In this “Only in America” conversation, Stanford professor and World Labs co-founder Fei-Fei Li, often called the “godmother of AI,” sits down with historian Stephen Kotkin to trace her journey from a 15-year-old immigrant in New Jersey to a pioneer of artificial intelligence. They discuss ImageNet, spatial intelligence, the pursuit of truth in science, deepfakes, civic responsibility, and how America must adapt to the cultural and technological changes ahead. Read the full transcript of this interview below:
Introduction
CONDOLEEZZA RICE: Curiosity is a universal human trait, and it’s a key ingredient in the scientific and technological discoveries that have advanced the human condition over centuries. But curiosity alone does not lead to discovery and innovation without the freedoms guaranteed in a nation like the United States of America.
In unfree societies, curiosity is often stymied. It is often discouraged, and it is often met with violent repression. Ask too many questions or search for alternatives to the officially sanctioned way of doing things, And it’s dangerous. In authoritarian societies, it can get you killed. But curiosity, when allowed to follow its course, can bring fabulous and novel inventions into our world, enriching lives and changing history in the process.
Fei-Fei Li embodies the pursuit of truth that is driven by curiosity. Often referred to as the “godmother of AI,” Fei-Fei spoke with Senior Fellow Stephen Kotkin at her company’s headquarters in San Francisco, where curiosity enabled by the unique conditions of freedom in the United States is pushing the boundaries of what is possible with artificial intelligence.
Fei-Fei’s story illustrates the best that our country has to offer. Here now to discuss her “Only in America” story, Fei-Fei Li.
Arriving in America: The Paradox of Opportunity
STEPHEN KOTKIN: (00:03:33 – 00:04:26) I’m here with Fei-Fei Li, co-founder of World Labs here in San Francisco, a colleague of mine, a professor at Stanford University. So you and I overlapped at Princeton. I was on the faculty there. You were an undergraduate, although you eventually joined the faculty and we overlapped on the faculty as well.
Now, so Princeton University undergraduate, Caltech PhD, Princeton University again on the faculty, Stanford University faculty, lots of opportunity there. Talk about your understanding of opportunity and institutions and what opportunities came your way and when and how you understood them and how you took advantage of them and made them work for you.
FEI-FEI LI: (00:04:27 – 00:05:02) Opportunity is a great word in America. As an immigrant, I came here with my parents when I was 15 years old, and we landed in New Jersey, an hour away from Princeton. So, Parsippany, New Jersey.
As an immigrant, there was a really interesting paradox. Because I did not know the language, we did not know anybody. My parents, just like so many immigrants, we came with $20 in our pocket. So there seemed to be no opportunities.
STEPHEN KOTKIN: (00:05:02 – 00:05:13) So you’re a high school-aged young girl landing in New Jersey, which maybe wasn’t part of the geography of the schools that you had previously gone to. No.
FEI-FEI LI: (00:05:13 – 00:05:18) Right. And also, I was too young. My parents made the decision. I didn’t even know what I was doing.
STEPHEN KOTKIN: (00:05:19 – 00:05:19) Right.
FEI-FEI LI: (00:05:20 – 00:05:24) Yeah. So at the beginning, it seemed like there was no opportunity.
STEPHEN KOTKIN: (00:05:24 – 00:05:24) Yes.
FEI-FEI LI: (00:05:25 – 00:06:11) But if we fast-track to 30-plus years later where I am, I am so grateful that this land is truly a land of opportunities. Looking at the journey my family and I have taken, that I now get to appreciate that I had the freedom to pursue any opportunity I could work for. And that really was big.
That has become my understanding of opportunity, is not anything that’s handed to you, is a place that allows you to work so hard, to dream big or small, and to seize those opportunities.
Princeton, Physics, and Albert Einstein
STEPHEN KOTKIN: (00:06:12 – 00:06:57) So it’s hard to imagine a 15-year-old not speaking English to then be receiving a few years later a bachelor’s degree from Princeton University, a PhD from Caltech. But there must be some drive or parental support or some ambition and some vision that puts you in a position to see those opportunities.
Not everybody understands, for example, that they should apply to Princeton University even if they live an hour away. It’s something that has— people have to understand that that opportunity is there. So what happened for you to perceive those opportunities or drive you to those opportunities?
FEI-FEI LI: (00:06:57 – 00:07:48) That’s a great question. The reason I applied to Princeton, it has only one thing to do with one person in the universe, and that’s Albert Einstein, is because I was— since I was a teenager or preteen, I just loved physics. Physics was my first love. Till today, I still love physics, even though I’m so far away from physics right now.
But as a teenager, even though I was an immigrant, my parents and I had to work all kinds of jobs— cashier, cleaning girl, restaurant takeout girl, and all that. I dreamed about physics. So when I was applying for college, I applied for Morris County College. I remember that’s where Parsippany is, Morris County.
STEPHEN KOTKIN: (00:07:48 – 00:07:48) Yes.
FEI-FEI LI: (00:07:48 – 00:07:51) I applied for New Jersey State University, Rutgers.
STEPHEN KOTKIN: (00:07:52 – 00:07:52) Yes.
FEI-FEI LI: (00:07:52 – 00:08:01) But I just had to apply to Princeton because that’s where Albert Einstein was. You asked about what was the push.
STEPHEN KOTKIN: (00:08:02 – 00:08:02) Yes.
FEI-FEI LI: (00:08:02 – 00:08:33) That’s a really interesting question because my parents are, in hindsight, are relatively unique in my opinion, is that they didn’t push me. They generally, they were not the ones who were checking my homework, asking which college I was thinking of checking, partially just because they don’t have, they didn’t have the knowledge to even know how to push me.
STEPHEN KOTKIN: (00:08:33 – 00:08:34) First generation.
FEI-FEI LI: (00:08:34 – 00:09:56) First generation.
They were trying to be— survive. And it was very, very difficult. I wrote that in my book, “The Worlds I See.” My mom had very bad health till today. So they didn’t push me because they didn’t know how to push me.
But in hindsight, they gave me the unconditional love to pursue my dream. They never said because we were poor, you have to be a doctor, or you have to be an accountant, or you have to be something. When I was totally in love with special relativity and Albert Einstein, not for a single moment they said, “This is probably not the easiest path to make money.” They just never did that.
And my dad came with an innate sense of curiosity. He would find curiosity in a— we didn’t have money to go to paid entertainment, but he would take me to parks that are free. He would take me to yard sales that he finds it fun to— almost like a scavenger hunt. And so he finds curiosities in so many places in life. That was a gift that I didn’t know it was a gift till I grew up and realized that was a gift.
STEPHEN KOTKIN: (00:09:58 – 00:10:24) Yes. I have to say our stories are somewhat parallel in the sense that my family is also an immigrant family, but I’m 4th generation. I was the first generation to go to college. I was rejected from Princeton University, undergraduate and PhD, twice, in fact. But when I got there as faculty, the first thing I did was to try to find Einstein’s office.
FEI-FEI LI: (00:10:25 – 00:10:27) Yeah. In the Advanced Institute.
STEPHEN KOTKIN: (00:10:28 – 00:10:40) Yes. And so I found the building it was in, but there was no plaque for his office. But there were German words. There was a German saying above the fireplace in the common room.
FEI-FEI LI: (00:10:40 – 00:10:42) Yeah, I know that fireplace very well.
STEPHEN KOTKIN: (00:10:42 – 00:10:43) Yes, exactly.
FEI-FEI LI: (00:10:43 – 00:10:56) So my first week, because I went in knowing I want to do physics, we were in this— I think that building is rebranded. It was called Palmer Hall. We were in this lecture room.
STEPHEN KOTKIN: (00:10:56 – 00:10:57) Yes.
FEI-FEI LI: (00:10:57 – 00:11:08) My physics professor said Einstein used to sit in these seats, and I was there, right? I just felt like I died. I went to heaven.
The Audacious Question of Intelligence
STEPHEN KOTKIN: (00:11:08 – 00:11:44) Yes. So you get into these institutions in the United States, and again, you have to find your way. But the trajectory you make of entering Princeton University in the physics department— and by the time you blink your eye, here you are with a PhD from Caltech. You’re carving this career out for yourself.
How are you understanding the path that you’re on? Are you on a path? You’re a woman in physics and in computer science that maybe wasn’t the dominant gender back then, at least from—
FEI-FEI LI: (00:11:44 – 00:11:47) still is not, from my recollection. Yeah.
STEPHEN KOTKIN: (00:11:47 – 00:11:57) So there’s a whole bunch of issues that one could imagine of how you navigated these spaces to seize those opportunities and to become the person you became.
FEI-FEI LI: (00:11:58 – 00:12:43) Well, there are different aspects to answer this question. First is the career path, and of course intertwined is the journey of becoming who you are for every person. Let me just start with the career path.
I think I went into Princeton undergrad physics for the love of actual science of physics. But I realized along the way what I truly love about physics, it’s not even necessarily the quantum mechanics, special relativity, and Maxwell equations, not even necessarily those, is the audacity to ask the hardest questions possible. The craziest, hardest questions.
STEPHEN KOTKIN: (00:12:43 – 00:12:43) Exactly.
FEI-FEI LI: (00:12:43 – 00:14:29) That was what physics taught me, is that there are people hundreds of years before us who wanted to understand the path of all stars. There are people 100 years before us who wanted to see the smallest particles of the universe. And there is Albert Einstein questioning, “What is time?” These are the most audacious questions. So I was very inspired by that.
So around my third, you were talking about junior paper, senior thesis. Around that time, Princeton partially forced you to think about what’s your choice of your junior papers and senior thesis. I start to ask, what’s my audacious question?
And I was so inspired by these giants of 20th century physics, the Schrödingers, the Einsteins, the Roger Penrose of the world. That towards the second half of their career, they start to ask questions beyond atomic world. Einstein is always a humanist. Schrödinger wrote the book, “What Is Life?” Roger Penrose wrote the book “The Emperor’s New Mind.”
So I was so inspired. I realized my audacious question is intelligence. I wanted to understand if we can build machines that can be intelligent? I did not know at that time it was Alan Turing’s question. I wasn’t the first person in the world to ask that question, but I came from physics. I wasn’t reading Alan Turing yet. So obviously Alan Turing in the 1940s actually asked that question, “What is a thinking machine?” right?
STEPHEN KOTKIN: (00:14:30 – 00:14:30) Yes.
FEI-FEI LI: (00:14:30 – 00:15:05) So I decided that I’m going to go pursue the most audacious question of my career, which is AI or intelligence. That’s when I went to Caltech. But at Caltech, I actually did almost a dual track. I did both computational neuroscience as well as artificial intelligence.
And like you said, it’s a blink. I never left that dream. It’s just— I feel so lucky and blessed that I found that.
Audacity, Courage, and the Immigrant Story
STEPHEN KOTKIN: (00:15:05 – 00:15:36) But the audacity though, Fei-Fei Li, that’s really the critical dimension here. A lot of us are sometimes looking what others are doing, how can we fit in, conformity.
I used to joke at Princeton that there were 2 things I don’t teach. One is creativity, because you can’t teach creativity. It’s a sort of genetic or it’s innate. And the other was conformity, because they already know that. Yeah. And then there’d be silence in the room.
FEI-FEI LI: (00:15:37 – 00:15:38) They’re like, “What’s left?”
STEPHEN KOTKIN: (00:15:39 – 00:15:48) After I would say I don’t teach conformity, there’d be silence in the room. And then I would say, “See, there’s no need to teach it.” But here we’re talking not conformity, we’re talking audacity.
FEI-FEI LI: (00:15:49 – 00:15:49) Yeah.
STEPHEN KOTKIN: (00:15:49 – 00:16:39) We’re talking about reaching for things, stretching for things, maybe finding a pathway that isn’t the well-lit pathway or isn’t the path dependence that we’ve come out of. So you write your senior thesis, you go to Caltech, you have neuroscience, you have artificial intelligence. By the way, that’s actually a combination that we see quite a lot in your generation and the generation after.
And so that audacity, that daring to go for it, to reach, to find something that’s not the obvious pathway. That’s a pretty special— that’s the curiosity that you talked about that came from your father. That’s still a pretty special trait.
FEI-FEI LI: (00:16:40 – 00:17:43) I think it’s a combination. And this really, to this day, I believe it’s part of my immigration story. It’s the curiosity combined with courage and fearlessness. And I attribute this to my parents as well as millions and millions of immigrants who come to this country, is that you have to have the courage to take the step of the unknown.
I did not have that introspection to think the last thing you want to do is to give credit to your parents as a teenager. But really, it’s their courage and fearlessness that landed me here.
And the one thing I learned as an immigrant teenager is that truly there’s no path to follow. I don’t even understand the language, let alone following path, right? So you almost have nothing to lose.
STEPHEN KOTKIN: (00:17:43 – 00:18:44) People attribute the striving culture in America often to the frontier. And I think there’s— there is something to the frontier story, obviously. And then we talk about the endless frontier in science, and the frontier metaphor is deep in American DNA.
My experience, again, was slightly different. My parents wanted me to take those well-beaten tracks and to become a doctor or a lawyer. And of course, I disappointed them and became only a history professor.
But nonetheless, the striving culture that they instilled, even though we’re 4th generation, of wanting success for the progeny, for the people, not only for themselves or not even for themselves, but for their offspring. And then driving and pushing and facilitating— maybe facilitating is a better word than pushing. And your parents teach you things that you don’t even realize that they’re teaching just by their example, as you’re describing it.
FEI-FEI LI: (00:18:44 – 00:18:44) Yeah.
STEPHEN KOTKIN: (00:18:44 – 00:18:54) But this striving culture and this reach for the stars audacity, that definitely is part of the immigration story, no question.
FEI-FEI LI: (00:18:54 – 00:19:50) It is part of the immigration story. It’s also part of the story of freedom, because as I grew up, I— as a grown-up now, I realize freedom also gives you agency. Yes, right.
And as an immigrant kid with total freedom to do whatever, but knowing you have to survive and thrive— yes, that instilled such a strong sense of agency that I have to make it, I have to do this, I have to reach for the stars or for whatever by myself.
And I think that is very much a— I’m not saying it’s only to immigrants, but it is so innate into an immigrant’s life story. And the other thing is beaten path, right?
STEPHEN KOTKIN: (00:19:50 – 00:19:50) Yeah.
FEI-FEI LI: (00:19:52 – 00:20:25) I never thought about this in the early years of my career, but now as a scientist, I realized being an immigrant and being a scientist have a lot of similarity. It’s where you have to cross borders. You have to cross boundaries.
Is that being an immigrant is crossing linguistic language boundaries, cultural boundaries, and I mean everything, right? Being a scientist is also crossing boundaries. You have to cross between the known and the unknown.
STEPHEN KOTKIN: (00:20:25 – 00:20:25) Yes.
FEI-FEI LI: (00:20:26 – 00:20:49) You have to cross between neuroscience and computer science. You have to cross between— now, when we talk about human-centered AI, technology to social science and humanities. So whether we’re crossing physical boundaries, language boundaries, or crossing knowledge boundaries and imagination boundaries, they actually share similarities.
Science, Truth, and Civic Responsibility
STEPHEN KOTKIN: (00:20:49 – 00:22:00) Yeah. Let’s talk a little bit more about science. I love this concept of seizing one’s destiny and creating one’s destiny and having— equating that with freedom, that you have the freedom to do, not just freedom from constraints, but freedom as an ability or an opportunity to do the kind of stuff that you might have dreamed about.
So you become a scientist. Science is a practice. It’s a way of thinking, a worldview. It’s a bunch of incredible instruments. It’s all these hard problems. It’s so many things, science. As you know well.
What’s the relationship in your mind between science and democracy, or science and freedom, or science and the other institutions that are in the political space? How do you feel as a scientist? What are your sort of moral responsibilities, civic responsibilities? Do you see those civic responsibilities as a scientist? And how do you conduct yourself as a result of this kind of nexus between science and civic responsibility, or science and democracy, science and freedom?
FEI-FEI LI: (00:22:02 – 00:23:37) So I think the most important moral responsibility as a scientist is to pursue truth. And it’s very important to emphasize science doesn’t mean it’s truth. Just because we’re doing science doesn’t mean we know it all and we know the truth.
It’s the pursuit of truth using rigorous methodology, using instruments, whether it’s physical instruments, experimental instruments, the instrument of debate and reviews and all that. And I think that’s a moral responsibility as scientists is that we have to be so intellectually honest that our goal is to pursue truth driven by curiosity or creativity or the desire to cure cancer or to whatever it is.
So that, I think, to me also can transcend science, right? It’s— as a person, I actually feel the line between being a scientist at work versus being a person in life does blur because I prefer truth. I prefer the freedom to uphold truth. I prefer that I’m allowed to pursue truth. And that’s important.
STEPHEN KOTKIN: (00:23:39 – 00:24:03) We may disagree about what the truth is at any given moment, of course, but we agree usually about the mechanisms of getting to the truth. We understand evidence and the necessity of evidence, preponderance of logic, for example, verification, so that if you do something, others need to verify it before it’s widely accepted.
FEI-FEI LI: (00:24:03 – 00:24:13) Part of pursuing truth can be messy because at some point those methods will butt against more messier things like value.
STEPHEN KOTKIN: (00:24:14 – 00:24:14) Yes.
FEI-FEI LI: (00:24:15 – 00:24:38) So I recognize that, and I come from hard science, physics and computer science. Even though there is probability theory, but by and large these hard sciences are pretty clean and deterministic and mathematical. But human world is messier, way messier.
STEPHEN KOTKIN: (00:24:39 – 00:24:39) Don’t I know it.
FEI-FEI LI: (00:24:39 – 00:25:08) Yes, you’re a historian, you know that. So I don’t think we should be, at least as a scientist from a technology field, I don’t think we have moral high ground of truth or even the methodology of truth.
I actually have a lot of respect to humanities and social science because in your pursuit of truth, it’s actually messy. There are things that cannot be totally measurable, or it’s hard to be measured.
Deepfakes and the “Truth Regime”
STEPHEN KOTKIN: (00:25:09 – 00:26:01) In some ways now, we’re having trouble with what you might call the truth regime, or the ways, the mechanisms in which we agree on the truth. We now have technologies that can fake people’s voices, behavior, the fake videos, so-called deepfakes.
In some ways, the truth regime is under siege by scientific techniques themselves, even though science, as you rightly point out and as you’ve written about and lectured so often about, is the pursuit of truth. So how do you as a scientist navigate this problem now where some of the deepest and most important discoveries that we’re making are putting pressure on the truth regime, so to speak.
FEI-FEI LI: (00:26:01 – 00:27:56) Yeah. Once again, I want to be very clear that the scientific career of pursuing truth doesn’t mean we know truth. I think that is so important because people do confound that, and even scientists themselves. So that humility of knowing we don’t know is very important.
The humility of knowing that a technology that we created, which my generation and my colleagues and I created, are now creating, constructing artifacts that will challenge what you call truth regime, is a very reality of our technology, the same technology that helps us to simulate productive environments for robots and self-driving cars, to simulate potential molecular pathways of viral infections, can be a technology that’s used for what you call deepfakes and all that.
So it is— this is why actually I started, co-founded Stanford’s Institute for Human-Centered AI. Because I think it’s very important to invite everybody to come and look at these issues and take advantage in a positive way these tools we build, but also look at how we can harness these tools and avoid harm.
So it’s messy, but it’s a necessary reality that we’re living as humanity invents more and more powerful tools with the intention of helping people, but creating also realities of messiness.
STEPHEN KOTKIN: (00:27:57 – 00:28:08) Respect, but humility, but the striving still remains. One can be humble, but— and one can have respect, but still the point is not to give up or not—
FEI-FEI LI: (00:28:08 – 00:28:09) no, never.
Building World Labs and Spatial Intelligence
STEPHEN KOTKIN: (00:28:10 – 00:28:24) Exactly. Yes. Let’s talk a little bit about what America is to you now. After all of these experiences, here we are at World Labs, which you founded in 2024.
FEI-FEI LI: (00:28:24 – 00:28:27) Yes, I co-founded with 3 other co-founders.
STEPHEN KOTKIN: (00:28:27 – 00:28:57) Right. And so tell us a little bit about World Labs, the story of World Labs, and how that connects to the kind of story of America. We started with opportunity. We talked about striving culture. We talked about pursuit of truth. We talked about freedom and the ability to pursue one’s dream. Let’s talk a little bit about how World Labs fits into that trajectory and what it might mean for our understanding of America.
FEI-FEI LI: (00:28:59 – 00:32:13) Yeah, so I started World Labs with the 3 other co-founders because we have a very audacious technological dream. And we believe this dream will be very important for making people’s lives and work better. And that’s about spatial intelligence, is the next chapter of AI’s frontier.
So 2024 was about 2 years after ChatGPT. The language model, large language model, is taking the world by storm because both in terms of our daily usage as well as workplace usage, we can see how incredibly powerful it is. But we also know that even through human intelligence as well as human work, there’s so much that is beyond language.
Our interaction with the 3D world, our design from home to factory to cities to big machinery, our ability to express and create, our need to simulate and train from surgeons to athletes. All these are beyond the regime of language. And I call them spatial intelligence. And that’s what we wanted to do.
We wanted to build a frontier model company that creates the frontier model of spatial intelligence so that we can empower whether it’s creators or robotics or healthcare or education and enterprise uses. That’s the birth of World Labs.
How does that connect to all the keywords you hit? Well, first of all, it’s a audacious technology goal. It’s a goal that, it’s a thesis I formed over the years as a researcher at Stanford doing the AI research, computer vision, robotics. These are the work I have done at Stanford. It helped me to arrive at the point of knowing and believing spatial intelligence is the next big frontier. That’s one thing.
Second is I love building. I always joke, right? My first company was a dry cleaning store shop. And I love building technology. I love building a team that can go after big, audacious problems.
I was lucky I have built ImageNet that brought— that contributed to the birth of modern AI. I built Stanford Human-Centered AI Institute so that this group of brilliant faculty and staff and students can work towards important problems. And I would love to, at this moment, build a startup that is focusing on spatial intelligence.
From ImageNet to Multidimensional Intelligence
STEPHEN KOTKIN: (00:32:14 – 00:34:57) So there were a whole bunch of amazing papers on neural networks. Intellectual breakthroughs, just brilliant stuff. Geoffrey Hinton, Yann LeCun, including on images and neural networks. And so you came along and you made it operational. You decided that, hey, these things need data. They need huge inventories of images in order for us to improve this capability. And use this capability.
So here you are, a young computer scientist, you’re in a career track, there’s things like tenure and publications and expectations, and you decide to go for broke on building out this colossal dataset of images. We’re talking millions and millions of images. 50 million, right? 50 million images. They have to be coded. You have a research budget. It’s not clear how one can pull off all of this work.
Anyway, long story short, you pulled it off and you brought that ImageNet from Princeton out to— maybe it started at Caltech back in the days. You brought it out to Stanford and you made the neural networks with images a reality. I think that’s— we— that’s an astonishing breakthrough.
But now it’s not just images. There’s something bigger than just images. I remember the LLMs and their words when they first broke through, because I work in words like most people in an academic setting, and it was pretty remarkable when you saw that. But the debate about intelligence I found to be a little bit strange.
Because even though it could do words maybe as well as I could do, maybe better when it first came out, and certainly now it’s much improved, but that’s not necessarily how intelligence works. The images stuff that you showed already before that was one hint of that. The degree to which this is, quote, “intelligence” remains a question.
Now we have this notion of the 3D world. Right? The world as it is, the world as humans navigate it, the ability to recognize, to perceive, to make decisions, to invent, etc. So now this is a sort of a second iteration of that leap in many ways, from images now all the way to 3D, as I understand it.
FEI-FEI LI: (00:34:57 – 00:35:55) Yeah. So I firmly believe intelligence is multidimensional. In fact, if you look at evolution, the trajectory of animal intelligence started with sensing and perception, not with language, especially not with the sophisticated human language, right?
Humans is practically, for most practical purposes, the only animal with language. I know that we have some animals that communicate by songs or whatever, but they’re not sophisticated language structure with a ton of syntax and semantics.
So language is an evolutionarily speaking, a phenomenon that started a few hundred thousand years ago, whereas intelligence driven by the first moment animals see light or touch on the surface is a half-billion-year journey. Started under the ocean.
STEPHEN KOTKIN: (00:35:55 – 00:35:55) Yes.
FEI-FEI LI: (00:35:55 – 00:37:01) Where trilobites saw the first glimpse of light, and that changed the entire trajectory of animal evolution because suddenly the concept of prey and predators became the central force of evolution. And so intelligence evolved more and more complex in order to respond to that survival pressure.
So that is a long way of saying that intelligence is highly multidimensional. It involves seeing, it involves touching, it involves planning, it involves talking. It involves communicating. It involves comprehension and reasoning in complex 3D world. It involves the ability to imagine and predict what is to come spatially as well as semantically.
So you’re right. I do think in order to fully realize the dream of AI. It’s a multidimensional approach.
Mentorship and Civic Responsibility
STEPHEN KOTKIN: (00:37:03 – 00:38:51) Yeah. And so let’s bring this back to the civic story, responsibility, civic responsibility, education, mentoring. You’re driving the science along with your colleagues. It’s just a spectacular story. There are all sorts of implications that we can’t fully understand yet. We try as laypeople to follow the debates and we do the best that we can, but some of it is confusing to us.
But what’s not confusing to us is that we have a set of institutions here in the United States to help us when we have differences of opinion, when we have shortcomings, we’re underperforming some of our promises and values. Opportunity is there, but is it spread widely enough so that there’s equality of opportunity on the front end so that, as I said, we can get the next Fei-Fei Li’s, who land here in the middle of New Jersey without the language, but can then create something special for themselves and touch many lives like that. And the ones who came before you, obviously, that we build on.
And so I’m thinking, where do we connect all the amazing— this is a private company, World Labs, and Stanford’s a private university, but we have a sense of civic responsibility. We have a sense that there’s a gift here of America, that we’re beneficiaries of something that others started before us, and we are stewards of it and want to pass it on, maybe even in a better way than we received it.
But how do you understand your platform, your civic responsibility, your mentorship, your influence on others, your ability to spread opportunity? What’s your thinking about that part of America?
FEI-FEI LI: (00:38:52 – 00:38:58) I don’t go around thinking I am a platform. That’s just not my personality.
STEPHEN KOTKIN: (00:38:58 – 00:38:58) Fair point.
FEI-FEI LI: (00:38:59 – 00:39:10) But one of my biggest privilege of my career is not only I’m a scientist, a technologist, I’m also an educator and a mentor.
STEPHEN KOTKIN: (00:39:10 – 00:39:11) Exactly.
FEI-FEI LI: (00:39:11 – 00:40:44) And even as a founder CEO I sometimes feel I have this dual role of being a business leader of a company, but also a mentor because the entire company that I have, they’re younger than me. And it’s such a privileged state and a humbling state to be in.
And so that part of my being a mentor and educator is, in my opinion, the biggest one of the biggest privileges of my life. And I take that seriously. I take that as a sense of responsibility.
I think that is— you use the word civic a lot. I’m a citizen of this society of America. I’m also a citizen of the world, a person living on this earth. And I really do believe that the hats I wear, I want to make a positive impact.
I’m very humbled and privileged that my technology is pushing the civilizational innovation forward. But I also think the mentorship, the education opportunities, the thought leadership, including the business, the products that we build, I care a lot about making a positive impact that is for the human flourishing.
STEPHEN KOTKIN: (00:40:44 – 00:40:45) Yes.
FEI-FEI LI: (00:40:45 – 00:40:51) And to me, that is my responsibility and privilege simultaneously.
America Is Change
STEPHEN KOTKIN: (00:40:52 – 00:41:58) Okay. Your story proves that there is something called the American dream. You dreamed it and you realized it. Again, sometimes we fall short. Sometimes we don’t live up to our ideals, and people don’t have the opportunities that they should have, and then it’s on us to try to provide that. But there’s got to be an American dream because you’re an empirical reality.
Let’s talk a little bit about how America could be changed. What in America doesn’t work for you or falls short? You exhibit the kind of very becoming humility that we don’t always see in people with degrees in physics and computer science, and it’s a joy to see that.
But allow yourself a little bit now to speak about America more broadly and about what you’d like to see us do better and how you could sort of charge us or inspire us to do that work ourselves, not just yourself doing it?
FEI-FEI LI: (00:42:00 – 00:42:55) America to me is change. This country is founded on the desire to change, right? One of the most— I mean, I’m talking to a historian— one of the most beautiful parts of the history of America is the founding story, the story of the Constitution, and that is about change. Talking about dream for the better.
So I would love for us as a country, as a society, and hopefully still as part of the leading societies of this world to embrace and recognize the change. This change is coming because of the cultural shift, because of the demography shift, but also very much so because of the technological shift.
STEPHEN KOTKIN: (00:42:55 – 00:42:55) Yes.
FEI-FEI LI: (00:42:56 – 00:43:36) So I think first of all, embracing this change is very, very important. Nothing pains me more today than seeing our teachers of K-12 education or even K-16 education are being left behind this change. That this dialogue of the technological civilizational change has not reached the entire country of teachers and parents.
And I think this is something I would love to push for more change. Where would this change come from? A healthy ecosystem.
STEPHEN KOTKIN: (00:43:37 – 00:43:37) Yes.
FEI-FEI LI: (00:43:37 – 00:43:40) A healthy ecosystem of talent creation.
STEPHEN KOTKIN: (00:43:41 – 00:43:41) Yes.
FEI-FEI LI: (00:43:41 – 00:45:03) A healthy ecosystem of public discourse, a healthy ecosystem of incentivization. So at Stanford, as the co-director of HAI, I’ve been talking to, going to Washington, D.C. with Condi often to talk about the need to resource our public sector and academia in the moment of change, because this is where public goods are produced.
And the public goods in today’s age means the talents as well as work that’s pursuit of truth, whether it’s scientific innovation, discovery for cancer, or predictive models of the economic change, the job change, the change of societal structures.
So I think there’s a lot more work that we as a society need to do. And I do worry as an educator and a technologist today that our society is not necessarily responding to this change in the most optimal way.
Adaptation, Immigration, and Inventing the Future
STEPHEN KOTKIN: (00:45:03 – 00:46:45) It’s a big one, the importance of being able to manage change, adaptability, flexible structures, that kind of nimbleness that comes from good institutions that are created with a set of values and a purpose but then have to perform in different circumstances that weren’t imaginable when they were first set up, right?
Our country citizenship was exclusionary in practice, even though it was universal in principle. And it took a long time and a lot of struggle for the universalism in principle to become universalism in practice.
But you touched on the cultural dimension. We’re open to the world. We have flourished. We’ve succeeded as a society because of our connections to the rest of the world. We’ve been both welcoming and unwelcoming to people from elsewhere during various periods of our history.
We’re about 48 million foreign-born right now in the United States, which is about a fifth or so of the population. That is to say, we have 48 million people who were born elsewhere. You’re one of those 48 million. The rest of us are descended either from immigrants or from slaves. Even the Native Americans were not originally from here.
And so in a way, we’ve had to adapt from the get-go. There’s been no way around this, and our ability to adapt is really make or break for our success. And these 48 million people born elsewhere who are now part of our country— San Francisco has the oldest Chinatown.
FEI-FEI LI: (00:46:45 – 00:46:47) Yes, in all of America, not very far from here.
STEPHEN KOTKIN: (00:46:48 – 00:46:50) Right outside the door dating from 1850.
FEI-FEI LI: (00:46:50 – 00:46:51) Yep.
STEPHEN KOTKIN: (00:46:51 – 00:47:16) And so this is a story that we’ve been down before and the need to assimilate and adapt. If we’re going to be open to the world, we have to actually be open to the world. Maybe it’s difficult. Maybe we have backlash. Maybe there are legitimate debates about scale and methods for entering the country. But you’re talking about technological adaptation as well. As cultural adaptation.
FEI-FEI LI: (00:47:16 – 00:48:42) I’m talking about all levels of adaptation because they’re all interconnected, right? Technology and scientific revolution 500 or 400 years ago led to the whole period of economical, cultural, political change that now we call Enlightenment period.
I believe that we’re in a bigger cycle of change because this wave of technology and science is even more profound. It goes directly into the human cognitive— cognition layer. And it changes work in profound ways. It changes learning in profound ways. It changes communication, starting with the internet and the social media.
We’re just compounding major changes technologically and scientifically. And that means downstream of that is cultural, political, economical change. And as a country and a world, we have to recognize that and bring people along and recognize that the change technology might give us improved productivity, but improved productivity absolutely does not guarantee shared prosperity, right? And all this, we need to recognize that it’s a test.
STEPHEN KOTKIN: (00:48:42 – 00:49:01) It’s a test of who we are and where we’ve come from and where we’re going. It’s also an opportunity, yeah, to seize and to shape, right? The future is yet to be invented. We can wonder about what the future might look like, but we can also invent it ourselves.
FEI-FEI LI: (00:49:01 – 00:49:03) Yeah, I mean, that’s what America is about.
STEPHEN KOTKIN: (00:49:04 – 00:49:04) Exactly.
FEI-FEI LI: (00:49:04 – 00:49:12) Is opportunity and future and how we can build towards that.
STEPHEN KOTKIN: (00:49:13 – 00:49:52) We need to seize the future again and a sense of the future and a sense of possibility and feel ownership and agency as you’ve expressed over that future. The future is to be invented. It’s plural and it’s ours to invent and it’s our students to invent and it’s our co-founders at enterprises like this, and it’s the children that we raise and the students that we teach, and it’s everybody that we touch.
And in turn, it’s everybody who comes here. Yeah, from elsewhere to help us do that, because that’s how we got to where we are today.
FEI-FEI LI: (00:49:52 – 00:49:53) Yeah, agreed.
STEPHEN KOTKIN: (00:49:54 – 00:49:57) That was really remarkable conversation. Thank you so much for your time.
FEI-FEI LI: (00:49:58 – 00:49:58) Thank you.
STEPHEN KOTKIN: (00:49:58 – 00:50:03) It’s really special to discuss America and “Only in America” with you.
FEI-FEI LI: (00:50:04 – 00:50:04) Thank you.
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