Daniela Amodei, Co-Founder and President of Anthropic: Building AI the Right Way

Daniela, welcome to Stanford and View from the top. Thank you so much for having me. We're so excited to hear to be with you here today. As you can see, we have a full house. And I want to start by asking everyone in the audience, please raise your hand if you're a user of clouds. — OH, WOW. [screaming] OKAY. BUT I FEEL LIKE if you had Sam Alman visit and you asked about chat GBT, would you all have raised your hands? Like let's be real. Okay. Still, you have a very supportive crown down here.

And you and your brother helped build one of the most important AI companies in the world. Yet neither of you grew up planning for any of this. Your background is in the arts. You studied English literature. And you your early career was in politics. Can you share more about what was your original career plan? — Oh my god. First of all, so nice of you to use the word plan in there. Um, I don't know that I necessarily would have described it that way at any point in time, but I I really think, you know, this is sort of a story that I hear from a lot of people who either wind up, you know, founding a company or just doing something a little bit unexpected or unconventional with their life. It was following what was most interesting to me at the time and the intersection of what was I good at, what was I interested in, and what was going to have a big impact in the world. So for me, I think coming out of college that looked like, by the way, I graduated in 2009, which was like not the most fun year to be a graduate. You were like, I have a literature degree and no skills. Who will hire me? Um, but at the time, I felt this very strong pull towards wanting to make the world better. I think that was always a sort of defining feature of both me and Daario from a young age. And where that started out for me was in international development working in global health. And I think my desire there was really to figure out like how do we build a world that is you know fair where everybody has access to basic things like food and water and medicine. And even though that's, you know, not what I directly work on now, I think that early grounding sort of gave me this foundation for thinking about how do you do good in the world, right? How do you build something that is of consequence and has a real purpose behind where you're spending, you know, 50 or 60 of your hours per week, right? What you're working on. Um, and so it was kind of a winding journey from there. I worked on Capitol Hill after that. I worked on a campaign. Uh, and eventually I ended up coming back to Silicon Valley. I am originally from San Francisco and started uh working at Stripe, which was this tiny company that at the time like nobody had heard of. My friends on Capitol Hill were like, "You're leaving to go do what? Payments. " Like now it looks like a great decision, but at the time it's about 40 people. Um and then from there things really just snowballed into working at OpenAI and then co-founding Anthropic. — You've moved across fields without being constrained by what you studied or had done before. Where does that mindset come from that your background doesn't have to define your next move? So, you know, it's really interesting. I think in some ways I really think of myself as a generalist, right? That if you were sort of look through my background, you would be like, what is this lady actually good at, right? She doesn't have a law degree. She's not a computer scientist. But I think this concept that um the ability to be curious and learn across a lot of disciplines, to have a strong foundation of wanting to have impact regardless of the area that you're working on, I think that is I think that's an underrated quality. And I see it a lot in the people that we hire at Anthropic and the really talented people that I've worked with in the technology industry more broadly. People who are curious and smart and they want to learn be helpful. That is like the first of all the description of like every role except for like engineer at a startup like you're like it's like what you know whatever people are like I have this degree I have that degree and those are sort of the qualities that you're looking for. But I think for me it was always very it was very interest and impact driven. So, I was like, "Okay, there's something that feels really wrong to me about the fact that, you know, I was born in America. I had access to um all of the sort of basic things that we take for granted in life. " Some people around the world just weren't they just that's just not where they were born. That's not what they were born into. Um how do I make that more fair? Like, how do we make that better as a broader community of the world? Um and from there, I was like, I'm just not having the level of impact that I want to. I need some skills. And so I went and I worked on a campaign and I was like, "Wow, a small number of people that work really hard who are young and driven can really change the world. " Not that surprising that eventually that led me to Silicon Valley where you're like, "You can do that. " But um it turns out that at a startup you have a lot more money and it's a lot easier going than the kind of 80 hours a week of working on a campaign. But I think those kind of core qualities around um you know really following your passion because you just want to do more when you care about the thing that you're working on either intellectually or from an implicit sense of meaning.

— And your career in AI started when you joined OpenAI in 2018 when it was still a relatively small research lab. Suddenly you were in rooms where people were talking about neural networks and transformers and scaling laws. How did you learn to speak that language? So I think I was well trained on two dimensions. I think the first is I had already spent um almost six years at Stripe and so I had worked with a lot of engineers. Obviously research and engineering are different but I think there was some overlap and some grounding. Um the second is that you know I grew up with a very talented uh technologyoriented physicist uh who's my sibling and obviously my co-founder at Anthropic among five others who are also all engineers or researchers. Um, but I think the number one thing I would say is both of those experiences just instilled in me this sense to just not be afraid of technology, right? It was ultimately it's a set of skills that are really highly prized I think but is something that anybody can learn and the sort of basics behind it I think the the terminology and the jargon can feel overwhelming at first but if you just ask enough questions and if you have people who are kind enough to be patient with you which I had in my life I was very lucky for that um you I just kept asking questions until I felt like I could understand it um and I think you know the second part of it was also just like knowing my lane and their lane. So, there were a lot of things that uh that the researchers I was like I probably couldn't have trained GP I certainly couldn't have trained GPT2 or GPT3, but like I brought things to the table that they didn't know how to do as well. And so, I really think understanding what your comparative advantage is and knowing how you fit into the broader ecosystem. Um that takes a lot of skills that are kind of interpersonal. Um curiosity I think is a very inherent skill, but one that you can learn and train. And I think all of those sort of put together really put me in this position to be able to be successful in that type of role.

— And in December of 2020, you, your brother, along with a group of colleagues left OpenAI. Why did you and Dario decide to start on topic? You take a big sip of water for that one. — Take your time. — I'll take one more actually. So, um, there were seven of us that originally left, me and Dario and our five co-founders, and then a number of people that kind of came over shortly thereafter. And I think for us it really came down to just the focus on what it was we really wanted the ultimate impact of the technology to be. And I think in our own, you know, very different ways. All seven of us are people that have a lot of integrity. We're people who care a lot about the impact of what it is that we build. And I think eventually it felt like it was just easier for us to sort of create the type of vision that we saw outside of the company we were in and in a new company. And I frequently say because I'm I know it'll shock you. I'm actually asked this question not infrequently. Um, and you know, we really, I think, were running towards something versus running away from something. Like we had this vision in our heads of wanting to create an organization where the values that mattered to us around safety, around responsibility um, were the kind of forefront of what we were doing. That's why we chose to incorporate as a public benefit corporation. That took a while to figure out what was the right kind of form factor to express. Look, we are going to be a commercial entity. We think there's lot of economic value that's going to be created by artificial intelligence, but it's really important to us that we do this the right way. And I think that was something that kind of united the seven of us. We had all worked on a combination of both capabilities and safety and policy work when we were at OpenAI and it felt like it was just easier to kind of create this structure in a new form.

— And you're building Enthropic not only with your brother but with five other co-founders. Many of us here are about to choose co-founders for the first time and we all know how often that ends badly. What does it take to make it work? — So, you know, I think of myself as just extremely lucky. Like the seven of us, I think, are a very special group on a couple of dimensions. I think the first thing I would say is like the interpersonal relationships, I know this is going to sound not that surprising, matter a lot more than you think. Like how do you guys have conflict together? So for example, Dario and I have been fighting and getting over it for almost 40 years because he's my brother and like I used to steal his toys, right? So like we know how to work through conflict together and like there's no question like we will love each other at the end of that no matter what. Um, with our co-founders, it's like I've known Jared for like 15 years. I've known Chris for 15 years. Tom and Sam were roommates. Um, Jared and Sam worked together at Stanford when they were in their PhD program. So, there was this kind of long history. Um, both Dario and I actually managed all of the other co-founders and like I think they had either reported to one of us or both of us. I think the majority had reported to both of us at OpenAI. So, we already had this kind of existing structure and framework of like we knew how to give each other feedback. work together. We'd like understood like who we were as people. And I think the other really important thing is just making sure you have a very strong sense of what it is you're trying to do and that picture is the same. Like if you locked yourself and your co-founder in another room and you wrote down or drew a picture of like what it is you're trying to build, you're not going to walk out and like one has drawn a unicorn and the other has drawn a platypus, right? Like that's the type of situation where you think you're doing the same thing, but I think it just doesn't end well. — And I think for us, this kind of vision of what it is we wanted to build, in some ways we were lucky because we had been in an environment where we're like, oo, it's not quite this. We want to do this other thing, but we were like in the same zone already. So, we're sort of pre-selected for that level of interest. But I think really being able to like pressure test to the degree that you can like instead of like starting a company together, like go on vacation together. Just like see how that go, share a room with them. Be like, how did that go? Um, and if you're like, man, all I want to do is spend more time with you. Great. If you're like, really, I'm going to need a vacation to recover from my vacation. You just might it might be the wrong choice. — I want to circle back to what you just said a few moments ago. anthropic is

deeply associated with AI safety, but I want to make sure that everyone understands what that actually means. So, when you say AI safety, what do you mean? — Yeah, this is a great question and I think this is a term that's gotten like almost a little bit overloaded in the past few years because it's sort of um it's kind of a catch-all that I think has been uh reached for in a lot of contexts. But I think to us the kind of highest level of framing is just taking a form of like radical responsibility for the technology that we're developing and the analog that we often use or that we often point to is social media companies which like it's so invogue to like crap all over them in public now. So I'm going to do that. Um, but basically, you know, like if you imagine going back in time, I actually think developers who created these technology companies, they weren't like, I'm setting out to cause a pandemic of eating disorders for teenage girls, right? That was not their intention, but they were like, what are the metrics that I'm trying to optimize for, right? I'm trying to build a company. I would like to see rapid scale growth. Like, let's just build towards that. And there wasn't this sort of at the time it just wasn't necessary because we'd never seen something on the level of scale that we have seen today, how quickly these companies grew, how many people adopt uh the technology so quickly. But if you could imagine, you could go back in time and say like, wow, you're starting Facebook or Instagram or Snapchat or Twitter and you're like, what if I really tried to think through all of the ways that this could go wrong? like what if I could think about what all the unintended externalities are and like really just kind of tried in advance to like prevent some of those from happening. And it's a little bit unfair because in AI we've had this whole generation of technologies before us where they've like gotten to [ __ ] up and we've gotten to be like, haha, we're not going to do that thing again. But that is a huge privilege, right? We're able to say, okay, you guys made this mistake. We are not going to make that mistake this time, right? we're going to be careful and we're going to say how do we make sure to think about the other things that might not go wrong because we understand the technology better. Um h how can we imagine a world where like everything goes right but also a world where everything goes wrong and I think for us safety means like all of the big stuff. So preventing chemical and biological weapons from being developed using our technology which by the way they could have the potential to do. Um but also like cyber right cyber warfare there's we've been in the news a lot lately about our decision to not um you know release our mythos class model because of the potential for cyber warfare. There's also a lot of work that happens around things like user wellness child safety um a lot of misinformation election integrity work. This is not something new that we invented. We've been able to stand on the shoulders of previous safety and security teams who worked on this at some of the other most consequential technology companies in history and say how do we learn from you right how do we do this better is an AI safety company that also has to generate revenue how do you manage the tension between the two — we're asked this question a lot too and I think in general the two don't come into conflict as much as you would expect. — So what I would say is most businesses in particular, which is by the way the majority of our revenue comes from businesses, are not looking to have models that are unsafe, right? They're [snorts] not like, "Wow, we would love for Claude to hallucinate more or it would be great if um Claude just produced like harmful outputs when you're asking it a question. " And so I think until like pretty recently this these things were just like a 100% in alignment, right? You were like it's actually really good for business to be safe because businesses are correctly they're riskaverse, right? They're like we don't want AI technologies that are going to be super unpredictable or unreliable. That said, I think we're now entering an era where the capabilities of the models are developing so rapidly that the tension is about time. So it's not necessarily the case that the models can't do amazing things. It's just we don't fully understand at this stage and I think it will be more the case going forward like how serious are the risks? — What are all of the risks and how do we help mitigate them? That sometimes means that we take slightly unusual actions like we did with Project Glass Wing and say this new class of model um it would be great if we could just release this to all of our customers. they all would love to use it, but we're just not confident enough yet. Like, we need a little more time to do some of the work to make the models safer to use. Um, but that's uncomfortable, right? It's uncomfortable to say that to your customers, right? They're like, look, we all believe in cyber defense, but like I really want access to that model. And I think this is the place where we just come back to the mission, right? We say, okay, we understand that desire. We want to get this technology to you as quickly as possible, but it is irresponsible of us to release it until we are confident that all of the patching that needs to be done has been done.

— We can't deny that when it comes to AI, there's a lot of fear. Fear that AI means fewer jobs because of less need for human judgment. Is that fear valid? — I think this is actually a very complicated question. Um my sense is that this probably will not surprise people here. Um AI is going to change what types of jobs are available and [clears throat] people do. So today I think there are jobs that exist that did not exist five years ago because of AI. I also think there will be some jobs that will not exist in the future because of AI. But what we have seen so far today is that according to our economic index where we study like how are people actually using artificial intelligence technology right now it mostly looks like complimentary skills right so you have artificial intelligence as an enabler of work you don't have it as a replacer of work um except in a very vanishingly small number of cases which is mostly customer service sorry if you have to email Comcast, it will never be a human again, probably. Um, but I don't know that was actually different five years ago. So, um, I think in reality what I expect is like there will be a number of types of work that will feel a lot like they rhyme with a job that exists today, but they're not necessarily the same as a job that exists today. And I think we just don't know the shape of what all of that is, right? Today, I think the thing that's most talked about is coding, right? software developers. Um I always, you know, in business meetings, right, people will say to me like we're talking shop about Claude and then like twothirds of the way through the conversation like a CEO will kind of conspiratorally lean across the table and say, you know, my daughter is a sophomore at Stanford, like what should she study, right? Like she was going to be a CS major. Should she not major in computer science? And I think, you know, the truth is we don't know. But my guess is software developers will still exist, but like they won't write as much code, — right? Like a lot of what software developers do is much bigger than just hands- on keyboard. They're talking to product managers. They're working closely with customers. And I think the percentage of that work is going to expand. Um, and I think the sort of things that can be more easily done by AI that will contract, but my sense is that is going to create a very different um scope of what's possible. But what

needs to happen in education, leadership, society that people feel prepared and excited and not just anxious? So I think there's a few things here. Um I think the first one is we need to start and lead from a place of like humility and not knowing the answers but doing the research. And I think at anthropic something that we've always aimed to do is be as kind of radically transparent about all of this as we possibly can be. Right? We've always said, look, we don't have all the answers. We do need to study this so that we're able to tell people what we see coming. And I think, you know, sometimes fairly people can say like, wow, you guys are just this is like a lot of negativity, right? You're like, here's what we think might happen in the future. But I think it's more important that we start the conversation sooner because we don't want people to be caught off guard, right? We're publishing the economic index to say here's how people are using artificial intelligence today because we want people to have an understanding of like where do we think this is going. So I think that's step one is we have to actually all agree on what reality is to the degree that's possible. I think step two is you know we have to be creative and experimental at many different layers. So, how do we have artificial intelligence really be something that is a grounding and a unifying force for people outside of just like, oh, I'm using it at my kind of job, right? Which is really important. But I think in some ways we need to sort of be rethinking the paradigm of this connection between uh work and meaning and like social life like all of these things I think are going to look very different in the future and we need to practice. And then I think the third one which is really outside of the realm of what a technology company can do alone is this is going to become a social and political issue. People are going to care if it feels like their jobs are being displaced by AI. People are already care about this, right? It comes up in polling. People are like, I have anxiety about what artificial intelligence is going to mean for my future, for my kids' future, right? That CEO that's leaning across the table from me, it's not just them. And so I think there is a broader discussion that needs to happen at many different levels of government with civil society with

universities by the way to say like what does this mean where what is the type of world that we want to be able to build where artificial intelligence is capable of doing many of the things that humans do today. At the core it is all about adoption. Here at Stanford we live and breathe AI but Stanford and Silicon Valley are not the whole world. what currently hinders AI adoption outside of this bubble. — You know, I think this is a really great call out. Um, it's so interesting because it feels like, you know, certainly to us at Anthropic and I'm sure at Stanford too, it's like the only thing people want to talk about is AI. Certainly, to me about is AI, but that's probably a me problem. Um, but I think I think that feeling you're totally right that even in other parts of America, it's not it's not something that people are comfortable with yet on the whole and it's not even something that people like necessarily know how to use with very high fluency, right? So, you read these like really astounding, super impressive numbers about how many people are using AI tools. Um, but there's there's a demographic component to that, right? So it's generally people who are college educated, not uniquely. Uh it's more men than women. Um there's racial demographics involved. There's like um wealth demographics involved. And if you look around the world, it's really not equally distributed. And so I think what's interesting is that you pair that with some other data that we've collected, which is that people in developing countries are much more optimistic about AI than people in higher income countries. So the global south is almost universally like, wow, this is a huge opportunity for us, right? This is the moment where perhaps we could have an equalizing force that will make things more fair. But I think in the US and in Europe and in parts of Asia, people have a lot more anxiety. They're like, I like things the way they are. I don't want AI to come in and disrupt that. That doesn't sound as good to me. What do we do with this information? I have no idea. But I think it's really interesting to say like there are different questions of access and adoption around the technology and I think we are we are actually still very early in the game and that's the thing that I think can be missed in Silicon Valley in our bubble that we're like it's already everybody who's a software engineer is like I'm using cloud code I'm using codeex that is not the vast majority of developers in the world at large and so I think the the race is still like we're at like the gun just went off to start the race. And I think there's a lot of opportunity

to still positively shape how this technology is going to be used and developed, what access looks like, and just what the values that are baked into it are going to ultimately be. So, let's forward to the future where AI is far more widely adopted. What are the things we risk losing if we start delegating too much to AI? Yeah. Um, we did this very large qualitative survey at Anthropic. I think it's the largest qualitative study ever done that we know about. We talked to 81,000 people about their use of artificial intelligence. And so some of them were cloud users, users of other AI tools. Um, and what was interesting is, you know, people have a lot of different feelings about AI, right? And again, you know, cuts differently depending on where you are and what you do. But some people are like, I've never been able, you know, it enabled me to do things that I never thought I could do, right? I think for myself as an example, like I didn't think I could build a website, right? And now using Cloud, I'm like, "Oh man, that's so easy. " Like I just click a couple buttons and Cloud like built a website for me. What that would have taken me probably a year if I tried to do it by myself and it would not have been a very good website. Um, there's some people though who express a feeling of there's not like a specific term for it, but I think there might be or there might be in another language one day. Um, like I don't engage my brain because I don't have to. — Yeah. — So, it's not the same feeling as like scrolling on your phone, but it's like I could have reached for this idea. I could have thought through it, but it was so much easier to not do it and to just trust what the AI tool was giving me. And I think this is the source I actually believe of a lot of the anxiety around AI is humans like to I think have an inherent desire to learn, to be curious, to want to expand the aperture of things that they know about. And AI in some ways enables that, but if used incorrectly can sort of disable that, right? It's like I've done this sometimes, right? And I was like, "Oh, I could like look this up and figure it out myself, but I'll just ask an AI tool and then I'll blindly trust that what it says is correct. " It's not always correct, by the way. Sometimes Claude is wrong. Heretical to say, but a fact. Um, and I think I think the anxiety there is around how do we actually set some guard rails in place so that it's just it's not impossible to do that, but you actually have to really be trying to do it, right? Like I think some of the work that we do with universities is maybe an interesting microcosm for this. We have this concept of learning mode. Maybe some of you even use it. I don't know if we're at the GSP yet, but um faculty and professors and students like one version of this is like you put your homework in chat GPT. I'm going to use that one instead. And you're like, "Haha, it just gave me the answer. " There's a word for that. It's called cheating, right? and you're like, "That was great. " There's another version where you use Claude in learning mode — and you're like, "I don't I'm I I'm stuck, right? I'm trying to write this essay and I like there's something about the format that doesn't feel right to me. " And Claude is this sort of patient tutor. It's almost like you have an individualized professor who like knows you and understands like what you most want to learn and why this class is important to you. It's like, "Let me help get you unstuck, right? Do you want to go back and read this section together? Could we talk through this? I think that's the version where like these tools can make you smarter. They can make you um expand the set of things that you think you can learn. And then I think there's the version that's just turn your brain off. And I'm

hoping that as an industry we're going to choose to do the second versus the first. So if you had to prioritize what human skills most likely going to be more important in an AIdriven world. So I have my own views on this which is I think like we talked about a lot of specific like task oriented things right like I'm a financial analyst or I'm a developer or I'm a copy editor. um those jobs are going to change a lot and a lot of that work I think will be able to be done by AI tools. — But I think ultimately there's this very real phenomenon which is that humans like to be with other humans. We like to spend time together with each other. We like to um learn from be creative. We like to spend time understanding the other person. And we're social creatures, right? And I think I'm imagining that in a world where AI is able to do a lot more of the productive day-to-day work that we do, those skills are going to become a lot more important and much more prized because ultimately like if you're in a work environment and you're like, well, I could just ask Claude to like write a bunch of code for me. You are going to choose to talk to the developer that's going to explain to you like why something broke or why we chose to build, you know, a tool the way that we did. And I think sort of expanding this outside of the realm of just a technology industry, the example I often use is in medicine, right? Today, we hire doctors who are really good diagnosticians. We're like, "Hey, can you tell me what's wrong with me? I don't feel well. " And you're like basically paying this doctor to say like, "Here's a set of things that could be wrong with you. This is the one that's the most likely. Let me run some tests. " Guess what? AI is going to get really good at doing that. But the thing that an AI tool can't do is actually like look at you and examine you and also like help understand how you're feeling and help you feel better. Right? There's a reasonable body of medical literature that indicates that people have a good relationship with their doctor. They just like their doctor um have better clinical outcomes

than people who do not like their doctor. Like that's really hard to explain, but like what's probably going on? probably the doctor like tries a little bit harder to understand what's wrong with you. Maybe they run a set of tests that were unexpected. Um, and I think those skills, right, that bedside manner is going to be like five times more important in a world where you're not trying to cram that into one of seven things that you're looking for to make a doctor qualified to treat you. — And when you're thinking about the future, what AI use cases you're most personally excited about? — Oh man. Um I think for me personally um I mean I'm a career manager so I spend most of my time with people and we have this sort of I don't know again it's maybe one day there's going to be a word for it but there's this phenomenon where everybody thinks that AI is not going to come for their job because they're so special and I am extremely guilty of this. I was like people love people. People are going to want to report to me. They're not Claude obviously. Um, but I actually think Claude is incredibly powerful as a management coach and as a person to help you be a better leader. So I use Claude, we write performance reviews at Anthropic and I've uploaded, you know, a lot of the people that I work with have reported to me for like, you know, three or four years. So in general, it's like you're the same person, they're the same person. You give them feedback, but like how much has really changed like in the past six months? But I think Claude has been really powerful in helping me to spot patterns about somebody. Um, so if you, you know, more data is better, but if you look back over the course of three to four years of time of working with somebody and you're like, wow, you know, you guys have been circling around like this topical issue for the past three to four years, like maybe they need some additional coaching. Um, or maybe they need somebody sort of outside of you. It's just the type of thing that I think tends to get missed because you're just in it dayto-day. — And in the opposite direction, Claude is great at giving you feedback. So, like I have I upload all of my reports upward feedback for me. And sometimes Claude will kind of very kindly be like, "It sounds like you haven't improved on this in the past year. Like maybe you should get some extra coaching, Daniela. " Um, but I think those I think Claude's ability to kind of coach and help people be the best versions of themselves. I think there's a version of that makes sense in the workplace, uh, in people's personal lives that I think could be done kind of, you know, quite carefully, but that I think could be really powerful. Um, and then the second is I have two little kids. So, I have a almost 5-year-old and almost one-year-old. And I have to tell you, number one, best thing Claude has ever done is help me through potty training. Um, that was not a fun experience. And Claude made it just like a little bit, it was empathetic, like very actionable. There were some diagrams I don't need to tell you guys, but um, it was really, really useful. And I think Claude's ability to help in particular um overwhelmed parents is going to be really powerful because there's so much bad information. It's like every time you Google is something wrong with your kid, the answer is yes. And I think

Claude is a lot more measured and like can be interactive in a way that I think is really helpful. Danielle, before we turn to student questions, when you think about the next generation of AI leaders and builders who are with us here today in this room, what's the one thing you hope they take from your journey? — I would say, can I do two? Go ahead. Okay. Um, I would say the first is it sounds so trite and so I almost like I almost won't say it but I truly think like following something that you really care about something that you are passionate about is the most important thing you can do. Um, there are so many great ideas and if you don't feel the sort of like burning feeling of like this is a thing that needs to exist in the world and I I will just run through walls to be able to do it. Um, it's just it matters for the times when like it's not fun and when it sucks. Like you just have to be able to say like I remember why this matters to me. I remember why it's important whether it's to me personally or it's because of a type of change that I want to see happen in the world. There will be time there certainly have been anthropic times where we were like this is not the most fun part, right? there are parts that are tough and so being able to relate it back to why you decided to do this in the first place and why it matters to you I think is so important. And then the second I would say is I think for you know this generation in particular and I think really in the past you know 5 to 10 years this concept that like being in business doesn't have to be in tension with doing good. I think that is very that is a very new idea and I think it is really special and I have been so impressed at the sort of generation of um founders and you know just like creators who are thinking in that way right like there's this kind of marriage of um innovation and social impact I think Stanford has always been exceptional at this but I think that is a very new concept and I think there's like more appetite for it today, right? I think there can sort of be this feeling of like only the kind of like mean sucky people can like build a business. I just don't think that's true. And I think um increasingly I feel that the desire to do good is a strong it's a strong correlate with actually doing well. — Let's turn to the students. — Hi Daniela, my name is Brandon. I'm a

secondy year MBA student here. Thank you for joining us. There's a debate about whether we're in an AI bubble, and people usually mean three different things when they say that. Company valuations, how much companies are spending on infrastructure, or whether the pace of AI progress is actually sustainable. Which of those three are you most worried about, and which do you think people are most wrong about? — That's a great question. Um, yeah, we need like different like we need like air bubbles and glass bubble. They're very different. I see what you're saying. Um, I think I think the one that probably I don't know if I would say I'm the most worried about, but I think is is a is valid as a concern about this industry in general is it is a high capital expenditure business and that inherently brings some risks along with it. Um, this is probably stuff you all already know, but it is really expensive to train these models. It takes a lot of compute and that compute is in scarce supply and when you put those things together, like there's a lot of demand, there's not a lot of supply. I'm not an economics professor, but I think that means the price goes up. Um and so so the compute that is sort of the lifeblood of these companies um you have to buy really far in advance. And so you're essentially making a bet on the future. You're like we think we're going to need this much compute at this period of time. That's a really big expenditure to make. And like it is a little bit harrowing to work at any of these companies. I think if someone doesn't tell you that maybe with the exception of Google because they have they're public company have so much money but I think certainly for anthropic for open AI like you're kind of making a calculated bet that you're going to be able to pay that money back over time. Um we obviously are very bullish on this. I think the revenue from both of those companies is like unbelievable. It's something that I think you know we hear all the time like venture capitalist nothing like this has ever happened before right? It's impossible to imagine a business, you know, getting to the kind of revenue numbers that are being talked about on such a short time scale. And if that ever were to change, there would be a problem, right? Both of these companies have bought a lot of compute for the future. It's very expensive. And so, I think that is probably the risk that feels um it's not crazy to be worried about that. We obviously think um we're in a very good position. I think the industry as a whole is um but that could change any time. And I think it's important to remember that like this ultimately a bet, right? It's ultimately the industry thinking, hey, this is going to have a lot of returns to it. But like we could absolutely be wrong. — Hi Daniela, I'm Yash MBA student. Uh my question is what does Enthropic believe is the right balance between government

regulation and AI innovation and what do you wish governments around the world were doing differently? — Great question. Um, so I think this is an area where um I think the conversation about it has been, you know, sadly as sort of is the case I think today just in the sort of political climate. It's like hard to have a nuanced discussion and I think that's a shame because I think it is a really nuanced question. I think sensible regulation will need to be part of the story for artificial intelligence, right? It's a very different technology than any other technology that's ever been built before and even the last generation of technologies probably could have benefited from slightly more regulation in my personal opinion. Um that being said, we're not blind to the fact that like you need to have some room to maneuver as a company to be able to try things if you want to come up with the next generation of incredible products that people want to use and that are adopted. And I think this is one of these things that my actual most kind of critical hope for the conversation is that it doesn't become politicized, which I fear it already has, right? It's sort of like, oh, like regulation bad, innovation good, or innovation bad, regulation good. I think it's just really complicated. Um, I think there are areas of regulation that just don't make a lot of sense. And then I think there are areas of regulation that are absolutely critical to make the technology be developed in a way that is good for people and that will prevent bad things from happening to the people that rely on it every day and to the broader world. My hope is that in an ideal world what that would look like is technology companies and regulators like working hand in hand because we have the information about how the technology can be abused because we see it every day, right? We have safeguards teams and security teams that look at like how are people poking on this and what are the actual risks, but regulators know how to provide a framework and a system that can actually be followed and enforced. And so maybe it's overly optimistic, but I still hold out hope that future's possible where I think the two sides can find common ground and say like how do

we ensure that we're able to develop the next, you know, amazing technology that doesn't even exist yet or the next company that's going to be like whatever the next Google or the next Meta. Um, but that we just put some common sense regulations in place that help protect people. — Hi Danielle, thanks for being here. My name's Jackie Kimmel. I'm an MSX student. My question is, AI is gaining access to increasingly sensitive personal data such as our health data. Uh, what do you think individuals should actually be doing to protect their privacy? I think this is also an excellent question. Um, you know, the first thing that I'll say is you would be surprised at how common of a use case it is to ask Claude medical questions. I think it's like one of our most common just casual use cases. People I use it all the time, right? I'm like, "This is wrong with my kid. this is wrong with me. Help me. I think there's two sides to this. I think the first is it's actually the company's jobs to use and protect your data with care. I think that's extremely important. Um I bluntly think like people should hold companies accountable for using their data carefully. um because it is very personal and I think for example our decision to not put ads in claude um is partly predicated on this belief that AI technology is just different right people have conversations with AI tools that are much more personal than even what you would put on an Instagram account or um on social media of any form. And so I think the first is like with that knowledge comes more responsibility for the technology companies to actually protect your data. Um the second is I think from a personal perspective like I don't know that I have the perfect answer. Um I can certainly tell you like a lot of people use it for medical questions. I would really think about safety from the perspective of like don't take the models on faith about medical things. Um, in my own experience, Claude has been right more often than my doctors about complex medical cases. And I would never do something without checking with a licensed medical professional. Right? We um we are very open about the fact that like the models make things up sometimes. They get confused. They don't know you. They can't examine you. Right? Just like I was saying on stage. So, I think like having some healthy skepticism is extremely correct. Um, but think of it as like if you had a friend who was a really good doctor who maybe wasn't a specialist. So, you're like, I'm seeing a specialist and I would like help kind of being guided in this conversation with my doctor. I think Claude is a great tool for that. Um, it's great for helping you think of like things that might be going on that you might not know. But I think my number one recommendation is please do not just do medical things that any I mean I know you are all too smart to do this but like any AI tool just says like go do X like look at it with some skepticism and actually talk to a professional.

— Thank you to the students and Daniela before we let you go we have to do our view from the top rapid fire tradition. — Love it. — Are you ready? — I'm so ready. — Okay let's go. What would you major in if you were back in college? — Can I if I say business, does that just get me out of this entirely? Um, what would I major in? I would probably major in literature again. I know that sounds crazy. I loved I like to read. Yeah. — What's your favorite thing about working with your brother? — Oh, um, Thanksgiving dinner. No, I'm — um I would say that we like know so much about each other and we're able to have like sometimes we're able to say things to each other that nobody else in the company can, right? Like sometimes we can get away with something that no one else feels like they could. — What about least favorite thing about working with your brother? — Um Thanksgiving dinner. Uh no. Um I think just like the um needing to also have separation between like our personal relationship and our work relationship. So we build in time every week when we hang out outside of the office. But I think it that's hard just that like we were siblings for a long time before we were co-founders. We will be siblings for a long time after we're co-founders. And making sure to just like continue to water that relationship outside of work. — Favorite book you found at the library in your office. — Ooh. Oh man. Um I don't know if I've discovered a new book, which maybe means I should get I was like, I like reading. Just kidding. Um I should probably go look more, but um I did I was reminded of a favorite book there. Maybe that counts. Um there's a book called The Guns of August. I don't know if there's any World War I like I'm not see I'm seeing some blank faces, so maybe not. It's a great book. If you're curious about World War I, um I picked it up from the library and actually reread it um because I read it I think maybe right after college or something, but I think it's a really important study of just like the individual people and personalities that resulted in and sort of led to um you know the beginnings of what became World War I and just how much like so many individual events and sort of people and personalities hinged on this like really ultimately sort of tragic and terrible thing that happened. So anyway, blanket shout out of read that book. It's great. — Amazing. And if Anthropic had ended up with a different name, what would it be? — Oh man. Um, wow. We went through some like truly tragic ideas before we came up with Anthropic. I think for some reason we were like very into birds at the time. We're like sparrow systems. I think no idea where that one came from. But um I think actually now that I'm remembering I think some of the like model names from the early days were all birds. So there was like Bert which then became like we had to snuff up against that's not a bird but like then anyway we had this kind of like bird thing. I don't know there were some terrible bird names. Thankfully better decisions prevailed and we named it anthropic which is now impossible to imagine is not our name. — Imagine. And finally not a rapid fire

question. Best advice you ever received? Drop the ant. No. Um, I'm trying to think of um, best advice I've ever received. I think probably, you know, I will say when we were thinking about leaving and it was it's now in retrospect people are like, of course you guys you all left and you found it anthropic. It didn't feel that way at the time. Yeah, — we were like, "This is a really, you know, this is kind of a crazy thing to do. Maybe we should stay. Maybe we could make this work. " Um, but we talked I talked to one, you know, sort of friend and mentor outside of work. And she was like, "Honestly, I don't think you really need to be on the phone with me. Like, you already know what the right answer is. " And I think that is I think in general like when you're in a moment of is this the right thing for my life often you actually know what the right answer is. Um and I think that was really good advice. — Daniela, it's been a pleasure. — Thank you. Thank you so much. — Thanks for having me.