:20
  SPEAKER_00: Well, it makes sense because the only way we can interact with dark matter is via gravity, and gravity is very, very weak.
• 11:27
  SPEAKER_00: Like there's hardly any power in gravity.
• 11:30
  SPEAKER_00: In order to sense something's gravity, you have to have a lot of it.
• 11:34
  SPEAKER_00: Like, you can tell that the earth is there because of its gravity, but you can't tell that like a book on your t is on your table because of its gravity.
• 11:42
  SPEAKER_00: You can't detect the the gravity of a book, it's so small.
• 11:46
  SPEAKER_00: And in the same way, we can tell that huge blobs of dark matter are out there because of their gravity, but we can't tell that an individual dark matter particle, whatever dark matter is made out of, is there because of its gravity.
• 11:59
  SPEAKER_00: Gravity is just too weak to detect books or particles.
• 12:02
  SPEAKER_00: So we've seen dark matter from a gravitational point of view, which means we know that it's there, where it is, how much of it there is, but we haven't seen it interact in any other way, so we can't tell what it's made out of, um, and we can't s probe its like fine structure.
• 12:22
  SPEAKER_01: How does it feel to search for a particle for years and find nothing?
• 12:31
  SPEAKER_00: Ouch! Um, yeah, I wish we had found it, but you know, the thing for me is that research is exploration, and you never know what you're gonna find.
• 12:44
  SPEAKER_00: Or what day might be the day you discover something.
• 12:48
  SPEAKER_00: Uh, could be today I come in and find something in my data, and oh my gosh, look at that.
• 12:53
  SPEAKER_00: Um, so that's always exciting.
• 12:55
  SPEAKER_00: Um, after years and decades of not finding something, is it still fun?
• 13:00
  SPEAKER_00: It is because to me the craft is fun, also.
• 13:03
  SPEAKER_00: Like I would love to discover dark matter or something else, even crazier, but I still have fun every day.
• 13:09
  SPEAKER_00: I'm writing programs, I'm analyzing data, I'm thinking about statistics.
• 13:12
  SPEAKER_00: These are topics that are fun for me, they're interesting puzzles.
• 13:16
  SPEAKER_00: Um, this is why I chose this field because 30 years ago I had fun working on little programs to analyze data, and I'm still doing that, and it's still fun.
• 13:25
  SPEAKER_00: Even if we discover nothing, it's a good time.
• 13:27
  SPEAKER_00: So that's why it's so important for students to figure out not just what field seems like it's asking fun big questions, but what field involves work that you enjoy doing day-to-day, right?
• 13:39
  SPEAKER_00: You can't hate the work because you can't rely on the big discoveries.
• 13:44
  SPEAKER_01: I love the way you put that.
• 13:46
  SPEAKER_01: How even if you don't find what you're searching for, you can still have lots of fun along the way.
• 13:52
  SPEAKER_01: And to this day too.
• 13:54
  SPEAKER_01: Has there ever been a moment when the data looked like you found something new?
• 13:59
  SPEAKER_01: What happens next?
• 14:03
  SPEAKER_00: Yeah.
• 14:04
  SPEAKER_00: One time a student came into my office and he had data that we couldn't explain.
• 14:09
  SPEAKER_00: And it looked a lot like the data you would expect from a new particle.
• 14:13
  SPEAKER_00: Like a bunch of collisions produced numbers that were very, very similar in exactly the way you would expect from a new particle.
• 14:21
  SPEAKER_00: And we thought, oh my gosh, maybe we found something.
• 14:24
  SPEAKER_00: But you know, the data are always indirect.
• 14:27
  SPEAKER_00: When you collide new particles, it's not like you produce a particle and then it sits there and you can like look at it.
• 14:33
  SPEAKER_00: Like I can't show you any Higgs bosons, I don't have any in my hand.
• 14:36
  SPEAKER_00: Uh we only saw them indirectly.
• 14:38
  SPEAKER_00: We thought we saw what they turned into because the Higgs boson or new other particle lasts for like a tiniest fraction of a second and then explodes into debris.
• 14:48
  SPEAKER_00: And so the patterns of the debris tell you what's there, but never uniquely.
• 14:52
  SPEAKER_00: You can say, oh, this debris looks like a new particle only because a bunch of different um collisions produced similar debris.
• 15:00
  SPEAKER_00: So it's never conclusive.
• 15:01
  SPEAKER_00: And so you can always find ways to convince yourself something's there when it isn't.
• 15:07
  SPEAKER_00: So we did like six months of cross-checks and understanding and like, is it this, is it that?
• 15:12
  SPEAKER_00: Can we explain it away this way?
• 15:13
  SPEAKER_00: And we couldn't explain it away.
• 15:15
  SPEAKER_00: There was no explanation for it.
• 15:17
  SPEAKER_00: Um, it was just a pile of events in exactly the way you would expect from a new particle.
• 15:23
  SPEAKER_00: Um, but we hadn't yet looked at all of our collisions.
• 15:27
  SPEAKER_00: We only looked at half of the data on purpose because we wanted to save the second half of the data to um help us understand if the particle was there after we'd cross-checked and made sure we didn't make any mistakes.
• 15:38
  SPEAKER_00: So we were very excited.
• 15:40
  SPEAKER_00: We opened the box on the second half of the data, we it was untouched, and uh we were hoping to see a similar pile of events in just the same way in the new data, which would tell us buy a ticket to Stockholm, you just discovered something.
• 15:53
  SPEAKER_00: But instead there was nothing there, which meant that the first pile of data was just luck, just bad luck or good luck, whichever you think about it.
• 16:01
  SPEAKER_00: Like in the same way that you can flip a coin a hundred times and you expect 50 um heads, and sometimes you get 52 or 57, and occasionally, very rarely, you will get like 75, and that doesn't mean that the coin is biased.
• 16:18
  SPEAKER_00: Just sometimes that's what happens, and so that's what happened here is that we weirdly randomly got a bunch of collisions that happen to pile up in the same place, the same way you would expect from a new particle, but this time it was just luck.
• 16:30
  SPEAKER_00: And that's why when we talk about discoveries in particle physics, we always say, you know, at 3 sigma confidence or 5 sigma confidence, that's telling you the probability for the background to randomly pile up in exactly this way.
• 16:43
  SPEAKER_00: And we only claim discovery when that's that probability is like very, very tiny, one in millions and millions of chances for that reason that we don't want to be fooled by random fluctuations.
• 16:54
  SPEAKER_00: So it was exciting for a few minutes, actually for a few months, while we thought maybe we had something, but then it went away.
• 17:01
  SPEAKER_01: In addition to searching for particles, you also write books.
• 17:05
  SPEAKER_01: What inspired you to collaborate with cartoonists for books on physics?
• 17:11
  SPEAKER_00: Well, I always wanted to share physics with everybody because it's publicly funded research, and you know, it's the universe.
• 17:20
  SPEAKER_00: The universe belongs to everybody, and I think there are a lot of people out there who are curious about it and want to know about it, want to understand what do we know and what don't we know without getting a PhD in physics.
• 17:33
  SPEAKER_00: And so I wanted to share the the the ideas and the joy and the mysteries with them.
• 17:38
  SPEAKER_00: Um, and I thought that cartoons would be a fun way to do it because they're very unintimidating.
• 17:44
  SPEAKER_00: Like uh, you know, sometimes I read books by famous physicists and I don't understand what they're talking about.
• 17:50
  SPEAKER_00: And I think like, well, if I can't get it, like who's understanding this?
• 17:54
  SPEAKER_00: So I wanted a book that was really accessible, really understandable, and that instead of intimidating you in a silence, put you at ease and made you feel like, oh, look, they're making fart jokes, so obviously this isn't something too serious that I can understand.
• 18:08
  SPEAKER_00: And so I reached out to a cartoonist and said, Hey, do you want to collaborate?
• 18:12
  SPEAKER_00: And he was interested.
• 18:13
  SPEAKER_00: And so we wrote a couple of books together, and now I'm working with another cartoonist on on a different couple of books.
• 18:19
  SPEAKER_00: And I just think it's um it's a fun way.
• 18:22
  SPEAKER_00: Number one, I like collaborating.
• 18:23
  SPEAKER_00: Um, writing by yourself is lonely.
• 18:26
  SPEAKER_00: Um, writing with somebody else is fun, and I like the flow of having both text and images because the text can be telling one story and the images can be telling another one, and they can sort of be in conversation, making fun of each other a little bit, back and forth.
• 18:40
  SPEAKER_00: And so um it also gives me a chance to work with really incredibly talented artists, um, which you know just elevates the books.
• 18:49
  SPEAKER_00: So um that that's why I work with cartoonists.
• 18:51
  SPEAKER_00: It's I just think it's fun.
• 18:54
  SPEAKER_01: Can you tell us how you balance being a scientist, author, and podcaster, and what each brings to your life?
• 19:01
  SPEAKER_00: Hmm.
• 19:02
  SPEAKER_00: Well, they're very different kind of work.
• 19:05
  SPEAKER_00: So, you know, being a scientist means um trying to get resources, thinking up questions, mentoring students, all this kind of stuff.
• 19:15
  SPEAKER_00: And um, you know, their daily puzzles of programming and data analysis, so it uses one part of your brain.
• 19:21
  SPEAKER_00: Writing and podcasting and communicating um uses a very different part of your brain.
• 19:26
  SPEAKER_00: It's explaining, it's translating, it's writing, it's choosing words, it's coming up with analogies.
• 19:32
  SPEAKER_00: So for me, it's a nice break.
• 19:34
  SPEAKER_00: Like when I'm stuck on physics, I switch over some writing jobs, and you know, it's a different kind of part of my brain, and so it gives my physics brain a break while my writing brain is working, and vice versa.
• 19:46
  SPEAKER_00: Um so for me it's it's pleasant to have these different kinds of things because I enjoy switching back and forth.
• 19:53
  SPEAKER_00: It's like uh, you know, deciding to go for a walk.
• 19:55
  SPEAKER_00: Uh you put you exercise your legs while you give your brain a rest.
• 19:58
  SPEAKER_00: For me, it's the same thing.
• 19:59
  SPEAKER_00: I'm exercising my walking legs while my physics brain rests.
• 20:03
  SPEAKER_00: Um so they're different kinds of challenges, they're both fun.
• 20:07
  SPEAKER_00: Um, I like meeting the different kinds of people in both worlds, like the writing world and the physics world, very different communities operate very differently.
• 20:15
  SPEAKER_00: You learn a lot about people and sociology and economics.
• 20:18
  SPEAKER_00: Um yeah, it's it's been a fun adventure.
• 20:22
  SPEAKER_01: Switching over to the AI side of things, if a machine found a pattern in collider data that no one could explain, would it still be physics?
• 20:34
  SPEAKER_00: Yeah, great question.
• 20:35
  SPEAKER_00: You know, that's exactly my research is like let's use machine learning to find patterns that nobody else can find.
• 20:41
  SPEAKER_00: And whether it's physics depends on whether we can understand it.
• 20:45
  SPEAKER_00: You know, if machines found a pattern and we wouldn't have found it on our own, but once we see it, we know what it means.
• 20:53
  SPEAKER_00: We could tell, oh, this is something new, then yeah, it's sort of like if machine learning found a Bigfoot, you know, could we understand it?
• 21:02
  SPEAKER_00: Yeah, man, we probe it, we test it, we like, you know, try to understand it.
• 21:06
  SPEAKER_00: The fact that machine learning or AI found it doesn't doesn't change what you do when you find it and how you understand it.
• 21:13
  SPEAKER_00: Um on the other hand, if AI is doing the interpreting, you know, if AI is studying the Bigfoot and it comes back with its conclusions, and we don't get to study Bigfoot by our ourselves, that you we don't get to be the ones asking the questions, then I don't know that that is really understanding.
• 21:30
  SPEAKER_00: So I think the crucial thing is that humans are still the ones asking the questions, driving the study.
• 21:36
  SPEAKER_00: Um, and and that's where the understanding comes from.
• 21:42
  SPEAKER_01: Could a machine learn physics in a way that looks nothing like ours?
• 21:48
  SPEAKER_00: Probably, yeah.
• 21:49
  SPEAKER_00: I mean, machines think differently and um and they're good at different kinds of things.
• 21:55
  SPEAKER_00: You know, a machine is not hesitant to make really big, complicated structures.
• 22:00
  SPEAKER_00: Involving lots and lots and lots of parameters because, like, whatever, it's got a perfect memory.
• 22:04
  SPEAKER_00: It uh doesn't struggle to remember what the 77th coefficient of something is, and so it doesn't need the same kind of simplicity.
• 22:13
  SPEAKER_00: So I think a machine would definitely build a different kind of explanation than we naturally would, um, for sure.
• 22:19
  SPEAKER_00: The same way that, like, you know, aliens might think differently, and their explanations of physics might be very different from ours in a way that reflects the way their brain works in contrast to the way that our brain works.
• 22:31
  SPEAKER_01: That's an interesting thought.
• 22:33
  SPEAKER_01: Ten to twenty years from now, what will someone doing your job do differently because of AI?
• 22:40
  SPEAKER_00: Oh man, I don't think I can predict that in one year, not to mention 10 to 20 years.
• 22:46
  SPEAKER_00: Um everything is changing in how our jobs work because things that used to be hard technically are now easy.
• 22:55
  SPEAKER_00: You know, I want to write a program that analyzes this data, and it requires pulling this kind of data and that kind of data and pulling it together and using packages that are badly documented that used to take weeks or months, so you have to find an expert to help you.
• 23:09
  SPEAKER_00: And now you can do that in an afternoon with AI, which reads the documentation and solves these problems and and writes the code, and in a in six months ago it would write code that was garbage and produce nonsense.
• 23:21
  SPEAKER_00: But now it writes code that's really good, and it produces real results that you can check and you can verify and that work.
• 23:27
  SPEAKER_00: And so it's accelerated science by making hard things faster.
• 23:34
  SPEAKER_00: Um, and so far it hasn't changed the process itself.
• 23:37
  SPEAKER_00: It's still, again, humans ask a question, do an investigation, AI has uh souped up those those investigations, but it's still the cycle of human understanding.
• 23:48
  SPEAKER_00: In the same way that like 50 years ago, when we first developed digital computers, they tremendously advanced the pace at which we could do science.
• 23:57
  SPEAKER_00: Like it used to be that to predict the weather six um hours in advance took six weeks of calculation, people like pen and paper and whatever.
• 24:07
  SPEAKER_00: When computers came about, we could for the first time make predictions that took less time than the universe, right?
• 24:15
  SPEAKER_00: We could say, okay, in six hours, we could take six minutes to predict what was gonna happen in six hours.
• 24:19
  SPEAKER_00: So it was actually useful.
• 24:21
  SPEAKER_00: And um that's huge, right?
• 24:23
  SPEAKER_00: And as a result, we didn't like stop doing science.
• 24:27
  SPEAKER_00: What we lost were people whose jobs were to do the hard the things that used to be hard and were now easy.
• 24:33
  SPEAKER_00: Like we used to have people whose jobs was computer, and they were a person, like a guy.
• 24:38
  SPEAKER_00: Like Einstein had a computer, a particular guy who would like do calculations for him.
• 24:43
  SPEAKER_00: And that job went away because now we had digital computers that could do those jobs much more efficiently.
• 24:48
  SPEAKER_00: And and so it's changed the way we do science, it's changed the questions we ask, the answers we can reach, and I think AI is gonna have the same effect.
• 24:57
  SPEAKER_00: Radically change the kinds of things we can do, but in a way that empowers humans to do more science.
• 25:03
  SPEAKER_00: I'm not worried about like AI taking my job.
• 25:07
  SPEAKER_00: We're always gonna be doing physics, we're always gonna have questions about the universe, no matter what AI can do, um, no matter what aliens share with us, we're always gonna be curious.
• 25:18
  SPEAKER_00: Um, and so we just have to keep you know following that curiosity and asking questions.
• 25:22
  SPEAKER_00: Whether there will still be academia and research funding in five years, I don't even know.
• 25:27
  SPEAKER_00: So, predicting the future that way, that's a social question.
• 25:31
  SPEAKER_00: Yeah.
• 25:33
  SPEAKER_01: Humans asking the questions while the algorithms just help speed up the code.
• 25:38
  SPEAKER_01: What is one concrete thing a student can do in the next year to move towards this kind of work?
• 25:46
  SPEAKER_00: I think the most important thing for students is to figure out who they are.
• 25:51
  SPEAKER_00: Like, what is your jam?
• 25:53
  SPEAKER_00: What is the thing that's going to make you happy and keep you occupied and feel satisfied?
• 25:58
  SPEAKER_00: If you knew today who you wanted to be at 45, like what your life what kind of life you wanted, you could just move towards it now.
• 26:07
  SPEAKER_00: It would be much easier than like, you know, trying this and trying that and wandering around.
• 26:12
  SPEAKER_00: It's sort of like, you know, finding love.
• 26:14
  SPEAKER_00: It's uh it's hard to know what you need and who to look for.
• 26:18
  SPEAKER_00: If you knew today who you wanted to be with the 45, you could just go find them.
• 26:22
  SPEAKER_00: Um but you don't.
• 26:23
  SPEAKER_00: You have to search around.
• 26:24
  SPEAKER_00: And so that's the thing, it's like try a bunch of different stuff, try different kinds of research, try computational stuff, try spending time in the lab, try, you know, um theoretical stuff, try different fields, just see how you react, and then pay close attention to that voice inside you that tells you whether you're having fun.
• 26:45
  SPEAKER_00: Don't do things that you think you're supposed to like, do the things you actually do enjoy.
• 26:50
  SPEAKER_00: Pay attention to that voice uh that tells you whether this is your jam or not.
• 26:55
  SPEAKER_00: Because that's the most important thing is figuring out where you fit in.
• 26:59
  SPEAKER_00: Because if you're doing the thing that you're excited about, then you're gonna do your best work because it's gonna keep you occupied, it's gonna keep you up at night, you're gonna have ideas while you're you know watching a movie, you're gonna scribble them down, um, it's gonna bring out your creativity and your passion, and also then as long as you're working on that, you're having fun.
• 27:21
  SPEAKER_00: And then when it whether it works out and you get to be a professor in that or you end up in industry making zillions of dollars or whatever, if you've been having fun, then you learned something and you had a good time, and whether you end up getting a job in that, you know, um, you can't feel like bitter about the time you spent, you know.
• 27:40
  SPEAKER_00: So don't work on something you think you're supposed to that you secretly hate, and then five years later you can't get a job and you're like, eh, and I hated it for five years, you know.
• 27:49
  SPEAKER_00: If you're sobbing into your keyboard, then you're in the wrong area.
• 27:54
  SPEAKER_01: For the student who's still trying to figure out what they enjoy, what advice do you have for them?
• 28:02
  SPEAKER_00: Um, try a bunch of different stuff, you know.
• 28:04
  SPEAKER_00: What are your friends enjoying?
• 28:06
  SPEAKER_00: Um, does that sound fun to you?
• 28:08
  SPEAKER_00: What are your parents, what do your friends' parents do?
• 28:10
  SPEAKER_00: You know, just you gotta explore because the things you know about now are a tiny fraction, you know, the pot possible lives that you could live, and the people you've met so far um, you know, don't give you the full breadth of possibility.
• 28:25
  SPEAKER_00: Not because they're you know not trying to, but you just haven't met enough people.
• 28:30
  SPEAKER_00: Um, and so you gotta go out and meet people, travel, move away, you know, don't go to college where you went to high school, don't go to grad school where you went to college, meet new people, explore, get different perspectives, eat weird stuff for breakfast, you know.
• 28:45
  SPEAKER_00: Um seriously, like you go to different countries where like you know they have spicy fish soup for breakfast, and you're like, what?
• 28:51
  SPEAKER_00: That's insane! And then you discover, oh my gosh, this whole time a spicy fish soup is what I wanted for breakfast.
• 28:57
  SPEAKER_00: I didn't even know it existed.
• 28:59
  SPEAKER_00: And you know, that's just a silly example, but like, how do you know you don't want it until you try it?
• 29:04
  SPEAKER_00: And so you have to discover who you are, and the best way to do that is to just go explore different ways of living and thinking and being.
• 29:13
  SPEAKER_01: What surprised you the most about this job when you started, and which skills do you think are underrated?
• 29:20
  SPEAKER_00: Hmm.
• 29:21
  SPEAKER_00: I didn't realize how being a professor had so many aspects to it you're never taught.
• 29:29
  SPEAKER_00: Like, I got taught physics and I got taught how to do research, but a big part of my job is teaching, and nobody ever taught me to teach.
• 29:38
  SPEAKER_00: I just like show up and they expect me to know how to do it and do a good job at it, but there's no education in teaching, like there's no training.
• 29:46
  SPEAKER_00: Um, and I manage a group which requires like understanding the finances and budgets and all sorts of stuff.
• 29:54
  SPEAKER_00: There's no training in that, and I mentor students.
• 29:58
  SPEAKER_00: Like I have to find projects for them and think about how they can grow and what their strengths and weaknesses are.
• 30:04
  SPEAKER_00: There's no training for that.
• 30:05
  SPEAKER_00: So it's a many faceted job, and you're trained in one area and selected for your your work in that area.
• 30:13
  SPEAKER_00: The reason that you get a job in physics is because of your of your research, and then you're expected to be good at all these other things also, for which there's no training.
• 30:22
  SPEAKER_00: Um, and so it's fascinating.
• 30:24
  SPEAKER_00: Um, and I like all those other things, so that's worked out well for me because I like teaching and I like students and I like um all that stuff.
• 30:32
  SPEAKER_00: One of my favorite things that's a surprise to me is, and this is gonna sound obvious, is that I get older, but the students stay the same age.
• 30:41
  SPEAKER_00: So, you know, they're always college students, there's 18 to 22, or the grad students are always, you know, 21 to 26, and there's like a an energy there and an enthusiasm and a little bit of naivety, and it's wonderful, and I love this age.
• 30:55
  SPEAKER_00: Um, they're so fun to talk to, there's so much optimism about life and the future, and I like um helping them and guiding them, and and um it fuels me.
• 31:07
  SPEAKER_01: Out of all the wonderful mysteries in the universe, what is one question you most wish you could answer?
• 31:16
  SPEAKER_00: Oh man, um you know I've devoted my whole life to asking the question, what's the universe made out of?
• 31:25
  SPEAKER_00: I think that if the universe has like a base layer of reality and some bits that it's made out of that are not made of smaller bits, they're just made of themselves, that that tells you something about the nature of the universe, something deep about its um quality.
• 31:45
  SPEAKER_00: And I want to know that, you know, what is the thing, the most basic thing the universe is made out of, because then everything that comes afterwards, you know, quarks and leptons and atoms and dark matter and ice cream and kittens and lava, that's just chemistry.
• 31:59
  SPEAKER_00: It's like uh, you know, how do you arrange this stuff to make different stuff?
• 32:02
  SPEAKER_00: I want to know the core nature of it, because philosophically that's I think very revealing.
• 32:09
  SPEAKER_00: Or maybe it doesn't even have one.
• 32:10
  SPEAKER_00: Maybe it's just like, you know, layers upon layers upon layers all the way down infinitely.
• 32:15
  SPEAKER_00: There's no base layer of reality.
• 32:17
  SPEAKER_00: And that would be fun to know also.
• 32:19
  SPEAKER_00: So, you know, if I could speak to an oracle or like super advanced aliens, um, then that's the question I would ask.
• 32:26
  SPEAKER_00: Is what is everything made out of fundamentally?
• 32:29
  SPEAKER_01: And before you go, what books, podcasts, or other media would you recommend for a student who wants to learn more?
• 32:38
  SPEAKER_00: Well, you can check out my podcast, uh Daniel and Kelly's Extraordinary Universe.
• 32:42
  SPEAKER_00: We talk about all the physics and biology and mysteries of the universe in a fun and accessible way.
• 32:48
  SPEAKER_00: Um, I also like uh Sean Carroll's podcast, Mindscape, that's a little bit more advanced.
• 32:54
  SPEAKER_00: Uh, guy's a very deep thinker, but he's a great explainer.
• 32:57
  SPEAKER_00: And uh The Joy of Why from Quanta is an excellent podcast on science, a lot of fun.
• 33:03
  SPEAKER_00: Steven Strove guides and Jan Eleven are excellent.
• 33:06
  SPEAKER_01: Dr.
• 33:07
  SPEAKER_01: Whiteson, thank you so much for joining us on passive curiosity.
• 33:15
  SPEAKER_00: Thanks so much for the fun uh conversation.