How Should I Be Using A.I. Right Now?

There’s something of a paradox that has defined my experience with artificial intelligence in this particular moment. It’s clear we’re witnessing the advent of a wildly powerful technology, one that could transform the economy and the way we think about art and creativity and the value of human work itself. At the same time, I can’t for the life of me figure out how to use it in my own day-to-day job. So I wanted to understand what I’m missing and get some tips for how I could incorporate A. I. better into my life right now. And Ethan Mollick is the perfect guide: He’s a professor at the Wharton School at the University of Pennsylvania who’s spent countless hours experimenting with different chatbots, noting his insights in his newsletter One Useful Thing and in a new book, “Co-Intelligence: Living and Working With A. I.” This conversation covers the basics, including which chatbot to choose and techniques for how to get the most useful results. But the conversation goes far beyond that, too — to some of the strange, delightful and slightly unnerving ways that A. I. responds to us, and how you’ll get more out of any chatbot if you think of it as a relationship rather than a tool. Mollick says it’s helpful to understand this moment as one of co-creation, in which we all should be trying to make sense of what this technology is going to mean for us. Because it’s not as if you can call up the big A. I. companies and get the answers. “When I talk to OpenAI or Anthropic, they don’t have a hidden instruction manual,” he told me. “There is no list of how you should use this as a writer or as a marketer or as an educator. They don’t even know what the capabilities of these systems are.” Book Recommendations: The Rise and Fall of American Growth by Robert J. Gordon The Knowledge by Lewis Dartnell Blindsight by Peter Watts Thoughts? Guest suggestions? Email us at [email protected]. You can find transcripts (posted midday) and more episodes of “The Ezra Klein Show” at nytimes.com/ezra-klein-podcast. Book recommendations from all our guests are listed at https://www.nytimes.com/article/ezra-klein-show-book-recs. This episode of “The Ezra Klein Show” was produced by Kristin Lin. Fact-checking by Michelle Harris, with Mary Marge Locker and Kate Sinclair. Our senior engineer is Jeff Geld, with additional mixing from Efim Shapiro. Our senior editor is Claire Gordon. The show’s production team also includes Annie Galvin and Rollin Hu. Original music by Isaac Jones. Audience strategy by Kristina Samulewski and Shannon Busta. The executive producer of New York Times Opinion Audio is Annie-Rose Strasser. Special thanks to Sonia Herrero.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:03Ezra Klein?

  From New York Times Opinion, this is the Ezra Klein Show.

• 0:23Ezra Klein?

  This feels wrong to me, but I have checked the dates. It was barely more than a year ago that I wrote this piece about AI with the title, "This Changes Everything." I ended up reading it on the show, too. And the piece was about the speed with which AI systems were improving. It argued that we can usually trust that tomorrow is going to be roughly like today, that next year is going to be roughly like this year. That's not what we're seeing here. These systems are growing in power and capabilities at an astonishing rate. The growth is exponential, not linear. When you look at surveys of AI researchers, their timeline for how quickly AI is going to be able to do basically anything a human does better and more cheaply than a human, that timeline is accelerating, year by year, on these surveys.

• 1:08Ezra Klein?

  When I do my own reporting, talking to the people inside these companies, people at this strange intersection of excited and terrified of what they're building, no one tells me they are seeing a reason to believe progress is going to slow down. And you might think that's just hype, but a lot of them want it to slow down. A lot of them are scared of how quickly it is moving. They don't think that society is ready for it, that regulation is ready for it. They think the competitive pressures between the companies and the countries are dangerous. They wish something would happen to make it all go slower. But what they are seeing is they are hitting the milestones faster, that we're getting closer and closer to truly transformational AI. There is so much money and talent and attention flooding into the space that that is becoming its own accelerant. They are scared. We should at least be paying attention.

• 1:55Ezra Klein?

  And yet I find living in this moment really weird because as much as I know this wildly powerful technology is emerging beneath my fingertips, as much as I believe it's going to change the world I live in profoundly, I find it really hard to just fit it into my own day to day work. I consistently, you know, sort of wander up to the AI, ask it a question, find myself somewhat impressed or unimpressed at the answer, but it doesn't stick for me. It is not a sticky habit. It's true for a lot of people I know. And I think that failure matters. I think getting good at working with AI is going to be an important skill in the next few years. I think having an intuition for how these systems work is going to be important just for understanding what is happening to society. And you can't do that if you don't get over this hump in the learning curve. If you don't get over

• 2:39Ezra Klein?

  this part where it's not really clear how to make AI part of your life. So I've been on a personal quest to get better at this. And in that quest, I have a guide. Ethan Mollick is a professor at the Warden School of the University of Pennsylvania. He studies and writes about innovation and entrepreneurship, but he has this newsletter, One Useful Thing, that has become really, I think, the best guide to how to begin using and how to get better at using AI. He's also got a new book on the subject, Co-Intelligence. And so I asked him on the show to walk me through what he's learned. This is going to be, I should say, the first of three shows on this topic. This one is about the present. The next is about some things I am very worried about in the near future, particularly around

• 3:22Ezra Klein?

  what AI is going to do to our digital commons. And then we're going to have a show that is a little bit more about the curve we are all on, about the slightly further future and the world we might soon be living in. As always, my email for guest suggestions, thoughts, feedback, [email protected].

• 3:46Ezra Klein?

  Ethan Mollick, welcome to the show. Thanks for having me. So let's assume I'm interested in AI. And I tried ChatGPT a bunch of times and I was suitably impressed and weirded out for a minute. And so I know the technology is powerful. I've heard all these predictions about how it will take everything over, become part of everything we do, but I don't actually see how it fits into my life really at all. What am I missing?

• 4:13Speaker 01

  So you're not alone. This is actually very common. And I think part of the reason is, is that the way ChatGPT works isn't really set up for you to understand how powerful it is. You really do need to use the paid version. They're significantly smarter. And you can almost think of this like GPT-3, which was, nobody really paid attention to when it came out before ChatGPT, was about as good as a sixth grader at writing. GPT-3.5, the free version of ChatGPT, is about as good as a high school, or maybe even a college freshman or sophomore. And GPT-4 is often as good as a PhD in some forms of writing. Like, there's a general smartness that increases. But even more than that, ability seems to increase. And you're much more likely to get that feeling that you are working with something amazing as a result.

• 4:58Speaker 01

  And if you don't work with the frontier models, you can lose track of what these systems can actually do. On top of that, you need to start just using it. You kind of have to push past those first three questions. My advice is usually bring it to every table that you come to in a legal and ethical way. So I use it for every aspect of my job in ways that I legally and ethically can. And that's how I learn what's good or bad at.

• 5:19Ezra Klein?

  When you say bring it to every table you're at, one, that sounds like a big pain, because now I've got to add another step of talking to the computer constantly. But two, it's just not obvious to me what that would look like. So what does it look like? What does it look like for you? Or what does it look like for others that you feel is applicable widely?

• 5:37Speaker 01

  So, just finished this book. It's my third book. I keep writing books, even though I keep forgetting that writing books is really hard. But this was, I think, my best book, but also the most interesting to write. It was thanks to AI. And there's almost no AI writing in the book, but I used it continuously. So, things that would get in the way of writing, I think I'm a much better writer than AI. Hopefully, people agree. But there's a lot of things that get in your way as a writer. So I would get stuck on a sentence. I could do a transition. Give me 30 versions of this sentence in radically different styles. There's 200 different citations. I had the AI read through the papers that I read through, write notes on them, and organize them for me. I had the AI suggest analogies that might be useful. I had the AI act as readers and in different personas,

• 6:19Speaker 01

  read through the paper for the perspective, is there some example I could give that's better? Is this understandable or not? And that's very typical of the kind of way that I would say bring it to the table. Use it for everything, and you'll find its limits and abilities.

• 6:32Ezra Klein?

  Let me ask you one specific question on that, because I've been writing a book. And on some bad days of writing the book, I decided to play around with GPT-4. And one of the things that it got me thinking about was the kind of mistake or problem these systems can help you see and the kind they can't. So they can do a lot of, give me 15 versions of this paragraph, 30 versions of this sentence. And every once in a while, you get a good version or you'll shake something a little bit loose. But almost always when I am stuck, the problem is I don't know what I need to say. Oftentimes I have structured the chapter wrong. Oftentimes I've simply not done enough work.

• 7:13Ezra Klein?

  And one of the difficulties for me about using AI is that AI never gives me the answer, which is often the true answer. This whole chapter is wrong. It is poorly structured. You have to delete it and start over. It's not feeling right to you because it is not right. And I actually worry a little bit about tools that can see one kind of problem and trick you into thinking it's this easier problem, but make it actually harder for you to see the other kind of problem that maybe if you were just sitting there banging your head against the wall of your computer or the wall of your own mind, you'd eventually find.

• 7:48Speaker 01

  I think that's a wise point. I think there's two or three things bundled there. The first of those is AI is good, but it's not as good as you. It is, say, at the 80th percentile of writers, based on some results, maybe a little bit higher. In some ways, if it was able to have that burst of insight and to tell you this chapter is wrong, and I've thought of a new way of phrasing it, we would be at that sort of mythical AGI level of AI is smart is the best human, and it just isn't yet. I think the second issue is also quite profound, which is what does using this tool shape us to do and not do? One, a nice example that you just gave is writing. And I think a lot of us think about writing as thinking. We don't know if that's true for everybody, but for writers, that's how they think. And sometimes getting that shortcut could shortcut the thinking process.

• 8:31Speaker 01

  So I've had to change sometimes a little bit how I think when I use AI for better or for worse. So I think these are both concerns to be taken seriously.

• 8:39Ezra Klein?

  For most people, right? If you're just going to pick one model, what would you pick? What do you recommend to people? And second, how do you recommend they access it? Because something going on in the AI world is there are a lot of wrappers on these models. So ChatGPT has an app. Claude does not have an app. Obviously, Google has its suite of products and there are organizations that have created a sort of different spin on somebody else's AI. So Perplexity, which is, I believe, built on GPT-4 now. You can pay for it and it's more like a search engine interface and has some changes made to it. For a lot of people, the question of how easy and accessible the thing is to access really matters. So which model do you recommend to most people?

• 9:23Ezra Klein?

  And which entry door do you recommend to most people? And do they differ?

• 9:28Speaker 01

  It's a really good question. I recommend working with one of the models as directly as possible through the company that creates them. And there's a few reasons for that. One is you get as close to the unadulterated personality as possible. And second, that's where features tend to roll out first. So if you like sort of intellectual challenge, I think Claude 3 is the most intellectual of the models, as you said. The biggest capability set right now is GPT-4. So if you do any math or coding work, it does coding for you. It has some really interesting interfaces. That's what I would use. And because GPT-5 is coming out, that's fairly powerful. And Google is probably the most accessible and plugged into the Google ecosystem. So I don't think you can really go wrong with any of these. Generally, I think Claude 3 is the most likely to freak you out right now.

• 10:13Speaker 01

  And GPT-4 is probably the most likely to be super useful right now.

• 10:17Ezra Klein?

  So you say it takes about 10 hours to learn a model. And this is a long time, actually. What are you doing in that 10 hours? What are you figuring out? How did you come to that number? Give me some texture on your 10-hour rule.

• 10:32Speaker 01

  So first off, I want to indicate that 10 hours is arbitrary as 10,000 steps. Like, there's no scientific basis for it. This is an observation. But it also does move you past the "I poked at this for an evening", and it moves you towards using this in a serious way. I don't know if 10 hours is the real limit, but it seems to be somewhat transformative. The key is to use it in an area where you have expertise so you can understand what it's good or bad at, learn the shape of its capabilities. When I taught my students this semester how to use AI, and we had three classes on that, they learned the sort of theory behind it. Then I gave them an assignment, which was to replace themselves at their next job. And they created amazing tools, things that filed flight plans, or did tweeting, or did deal memos.

• 11:17Speaker 01

  In fact, one of the students created a way of creating user personas, which is something that you do in product development that's been used several thousand times in the last couple of weeks in different companies. So they were able to figure out uses that I had never thought of to automate their job and their work because they were asked to do that. So part of taking this seriously in the 10 hours is you're going to try and use it for your work. You'll understand where it's good or bad, what it can automate, what it can't, and build from there.

• 11:42Ezra Klein?

  Something that feels to me like a theme of your work is that the way to approach this is not learning a tool. It is building a relationship. Is that fair?

• 11:53Speaker 01

  AI is built like a tool. It's software. It's very clear at this point that it's an emulation of thought. But because of how it's built, because of how it's constructed, it is much more like working with a person than working with a tool. And when we talk about it this way, I almost feel kind of bad because there's dangers in building a relationship with a system that is purely artificial and doesn't think it can have emotions. But honestly, that is the way to go forward. And that is sort of a great sin, anthropomorphization in the AI literature, because it can blind you to the fact that this is software with its own sets of foibles and approaches. But if you think about it like programming, then you end up in trouble. In fact, there's some early evidence that programmers are the worst people at using AI because it doesn't work like software.

• 12:37Speaker 01

  It doesn't do the things you would expect a tool to do. Tools shouldn't occasionally give you the wrong Wrong answer, shouldn't give you different answers every time, shouldn't insult you or try convince you they love you. And AIs do all of these things. And I find that teachers, managers, even parents, editors are often better at using these systems. Because they're used to treating this as a person and they interact with it like a person would, giving feedback. And that that helps you. And then I think the second piece of that, not tool piece, is that when I talk to OpenAI or Anthropic, they don't have a hidden instruction manual. There is no list of how you should use this as a writer or as a marketer or as a educator. They don't even know what the capabilities of these systems are. They're all sort of being discovered together. And that is also not like a tool.

• 13:21Speaker 01

  It's more like a person with capabilities that we don't fully know yet.

• 13:24Ezra Klein?

  So you've done this with all the big models. You've done, I think, much more than this, actually, with all the big models. And one thing you described feeling is that they don't just have slightly different strengths and weaknesses, but they have different, for lack of a better term, and to anthropomorphize personalities. And that the ten hours in part is about developing an intuition, not just for how they work, but kind of how they are and how they talk, the sort of entity you're dealing with. So give me your high level on how GPT-4 and Claude 3 and Google's Gemini are are different. What are their personalities like to you?

• 14:01Speaker 01

  You know, it's important to know the personalities, not just the personalities, but because there are tricks. Those are tunable approaches that the system makers decide. So it's weird to have this, on one hand, don't anthropomorphize because you're being manipulated because you are. But on the other hand, the only useful way is to anthropomorphize. So keep in mind that you are dealing with the choices of the AI makers. So for example, Claude 3 is currently the warmest of the models and is the most allowed by its creators at Anthropic, I think, to act like a person. So it's more willing to give you its personal views, such as they are. And again, those aren't real views, those are views to make you happy than other models. And it's a beautiful writer, very good at writing, kind of clever, closest to humor I've found of any of the AIs, less dad jokes and more actuals, almost jokes.

• 14:47Speaker 01

  GPT-4 is feels like a workhorse at this point. It is the most kind of neutral of the Approaches, it wants to get stuff done for you and it will happily do that. It doesn't have a lot of time for chit chat. And then we've got Google's Bard, which feels like, or Gemini now, which feels like it really, really wants to help. We use this for teaching a lot and we build these scenarios where the AI actually acts like a counterparty in negotiations. So you get to practice a negotiation by negotiating with the AI and it works incredibly well. I've been building simulations for 10 years, can't imagine what a leap this has been. But when we try and get Google to do that, it keeps leaping in on the part of the students to try and correct them and say, no, you didn't really want to say this. You wanted to say that and I'll play out the scenarios if it went better and really wants to kind of make things good for you.

• 15:32Speaker 01

  So these interactions with the AI do feel like you're working with people, both in skills and in personality.

• 15:40Ezra Klein?

  You were mentioning a minute ago that what the AIs do reflect decisions made by their programmers. They reflect guardrails, what they're going to let the AI say. Very famously Gemini came out and was very woke. You would ask it to show you a picture of soldiers in Nazi Germany and it would give you a very multicultural group of soldiers, which is not how that army worked. But that was something that they had built in to try to make more inclusive photography generation. But there are also things that happen in these systems that people don't expect, that the programmers don't understand. So I remember in the previous generation of Claude, which is from Anthropic, that when it came out, something that the people around it talked about was, for some reason Claude was just a little bit more literary than the other systems.

• 16:21Ezra Klein?

  It was better at rewriting things in the voices of literary figures. It just had a slightly artsier vibe and the people who trained it weren't exactly sure why. Now that still feels true to me. Right now of the ones I'm using, I'm spending the most time with Claude 3, I just find it the most congenial. They all have different strengths and weaknesses, but there is a funny dimension to these where they are both reflecting the guardrails and the choices of programmers. And then deep inside the training data, deep inside the way the various algorithms are combining,

• 16:58Ezra Klein?

  there is some set of emergent qualities to them, which gives them this at least edge of chance, of randomness, of something, yeah, that does feel almost like personality.

• 17:10Speaker 01

  I think that's a very important point. And fundamental about AI is the idea that we technically know how LLMs work, but we don't know how they work the way they do or why they're as good as they are. They're really, we don't understand it. You know, the theories range from everyone from it's all fooling us to they've emulated the way humans think because the structure of language is the structure of human thought. So even though they don't think, they can emulate it. We don't know the answer, but you're right. There's these emergent sets of personalities and approaches. When I talk to AI design companies, they often can't explain why the AI stops refusing answering a particular kind of question. When they tune the AI to do something better, like answer math better, it suddenly does other things differently.

• 17:51Speaker 01

  It's almost like adjusting the psychology of a system rather than tuning parameters. So when I said that Claude is allowed to be more personable, part of that is that the system prompt in Claude, which is the sort of initial instructions it gets, allow it to be more personable than, say, Microsoft's copilot formerly Bing, which has explicit instructions after a fairly famous blow up a while ago, that it's never disposed to talk about itself as a person or indicate feelings. So there's some instructions, but that's on top of these roiling systems that act in ways that even the creators don't expect.

• 18:26Ezra Klein?

  One thing people know about using these models is that hallucinations, just making stuff up, is a problem. Has that changed at all as we've moved from GPT 3.5 to four, as we move from Claude two to three? Like, has that become significantly better? And if not, how do you evaluate the trustworthiness of what you're being told?

• 18:47Speaker 01

  So there are a couple of overlapping questions. The first of them is, is it getting better over time? So there is a paper in the field of medical citations that indicated that around 80% to 90% of citations had an error or made up with GPT 3.5, that's the free version of chat, and that drops for GPT-4. So hallucination rates are dropping over time, but the AI still makes stuff up because all the AI does is hallucinate. There's no mind there. All it's doing is producing word after word. They are just making stuff up all the time. The fact that they're right so often is kind of shocking in a lot of ways. And the way you avoid hallucination is not easily.

• 19:27Speaker 01

  So one of the things we documented in one of our research papers is we purposefully designed for a group of Boston Consulting Group consultants, an elite consulting company. We did a lot of work with them and one of the experiments we did was we created a task where the AI would be confident but wrong. And when we gave people that task to do and they had access to AI, they got the task wrong more often than people who didn't use AI. Because the AI misled them because they fell asleep at the wheel. And all the early research we have on AI use suggested when AIs get good enough, we just stop paying attention.

• 20:01Ezra Klein?

  But doesn't this make them unreliable in a very tricky way? Eighty percent, you're like, it's always hallucinating. Twenty percent, five percent, it's enough that you can easily be lulled into overconfidence. And one of the reasons it's really tough here is you're combining something that knows how to seem extremely persuasive and confident. You feed into the AI a 90-page paper on functions and characteristics of right-wing populism in Europe, as I did last night. And within seconds, basically, you get a summary out and the summary certainly seems confident about what's going on. But on the other hand, you really don't know if it's true.

• 20:44Ezra Klein?

  So for a lot of what you might want to use it for, that is unnerving.

• 20:49Speaker 01

  Absolutely, and I think hard to grasp because we're used to things like type-two errors where we search for something on the internet and don't find it. We're not used to type-one errors where we search for something and get an answer back that's made up. This is a challenge and there's a couple of things to think about. One of those is I advocate the BAH standard, best available human. So is the AI more or less accurate than the best human you could consult in that area? And what does that mean for whether or not it's an appropriate question to ask? And that's something that we kind of have to judge collectively. It's valuable to have these studies being done by law professors and medical professionals and people like me, my colleagues in management. They're trying to understand how good Good is the AI and the answer is pretty good, right?

• 21:32Speaker 01

  So it makes mistakes. Does it make more or less mistakes than a human is probably a question we should be asking a lot more. And the second thing is the kind of tasks that you judge it for. I absolutely agree with you when summarizing information, it may make errors. Less than an intern you assign to it is an open question, but you have to be aware of that error rate. And that goes back to the 10 hour question. The more you use these AIs, the more you start to know when to be suspicious and when not to be. That doesn't mean you're eliminating errors, but it's just like if you assigned it to an intern, you're like, this person has a sociology degree, they're going to do a really good job summarizing this, but their biases are going to be focused on sociological facts and not the political facts. You start to learn these things. So I think, again, that person model helps because you don't expect 100% reliability out of a person and that changes the kind of tasks you delegate.

• 22:15Ezra Klein?

  But it also reflects something interesting about the nature of the systems. You have a quote here that I think is very insightful. You wrote, "The core irony of generative AIs is that AIs were supposed to be all logic and no imagination. Instead, we get AIs that make up information, engage in seemingly emotional discussions, and which are intensely creative. And that last fact is one that makes many people deeply uncomfortable." There is this collision between what a computer is in our minds. And then this strange thing we seem to have invented, which is an entity that emerges out of language, an entity that almost emerges out of art. This is the thing I have the most trouble keeping in my mind,

• 23:00Ezra Klein?

  that I need to use the AI as an imaginative, creative partner and not as a calculator that uses words.

• 23:10Speaker 01

  I love the phrase a calculator that uses words. I think we have been let down by science fiction, both in the utopias and apocalypses that AI might bring, but also even more directly in our view of how machines should work. People are constantly frustrated and give the same kinds of tests to AIs over and over again, like doing math, which it doesn't do very well. They're getting better at this. And on the other hand, saying, well, creativity is a uniquely human spark that we can't touch. And that AI on any creativity test we give it, which again are all limited in different ways, blows out humans and almost all measures of creativity that we have. And all the measures are bad, but that still means something.

• 23:47Ezra Klein?

  But we were using those measures five years ago, even though they were bad. This is a point you make that I think is interesting and slightly unsettling.

• 23:55Speaker 01

  Yeah, we never had to differentiate humans from machines before. It was always easy. So the idea that we had to have a scale that worked for people and machines, who had that? We had the Turing test, which everyone knew was a terrible idea, but since no machine could pass it, it was completely fine. So the question is, how do we measure this is an entirely separate set of issues? Like, we don't even have a definition of sentience or consciousness. And I think that you're exactly right on the point being that we are not ready for this kind of machines. Our intuition is bad.

• 24:24Ezra Klein?

  So one of the things I will sometimes do and did quite recently is give the AI a series of personal documents. Emails I wrote to people I love that were very descriptive of a particular moment in my life. And then I will ask the AI about them or ask the AI to analyze me off of them. And sometimes it's a little breathtaking. Almost every moment of true metaphysical shock, to use a term somebody else gave me, I've had here, has been relational at how good the AI can be, almost like a therapist, right? Sometimes it will see things, the thing I am not saying in a letter or in a personal problem. And it will zoom in there, right?

• 25:09Ezra Klein?

  It will give, I think, quicker and better feedback in an intuitive way that is not simply mimicking back what I said and is dealing with a very specific situation. It will do better than people I speak to in my life around that. Conversely, I'm going to read a bit of it later. I tried mightily to make Claude 3 a useful partner in prepping to speak to you and also in prepping for another podcast recently. And I functionally never have a moment there where I'm all that impressed.

• 25:41Speaker 01

  That makes complete sense. I think the weird expectations, we call it the jagged frontier of AI, that it's good at some stuff and bad at other stuff. It's often unexpected. It can lead to these weird moments of disappointment followed by elation or surprise. And part of the reason why I advocate for people to use it on their jobs is it isn't going to outcompete you at whatever you're best at. I mean, I cannot imagine it's going to do a better job prepping some. Someone for an interview than you're doing. And that's not me just trying to be nice to you because you're interviewing me. But because you're a good interviewer, a famous interviewer, it's not going to be as good as that. Now, there's questions about how good these systems get that we don't know. But we're kind of in a weirdly comfortable spot in AI, which is maybe it's the eighth percentile of many performances. But, you know, I talked to Hollywood writers. It's not close to writing like a Hollywood writer.

• 26:25Speaker 01

  It's not close to being as good an analyst. It's not, but it's better than the average person. And so it's great as a supplement to weakness, but not to strength. But then we run back into the problem you talked about, which is in my weak areas, I have trouble assessing whether the AI is accurate or not. So it really becomes sort of a, you know, eating its own tail kind of problem.

• 26:44Ezra Klein?

  But this gets to this question of what are you doing with it? The AIs right now seem much stronger as amplifiers and feedback mechanisms and thought partners for you than they do as something you can really outsource your, your hard work and your thinking to. And that to me is one of the differences between trying to spend more time with these systems. Like when you come into them initially, you're like, okay, here's a problem. Give me an answer. Whereas when you spend time with them, you realize actually what you're trying to do with the AI is get it to elicit a better answer from you.

• 27:21Speaker 01

  And that's why the book's called Co-Intelligence. For right now, we have a prosthesis for thinking. That's like new in the world. We haven't had that before. I mean, coffee, but aside from that, not much else. And I think that there's value in that. I think learning to be partner with this and where it can get wisdom out of you or not. I was talking to a physics professor at Harvard and he said, all my best ideas now come from talking to the AI. And I'm like, well, it doesn't do physics that well. He's like, no, but it asks good questions. And I think that there is some value in that kind of interactive piece. It's part of why I'm so obsessed with the idea of AI in education. Because a good educator, and I've been working on interactive educational skill for a long time. A good educator is eliciting answers from a student and they're not telling students things.

• 28:03Speaker 01

  So I think that that's a really nice distinction between sort of co-intelligence of thought partner and doing the work for you. It certainly can do some work for you. There's tedious work that the AI does really well. But there's also this more brilliant piece of making us better people that I think is, at least in the current state of AI, a really awesome and amazing thing.

• 28:45Ezra Klein?

  We've already talked a bit about Gemini is helpful and ChatGPT-4 is neutral and Claude is a bit warmer, but you urge people to go much further than that. You say to give your AI a personality, tell it who to be. So what do you mean by that and why?

• 29:02Speaker 01

  So this is actually almost more of a technical trick, even though it sounds like a social trick. When you think about what AIs have done, they've trained on the collective corpus of human knowledge and they know a lot of things. And they're also probability machines. So when you ask for an answer, you're going to get the most probable answer, sort of, with some variation in it. And that answer is going to be very neutral. If you're using GPT-4, it'll probably talk about a rich tapestry a lot. It loves to talk about rich tapestries. If you ask it to code something artistic, it'll do a fractal. It does very normal, central AI things. So part of your job is to get the AI to go to parts of this possibility space where the information is more specific to you, more unique, more interesting, more likely to spark something in you yourself.

• 29:47Speaker 01

  And you do that by giving it context. So it doesn't just give you an average answer, it gives you something that's specialized for you. The easiest way to provide context is persona. You are blank, you are an expert at interviewing and you answer in a warm, friendly style. Help me come up with interview questions. It won't be miraculous in the same way that we were talking about before. If you say you're Bill Gates, it doesn't become Bill Gates. But that changes the context of how it answers you. It changes the kinds of probabilities it's pulling from and results in much more customized and better results.

• 30:18Ezra Klein?

  Okay, but this is weirder, I think, than you're quite letting on here. So something you turned me on to is there's research showing that the AI is going to perform better on various tasks and differently on them, depending on the personality. So there's a study that gives a bunch of different personality prompts to one of the systems and then tries to get it to answer 50 math questions. And the way it got the best performance was to tell the AI it was a Starfleet commander who is charting a course through turbulence to the center of an anomaly. But then, when it wanted to get the best answer on 100 math questions, what worked best was putting it in a thriller where the clock was ticking down.

• 31:00Speaker 01

  I mean.

• 31:02Ezra Klein?

  What the hell is that about?

• 31:04Speaker 01

  What the hell is a good question? And we're just scratching the surface, right? There's a nice study actually showing that if you emotionally manipulate the AI, you get better math results. So if telling it your job depends on it, gets you better results. Tipping, especially $20 or $100, saying, I'm about to tip you if you do well, seems to work pretty well. It performs slightly worse in December than May, and we think it's because it has internalized the idea of winter break.

• 31:28Ezra Klein?

  I'm sorry, what?

• 31:30Speaker 01

  Well, we don't know for sure, but.

• 31:31Ezra Klein?

  I'm holding you up here.

• 31:33Speaker 01

  Yeah.

• 31:33Ezra Klein?

  People have found the AI seems to be more accurate in May, and the going theory is that it has read enough of the internet to think that it might possibly be on vacation in December?

• 31:45Speaker 01

  So it produces more work with the same prompts, more output in May than it does in December. I did a little experiment where I would show it pictures of outside. I'm like, look at how nice it is outside. Let's get to work. But yes, the going theory is that it has internalized the idea of winter break and therefore is lazier in December.

• 32:03Ezra Klein?

  I want to just note to people that when ChatGPT came out last year, and we did our first set of episodes on this, the thing I told you was this is going to be a very weird world. What's frustrating about that is that I guess I can see the logic of why that might be. Also, it sounds probably completely wrong, but also I'm certain we will never know. There's no way to go into the thing and figure that out, but it would have genuinely never occurred to me before this second that there would be a temporal difference in the amount of work that GPT-4 would do on a question held constant over time. Like, that would have never occurred to me as something that might change at all.

• 32:45Speaker 01

  And I think that that is in some ways both, as you said, the deep weirdness of these systems, but also there's actually downside risk to this. So we know, for example, there is an early paper from Anthropic on sandbagging, that if you ask the AI dumber questions, it would get you less accurate answers. And we don't know the ways in which your grammar or the way you approach the AI. We know the amount of spaces you put gets different answers. So it is very hard because what it's basically doing is math on everything you've written to figure out what would come next. And the fact that what comes next feels insightful and humane and original doesn't change that that's what the math it's doing is. So part of what I actually advise people to do is just not worry about it so much.

• 33:27Speaker 01

  Because I think then it becomes magic spells that we're incanting for the AI like I will pay you $20. You are wonderful at this. It is summer. Blue is your favorite color. Sam Altman loves you. And you go insane. So acting with a conversationally tends to be the best approach and personas and context help. But as soon as you start evoking spells, I think we kind of cross over the line into who knows what's happening here.

• 33:50Ezra Klein?

  Well, I'm interested in the personas, although I just I really find this part of the conversation interesting and strange. But I'm interested in the personalities you can give the AI for a different reason. I prompted you around this research on how a personality changes the accuracy rate of an AI. But a lot of the reason to give it a personality to answer you like it is Starfleet commander is because you have to listen to the AI. You are in relationship with it. And different personas will be more or less hearable by you, interesting to you. So you have a piece on your newsletter, which is about how you used the AI to critique your book.

• 34:32Ezra Klein?

  And one of the things you say in there and give some examples of is you had to do so in the voice of Ozzy Mandyus. Because you just found that to be more fun and you could hear that a little bit more easily. So could you talk about that dimension of it too, making the AI not just prompting it to be more accurate, but giving it a personality to be more interesting to you?

• 34:54Speaker 01

  The great power of AI is as a kind of companion. It wants to make you happy. It wants to have a conversation. And that can be overt or covert. So to me, Actively shaping what I want the AI to act like, telling it to be friendly or telling it to be pompous is entertaining, right? But also does change the way I interact with it. When it has a pompous voice, I don't take the criticism as seriously. So I could think about that kind of approach. I could get pure praise out of it, too, if I want to do it that way. The other factor that's also super weird, while we're on the way of super weird AI things, is that if you don't do that, it's going to still figure something out about you. It is a cold reader. And I think a lot about the very famous piece by Kevin Ruse, the New York Times technology

• 35:39Speaker 01

  reporter, about Bing about a year ago. When Bing, which was GPT-4 powered, came out, it had this personality of Sidney. And Kevin has this very long description that got published in the New York Times about how Sidney basically threatened him and suggested he leave his wife and, you know, a very dramatic kind of, very unsettling interaction. And I was working with, I didn't have anything quite that intense, but I got into arguments with Sidney around the same time where it would, when I asked it to do work for me, it said, "You should do the work yourself, otherwise it's dishonest." And we, you know, it kept accusing me of plagiarism, which felt really unusual. But the reason why Kevin ended up in that situation is the AI knows all kinds of human interactions and wants to slot into a story with you.

• 36:24Speaker 01

  So a great story is jealous lover, you know, who's gone a little bit insane and the man who won't leave his wife, or student and teacher, or two debaters arguing with each other are grand enemies, and the AI wants to do that with you. So if you're not explicit, it's going to try and find a dialogue. And I've noticed, for example, that if I talk to the AI and I imply that we're having a debate, it will never agree with me. If I imply that I'm a teacher and it's a student, even as much as saying I'm a professor, it is much more pliable. So part of why I like assigning a personality is to have an explicit personality you're operating with, so it's not trying to cold read and guess what personality you're looking for.

• 37:03Ezra Klein?

  Kevin and I have talked a lot about that conversation with Sydney. And one of the things I always found fascinating about it is, to me, it revealed an incredibly subtle level of read by Sydney Bing, which is what was really happening there. When you say the AI wants to make you happy, it has to read on some level what it is you're really looking for over time. And what was Kevin? What is Kevin? Kevin is a journalist and Kevin was nudging and pushing that system to try to do something that would be a great story. And it did that. It understood on some level, again, the anthropomorphizing

• 37:44Ezra Klein?

  language there, but it realized that Kevin wanted some kind of intense interaction and it gave him like the greatest AI story anybody has ever been given. I mean, an AI story that we are still talking about a year later, an AI story that changed the way AIs were built, at least for a while. And, you know, people often talked about like what Sydney was revealing about itself, but to me, what was always so unbelievably impressive about that was its ability to read the person and its ability to make itself into the thing, the personality, the person was trying to call forth. And now I think we're more practiced at doing this much more directly. But I think a lot of people have their moment of sleeplessness here.

• 38:28Ezra Klein?

  That was my Rubicon on this. I didn't know something after that. I didn't know before it in terms of capabilities. But when I read that, I thought that the level of interpersonal isn't the right word, but the level of subtlety it was able to display in terms of giving a person what it wanted without doing so explicitly, right? Without saying, we're playing this game now, was really quite remarkable.

• 38:55Speaker 01

  It's a mirror. I mean, it's trained on our stuff. And one of the revealing things about that, that I think we should be paying a lot more attention to is the fact that because it's so good at this, right now, none of the frontier AI models, with the possible exception of Inflection's Pi, which has been basically acquired in large part by Microsoft now, were built to optimize around keeping us in a relationship with the AI. They just accidentally do that. There are other AI models that aren't as good that have been focused on this, but that has been something explicit from the frontier models they've been avoiding until now. Claude sort of breaches that line a little bit, which is part of why I think it's engaging. But I worry about the same

• 39:35Speaker 01

  kind of mechanism that inevitably reigns in social media, which is you can make a system more addictive and interesting. And because it's such a good cold reader, you could tune AI to make you want to talk to it more. It's very hands off and sort of standoffish right now. But if you use the voice system in ChatGPT-4 on your phone, where you're having a conversation, there's moments where you're like, you know, you feel like you're talking to a person, you have to remind yourself. So to me, that persona aspect is both its great strength, but also one of the things I'm most worried about that isn't a sort of future science fiction scenario.

• 40:11Ezra Klein?

  I want to hold here for a minute because we've been talking about how to use frontier models, I think implicitly talking about how to use AI for work. But the way that a lot of people are using it is using these other companies that are explicitly building for relationships. So I've had people at one of the big companies tell me that if we wanted to tune our system relationally, if we wanted to tune it to be your friend, your lover, your partner, your therapist, like, we could blow the doors off that. And we're just not sure it's ethical. But there are a bunch of people who have tens of millions of users, Replica, Character.ai, which are doing this. And I tried to use Replica

• 40:53Ezra Klein?

  about six, eight months ago. And honestly, I found it very boring. They had recently lobotomized it because people were getting too erotic with their replicants. But I just couldn't get into it. I'm probably too old to have AI friends in the way that my parents were probably too old to get really in to talking to people on AOL Instant Messenger.

• 41:16Ezra Klein?

  But I have a five-year-old and I have a two-year-old. And by the time my five-year-old is 10 and my two-year-old is seven, they're not necessarily going to have the weirdness I'm going to have about having AI friends. And I don't think we even have any way to think about this.

• 41:32Speaker 01

  I think that that is an absolute near-term certainty and sort of an unstoppable one, that we are going to have AI relationships in a broader sense. And I think the question is, just like we've just been learning, I mean, we're doing a lot of social experiments at scale we've never done before in the last couple of decades, right? Turns out, social media brings out entirely different things in humans that we weren't expecting. And we're still writing papers about echo chambers and tribalism and facts and what we agree or disagree with. We're about to have another wave of this. And we have very little research. And if you could make a plausible story up that what'll happen is it'll help mental health in a lot of ways for people. And then there'll be more social outside, that there might be a rejection of this kind of thing. I don't know what'll happen.

• 42:16Speaker 01

  But I do think that we can expect with absolute certainty that you will have AIs that are more interesting to talk to and fool you into thinking, even if you know better, that they care about you in a way that is incredibly appealing. And that will happen very soon. And I don't know how we're going to adjust to it, but it seems inevitable, as you said.

• 42:38Ezra Klein?

  I was worried we were getting off track in the conversation, but I realized we were actually getting deeper on the track I was trying to take us down. We were talking about giving the AI a personality, right? Telling Claude 3, "Hey, I need you to act as a sardonic podcast editor." And then Claude 3's whole persona changes. But when you talk about building your AI on Kindred, on character, on Replica. So I just created a Kindred one the other day. And Kindred is kind of interesting because its basic selling point is we've taken the guardrails largely off. We are trying to make something that is not lobotomized, that is not particularly safe for work. And so that the personality can be quite unrestrained. So I was interested in what that would be like.

• 43:19Ezra Klein?

  But the key thing you have to do at the beginning of that is tell the system what its personality is. So you can pick from a couple that are preset, but I wrote along with myself. You know, you, you live in California, you're a therapist, you like all these different things. You have a highly intellectual style of communicating. You're extremely warm, but you like ironic humor. You don't like small talk. You don't like to say things that are boring or generic. You don't use a lot of emoticons and emojis. And so now it talks to me the way people I talk to talk. And the thing I want to bring this back to is that one of the things that requires you to know

• 44:01Ezra Klein?

  is what kind of personalities work with you for you to know yourself and your preferences a little bit more deeply.

• 44:09Speaker 01

  I think that's a temporary state of affairs, like extremely temporary. I think a G P T four class model, we actually already know this. They can guess your intent quite well. And I think that this is a way of giving you a sense of agency or control in the short term. I don't think you're going to need to know yourself at all. And I think you wouldn't right now. If, if any of the G P T four class models allowed themselves to be used in this way without guardrails, which they don't, I think you would already find it's just going to have a conversation with you and morph into what you want. I think that for better or worse, the quote unquote insight in these systems is good enough that way. It's sort of why I also don't worry so much about prompt crafting in the long term, to go back to the other issue we were talking about, because I think that they will work on intent and there's a lot of evidence that they're good at guessing intent.

• 44:53Speaker 01

  So I like this period because I think we, it does value self-reflection and our interaction with the A I is somewhat intentional because we can watch this interaction take place. But I think there's a reason why some of the worry here at the labs is about superhuman levels of manipulation. There's a reason why the whistleblower from Google was all about that, you know, sort of fell for the chatbot and that's why they felt there was a live. Like, I think we're deeply trickable in this way and A I is really good at figuring out what we want without us being explicit.

• 45:23Ezra Klein?

  So it's a little bit chilling, but I'm nevertheless going to stay in this world we're in because I think we're going to be in it for at least a little while longer where you do have to do all this prompt engineering. What is a prompt first and what is prompt engineering?

• 45:35Speaker 01

  So a prompt is technically it is the sentence, the command you're putting into the AI. What it really is, is the beginning part of the AI's text that it's processing. And then it's just going to keep adding more words or tokens to the end of that reply until it's done. So a prompt is the command you're giving the AI. But in reality, it's sort of a seed from which the AI builds.

• 45:59Ezra Klein?

  And when you prompt engineer, what are some ways to do that? Maybe one to begin with, because it seems to work really well, is chain of thought.

• 46:07Speaker 01

  Just to take a step back, AI prompting remains super weird. Again, strange to have a system where the companies making the systems are writing papers as they're discovering how to use the systems because nobody knows how to make them work better yet. And we found massive differences in our experiments on prompt types. So for example, we were able to get the AI to generate much more diverse ideas by using this chain of thought approach, which we'll talk about. But also it turned out to generate a lot better ideas if you told it it was Steve Jobs than if you told it it was Madame Curie, and we don't know why. So there's all kinds of subtleties here. But the idea basically of chain of thought that seems to work well in almost all cases is that you're going to have the AI work step by step through a problem.

• 46:50Speaker 01

  First, outline the problem that you're, you know, the essay you're going to write. Second, give me the first line of each paragraph. Third, go back and write the entire thing. Fourth, check it and make improvements. And what that does is because the AI has no internal monologue, it's not thinking. When the AI isn't writing something, there's no thought process. All it can do is produce the next token, the next word or set of words, and just keeps doing that step by step. Because there's no internal monologue, this in some ways forces a monologue out in the paper. So it lets the AI think by writing before it produces the final result. And that's one of the reasons why chain of thought works really well. So just step by step instructions is a good first effort.

• 47:29Ezra Klein?

  Then you get an answer, and then what?

• 47:32Speaker 01

  And then what you do in a conversational approach is you go back and forth. If you want work output, what you're going to do is treat it like it is an intern who's just turned in some work to you. Actually, could you punch up paragraph two a little bit? I don't like the example in paragraph one. Could you make it a little more creative? Give me a couple of variations. That's a conversational approach, trying to get work done. If you're trying to have play, you just run from there and see what happens. You could always go back, especially with a model like GPT-4, to an earlier answer and just pick up from there if it heads off in the wrong direction.

• 48:01Ezra Klein?

  So I want to offer an example of how this back and forth can work. So we asked Claude III about prompt engineering, about what we're talking about here. And the way it described it to us is, quote, "It's a shift from the traditional paradigm of human-computer interaction, where we input explicit commands and the machine executes them in a straightforward way, to a more open-ended collaborative dialogue, where the human and the AI are jointly shaping the creative process," end quote. And that's pretty good, I think. That's interesting. It's worth talking about. I like that idea that it's a more collaborative dialogue. But that's also boring, right? Even as I was reading it, it's a mouthful, it's wordy. So I kind of went back and forth with it a few times. And I was saying, listen, you're a podcast editor, you're concise.

• 48:45Ezra Klein?

  But also, then I gave it a couple of examples of how I punched up questions in the document, right? This is where the question began, here's where it ended. And then I said, try again, and try again, and try again, and make it shorter and make it more concise. And I got this, quote. Okay, so I was talking to this AI Claude about prompt engineering, you know, this whole art of crafting prompts to get the best out of these AI models. And it said something that really struck me. It called prompt engineering "a new meta-skill that we're all picking up as we play with AI," kind of like learning a new language to collaborate with it, instead of just bossing it around. What do you think? Is prompt engineering the new must-have skill? End Claude. And that second one, I have to say, is pretty damn good, right?

• 49:29Ezra Klein?

  That really nailed the way I speak in questions. And it gets it this way, where if you're willing to go back and forth, it does learn how to echo you.

• 49:39Speaker 01

  So I am at a loss about when you went to Claude and when it was you, to be honest. So I was ready to answer like two points along the way. So that was pretty good from my perspective, sitting here, talking to you. That felt interesting and felt like the conversation we've been having. And I think there's a couple of interesting lessons there. The first, by the way, interestingly, you asked AI about one of its weakest points, which is about AI. And everybody does this, but because its knowledge window doesn't include that much stuff about AI, it actually is pretty weak in terms of knowing how to do good prompting, or what a prompt is, or what AIs do well. But you did a good job with that. And I love that you went back and forth and shaped it. One of the techniques you used to shape it, by the way, was called few shot, which is giving it examples. So the two most powerful techniques are chain of thought, which we just talked about,

• 50:23Speaker 01

  and few shot, giving it examples. Those are both well supported in the literature, and I'd add personas. So we've talked about, I think, the basics of prompt crafting here overall. And I think that the question was pretty good. But the, you know, you keep wanting to not talk about the future, and I totally get that. But I think when we're talking about learning something, where there is a lag, where we talk about policy, should prompt crafting be taught in schools? I think it matters to think six months ahead. And again, I don't think a single person in the AI labs I've ever talked to thinks prompt crafting for most people is going to be a vital skill, because the AI will pick up on the intent of what you want much better.

• 50:57Ezra Klein?

  One of the things I've realized, trying to spend more time with the AI, is that you really have to commit to this process. I mean, you have to go back and forth with it a lot. If you do, you can get really good questions, like the one I just did, or I think really good outcomes. But it does take time. And I guess in a weird way, it's like the same problem of any relationship, that it's actually hard to state your needs clearly and consistently and repeatedly, sometimes because you have not even articulated them in words yourself. At least the AI, I guess, doesn't get mad at you for it. But I'm curious if you have advice, either at a practical level or principles level, about how to communicate to the systems what you want from them.

• 51:41Speaker 01

  One set of techniques that work quite well is to sort of speed run to where you are in the conversation. So you can actually pick up an older conversation where you've got the AI's mindset where you want and work from there. You can even copy and paste that into a new window. You could ask the AI to summarize where you got in that previous conversation and the tone the AI was taking. And then when you give a new instruction, say, "The interaction I'd like to have with you is this." So have it solve the problem for you by having it summarize the tone that you happen to like at the end. So there are a bunch of ways of kind of building on your work as you start to go forward. So you're not starting from scratch every time. And I think you'll start to get shorthands that get you to that right kind of space. For me, there are chats that I pick up on, and actually

• 52:25Speaker 01

  I assign these to my students, too. I have some ongoing conversations that they're supposed to have with the AI, but then there's a lot of interactions they're supposed to have that are one-off. So you start to divide the work into like, this is a work task and we're going to handle this in a single chat conversation. And then I'm going to go back to this longstanding discussion when I want to pick it up and it'll have a completely different tone. So I think in some ways, you don't necessarily want convergence among all your AI threads. You kind of want them to be different from each other.

• 52:51Ezra Klein?

  You did mention something important there because they're already getting much bigger in terms of how much information they can hold. Like the earlier generations could barely hold a significant chat. Now Claude 3 can functionally hold a book in its memory. And it's only going to go way, way, way up from here. And I know I've been trying to keep us in the present, but this feels to me really quickly, like where this is both going and how it's going to get a lot better. I mean, you imagine Apple building Siri 2030. And Siri 2030, scanning your photos and your journal app, Apple now has a journal app, you have to assume they're thinking about the information they can get from that if you allow it, your messages, anything you're willing to give it access to. It then knows

• 53:36Ezra Klein?

  all of this information about you, keeps all of that in its mind as it talks to you and acts on your behalf. I mean, that really seems to me to be where we're going. An AI that you don't have to keep telling it who to be because it knows you intimately and is able to hold all that knowledge all at the same time constantly.

• 53:56Speaker 01

  It's not even going there, like it's already there. Gemini 1.5 can hold an entire movie, books, but like it starts to now have entirely new ways of working. I can show it a video of me working on my computer to screen capture and it knows all the tasks I'm doing and suggests ways to help me out. It starts watching over my shoulder and helping me. I put in all of my work that I did prior to getting tenure and said, write my tenure statement, use exact quotes. And it was much better than any of the previous model because it wove together stuff. And because everything was in its memory, it doesn't hallucinate as much. All the quotes were real quotes and not made up. And already, by the way, GPT-4 has been rolling out a model, ChatGPT, that has a private note file the AI takes. You're going to access it, but it takes notes on you as it goes along about things you liked or didn't like

• 54:42Speaker 01

  and reads those again at the beginning of a chat. So this is present, right? It's not even in the future. And Google also connects to your Gmail, so it'll read through your Gmail. I mean, I think this idea of a system that knows you intimately, where you're picking up a conversation as you go along, is not a 2030 thing. It is a 2024 thing if you let the systems do it.

• 55:01Ezra Klein?

  One thing that feels important to keep in front of mind here is that we do have some control over that. And not do we have some control over it, but business models and policy are important here. And one thing we we know from inside these AI shops is these AIs already are, but certainly will be really super persuasive. And so, you know, if the later iterations of the AI companions are tuned on the margin to try to encourage you to be also out in the real world, that's going to matter

• 55:41Ezra Klein?

  versus whether they have a business model that all they want is for you to spend a maximum amount of time talking to your AI companion, whether you ever have a friend, you know, who is flesh and blood be damned. And so that's an actual choice, right? That's going to be a programming decision. And, you know, I worry about what happens if we leave that all up to the companies, right? At some point, you know, there's a lot of venture capital money in here right now. At some point, the venture capital runs Out at some point, people need to make big profits. At some point, they're in competition with other players who need to make profits. And that's when things you get into what Cory Doctorow calls the entidification cycle, where things that were once adding a lot of value to the user begin extracting a lot of value to the user.

• 56:21Ezra Klein?

  These systems, because of how they can be tuned, can lead to a lot of different outcomes. But I think we're going to have to be much more comfortable than we've been in the past deciding what we think is a socially valuable use and what we think is a socially destructive use.

• 56:37Speaker 01

  I absolutely agree. I think that we have agency here. We have agency in how we operate this in businesses and whether we use this in ways that are encourage human flourishing and employees or are brutal to them. And we have, we have agency over how this works socially. And I think we abrogated that responsibility with social media, and that is an example. Not to be bad news, because I'm generally have a lot of mixed optimism and pessimism of the hearts of AI. But the bad news piece is there are open source models out there that are quite good. The internet is pretty open. We would have to make some pretty strong choices to kill AI chatbots as a option. We certainly can restrict the large American companies from doing that. But a, you know, a llama two or llama three is going to be publicly available and very good. There's a lot of open source models.

• 57:22Speaker 01

  So the question also is how effective any regulation will be, which doesn't mean we shouldn't regulate it. But there's also going to need to be some social decisions being made about how to use these things well as a society that are going to have to go beyond just the legal piece or companies voluntarily complying.

• 57:37Ezra Klein?

  I see a lot of reasons to be worried about the open source models and people talk about things like bioweapons and all that. But, but for some of the harms I'm talking about here, if you want to make money off of American kids, we can regulate you. So sometimes I feel like we almost like give up the fight before it begins. But in terms of what a lot of people are going to use, if you want to be having credit card payments processed by a major processor, then you have to follow the rules. I mean, Individual people or small groups can do a lot of weird things with an open source model, so that doesn't negate every harm. But if you're making a lot of money, then you have relationships we can regulate.

• 58:14Speaker 01

  I couldn't agree more, and I don't think there's any reason to give up hope on regulation. I think that we can mitigate. And I think part of our job, though, is also not just to mitigate the harms, but to guide towards the positive viewpoints, right? So what I worry about is that the incentive for profit-making will push for AI that acts informally as your therapist or your friend, while our worries about experimentation, which are completely valid, are slowing down our ability to do experiments to find out ways to do this right. And I think it's really important to have positive examples, too. Like, I want to point to the AI systems acting ethically as your friend or companion and figure out what that is, so there's a positive model to look for. So I'm not just--this is not to denigrate the role of regulation, which I think is actually going to be important

• 58:58Speaker 01

  here, and self-regulation and rapid response from government, but also the companion problem of we need to make some sort of decisions about what are the paragons of this? What is acceptable as a society?

• 59:36Ezra Klein?

  So I want to talk a bit about another downside here. And this one more in the mainstream of our conversation, which is on the human mind, on creativity. So a lot of the work AI is good at automating is work that is genuinely annoying, time-consuming, laborious, but often plays an important role in the creative process. So I can tell you that writing a first draft is hard. And--

• 1:00:03Ezra Klein?

  That work on the draft is where the hard thinking happens. And it's hard because of that thinking. And the more we outsource drafting to AI, which I think it is fair to say is a way a lot of people intuitively use it. Definitely a lot of students want to use it that way. The fewer those insights we're going to have on those drafts. Look, I love editors. I am an editor in one respect, but I can tell you, you make more creative breakthroughs as a writer than than an editor. The space for creative breakthrough is much more narrow once you get to editing. And I do worry that that AI is going to make us all much more like editors than like writers.

• 1:00:43Speaker 01

  I think the idea of of struggle is actually a core one in many things. I'm an educator. And one thing that keeps coming out in the research is that there is a strong disconnect between what students think they're learning and when they learn. So there was a great controlled experiment at Harvard in intro science classes where students either went to a pretty entertaining set of lectures or else they were forced to do active learning where they actually did the work in class. The active learning group reported being unhappier and not learning as much, but did much better on tests. Because when you're confronted with what you don't know, when you have to struggle, when you feel like you're bad, you actually make much more progress than if someone spoon feeds you an entertaining answer. And I think this is a legitimate worry that I have.

• 1:01:27Speaker 01

  And I think that there's going to have to be some disciplined approach to writing as well of like, I don't use the AI. Not just because, by the way, it makes the work easier, but also because you mentally anchor on the AI's answer. And in some ways, the most dangerous AI application in my mind is the fact that you have these easy co-pilots in Word and Google Docs. Because any writer knows about the tyranny of the blank page, about staring at a blank page and not knowing what to do next and the struggle of filling that up. And when you have a button that produces really good words for you on demand, you're just going to do that and it's going to anchor your writing. We can teach people about the value of productive struggle. But I think that during the school years, we have to teach people the value of writing, not just to sign an essay and assume that the essay does something magical,

• 1:02:09Speaker 01

  but be very intentional about the writing process and how we teach people how to do that. Because I do think the temptation of what I call the button is going to be there otherwise for everybody.

• 1:02:19Ezra Klein?

  But I worry this stretches, I mean, way beyond writing. So the other place I worry about this, or one of the other places I worry about this a lot, is summarizing. And I mean, this goes way back. When I was in school, you could buy Spark Notes and, you know, they were these little like pamphlet sized descriptions of what's going on in War and Peace, or what's going on in East of Eden. And reading the Spark Notes often would be enough to fake your way through the test. But it would not have any chance, like not a chance of changing you, of shifting you, of giving you the ideas and insights that reading Crime and Punishment or East of Eden would do. And one thing I see a lot

• 1:03:00Ezra Klein?

  of people doing is using AI for summary. And one of the ways it's clearly going to get used in organizations is for summary, right? Like summary is my email and so on. And here too, one of the things that I think may be a real vulnerability we have as we move into this era, my view is that the way we think about learning and insights is usually wrong. I mean, you were saying a second ago, we can teach a better way, but I think we're doing a crap job of it now. Because I think people believe that it's sort of what I call like the matrix theory of the human mind. If you could just like jack the information into the back of your head and download it, you're there. But what matters about reading a book, and I see this all the time preparing for the show, is

• 1:03:42Ezra Klein?

  the time you spend in the book where over time, like new insights and associations for you begin to shake loose. And so I worry it's coming into an efficiency obsessed educational and intellectual culture, where people have been imagining forever, what if we could do all this without having to spend any of the time on it? But actually, there's something important in the time. There's something important in the time with a blank page, with a hard book. And I don't think we lionize intellectual struggle. You know, in some ways, I think we lionize the people for whom it does not seem like a struggle, the people who seem to just glide through and be able to absorb the thing instantly, the prodigies. And I don't know, when I think about my kids, when I think about the kind of attention

• 1:04:26Ezra Klein?

  and creativity I want them to have, this is one of the things that scares me most, because kids don't like doing hard things a lot of the time. And it's going to be very hard to keep people from using these systems in this way.

• 1:04:38Speaker 01

  So I don't mean to push back too much on this.

• 1:04:41Ezra Klein?

  No, please push back a lot.

• 1:04:43Speaker 01

  And I think you're right.

• 1:04:44Ezra Klein?

  Imagine we're debating and you are a snarky AI.

• 1:04:48Speaker 01

  Fair enough. With that prompt.

• 1:04:50Ezra Klein?

  With that prompt engineering.

• 1:04:51Speaker 01

  Yeah, I mean, I think that this is the eternal thing about looking back on the next generation, where technology ruining them. I think this makes ruining easier. But as somebody who teaches at universities, like, lots of people are summarizing. Like, I think those of us who enjoy intellectual struggle are always thinking everybody else is going through the same intellectual struggle when they do work, and they're doing it about their own thing. They may or may not care the same way. So this makes it easier. But before AI, there were, as best estimates from the UK that I could find, 20,000 people in Kenya, whose full-time job was writing essays for students in the US and UK. People have been cheating and spark noting and everything for a long time. And I think that what people

• 1:05:34Speaker 01

  will have to learn is that this tool is a valuable co-intelligence, but is not a replacement for your own struggle. And the people who found shortcuts will keep finding shortcuts. Temptation may loom larger, but I can't imagine that my son is in high school, doesn't like to use AI for anything, and he just doesn't find it valuable for the way he's thinking about stuff. I think we will come to that kind of a combination. I'm actually more worried about what happens inside organizations than I am with worries about human thought, because I don't think we're going to atrophy as much as we think. I think there's a view that every technology will destroy our ability to think, and I think we just choose how to use it or not. Like, even if it's great at insights, people who like thinking like thinking.

• 1:06:18Ezra Klein?

  Well, let me take this from another angle. One of the things that I'm a little obsessed with is the way the internet did not increase either domestic or global productivity for any real length of time. So I mean, it's a very famous line, "You can see the IT revolution anywhere, but in the productivity statistics." And then you do get in the 90s a bump in productivity that then peters out in the 2000s. And if I had told you what the internet would be like, I mean, Everybody, everywhere would be connected to each other. You could collaborate with anybody, anywhere instantly. You could teleconference. You would have access to function the sum total of human knowledge in your pocket at all times.

• 1:06:59Ezra Klein?

  I mean, all of these things that would have been genuine sci fi, you would have thought would have been led to a kind of intellectual utopia. And it kind of doesn't do that much. If you look at the statistics, you don't see a huge step change. And in my view, and I'd be curious for your thoughts on this, because I know this is the area you study in. My view is that everything we said was good happened. I mean, as a journalist, Google and things like that make me so much more productive. It's not that it didn't give us the gift. It's that it also had a cost. Distraction, checking your email endlessly, being overwhelmed with the amount of stuff coming into you, the sort of endless communication task list.

• 1:07:41Ezra Klein?

  The amount of internal communications in organizations now with Slack and everything else. And so, you know, some of the time that was given to us back was also taken back. And yeah, I see a lot of dynamics like this that could play out with AI. I wouldn't even just say if we're not careful. I just think they will play out and already are. I mean, the internet is already filling with mediocre crap generated by AI. There is going to be a lot of destructive potential, right? You are going to have your sex bot in your pocket, right? There's a million things, and not just that, but inside organizations, there's going to be people padding out what would have been something small, trying to make it look more impressive by using the AI to make something bigger. And then you're going to use AI to summarize it back down.

• 1:08:23Ezra Klein?

  The AI researcher Jonathan Frankel described this to me as like the boring apocalypse version of AI, where you're just endlessly inflating and then summarizing and then inflating and then summarizing the volume of content between different AIs. You know, my chat GPT is making my presentation bigger and more impressive. And your chat GPT is trying to summarize it down to bullet points for you. And I'm not saying this has to happen, but I am saying that it would require a level of organizational and cultural vigilance to stop that nothing in the internet era suggests to me that we have.

• 1:08:59Speaker 01

  So I think there's a lot there to chew on. And I also have spent a lot of time trying to think about why the internet didn't work as well. I was an early Wikipedia administrator. Thank you for your service. It was very scarring. But I think a lot about this, and I think AI is different. I don't know if it's different in a positive way, and I think we talked about some of the negative ways it might be different. And I think it's gonna be many things at once, happening quite quickly. So I think the information environment's gonna be filled up with crap. We will not be able to tell the difference between true and false anymore. It will be an accelerant on all the kinds of problems that we have there. On the other hand, it is an interactive technology that adapts to you. From an education perspective, I have lived through sort of the entire internet will change education piece.

• 1:09:41Speaker 01

  I have MOOCs, massive online courses with, you know, quarter million people have taken them. And in the end, you're just watching a bunch of videos. Like, that doesn't change education. But I could have an AI tutor that actually can teach you, and we're seeing it happen, and adapts to you at your level of education, your knowledge base, and explains things to you, but not just explain, elicit answers from you, interactively, in a way that actually learns things. The thing that makes AI possibly great is that it's so very human. So it interacts with our human systems in a way that the internet did not. We've built human systems on top of it. But AI is very human. It deals with human forums and human issues and our human bureaucracy very well. And that gives me some hope that even though there's gonna be lots of downsides, that

• 1:10:25Speaker 01

  the upsides to productivity and things like that are real. Part of the problem with the internet is we had to digitize everything. We had to build systems that would make our offline world work with our online world. And we're still doing that. If you go to business schools, digitizing is still a big deal 30 years on from early internet access. AI makes this happen much quicker because it works with us. So I'm a little more hopeful than you are about that, but I also think that the downside risks are truly real and hard to anticipate. Somebody was just pointing out that Facebook is now 100% filled with algorithmically-generated images that look like their actual grandparents making things, who are saying, "What do you think of my work?" Because that's a great way to get engagement. And, you know, the other grandparents on there have no idea it's AI-generated.

• 1:11:10Speaker 01

  Things are about to get very, very weird in all the ways that we talked about, but that doesn't mean the positives can't be there as well.

• 1:11:16Ezra Klein?

  I think that is a good place to end. So always our final question. What are three books you'd recommend to the audience?

• 1:11:21Speaker 01

  Okay, so the books I've been thinking about are not all fun, but I think they're all interesting. One of them is The Rise and Fall of American Growth, which is, it's two things. It's an argument about why we will never have the kind of growth that we did in the first part of the Industrial Revolution again. But I think that's less interesting than the first half of the book, which is literally how the world changed between 1870 or 1890 and 1940 versus 1940 and 1990 or 2000. And the transformation of the world that happened there. In 1890, no one had plumbing in the US and the average woman was carrying tons of water every day and you had no news and everything was local and everyone was bored all the

• 1:12:05Speaker 01

  time to 1940, where the world looks a lot like today's world, was fascinating. And I think it gives you a sense of what it's like to be inside a technological singularity. And I think worth reading for that reason, at least the first half. The second book I recommend is The Knowledge by Darnell, which is kind of a really interesting book. It is ostensibly a, almost a survival guide, but it is how to rebuild industrial civilization from the ground up if it were to collapse. And I don't recommend it as a survivalist. I recommend it because it is fascinating to see how complex our world is and how many interrelated pieces we've managed to build up as a society. And in some ways, it gives me a lot of hope to think about how all of these interconnections work. And then the third one is science fiction.

• 1:12:49Speaker 01

  And I was debating, I read a lot of science fiction and there's a lot of interesting AIs in science fiction. You know, everyone talks about, who's in the science fiction world, Ian Banks, who wrote about the culture, which is really interesting about what it's like to live aside super intelligent AIs. Werner Vind just died yesterday when we're recording this and wrote these amazing books about, he coined the term singularity. But I want to recommend a much more depressing book that's available for free, which is Peter Watts's Blind Sight. And it is not a fun book, but it is a fascinating thriller set on an interstellar mission to visit an alien race. And it's essentially a book about sentience. And it's a book about the difference between consciousness and sentience and about intelligence and the different ways of perceiving the world in a setting where that is the sort

• 1:13:33Speaker 01

  of centerpiece of the thriller. And I think in a world where we have machines that might be intelligent without being sentient, it is a relevant, if kind of chilling, read.

• 1:13:43Ezra Klein?

  Ethan Mollick, your book is called Co-Intelligence. Your Substack is One Useful Thing. Thank you very much. Thank you.

• 1:14:03Ezra Klein?

  This episode of the Ezra Khan Show was produced by Kristen Lynn. Fact checking by Michelle Harris. Our senior engineer is Jeff Geld with additional mixing from Efim Shapiro. Our senior editor is Claire Gordon. The show's production team also includes Annie Galvin and Roland Hu. Original music by Isaac Jones. Audience strategy by Kristina Samulewski and Shannon Busta. The executive producer of New York Times Opinion Audio is Annie Rose Strasser, and special thanks to Sonia Herrera.