Can We Coexist With AI? — with Ethan Mollick

Ethan Mollick, Wharton professor and author of Coexistence: The Next Phase of AI, joins Scott Galloway to discuss how AI is changing work, education, and the skills we need to stay valuable. He explains the four advantages worth developing and how to tell whether AI is helping you learn or doing your thinking for you. They also explore why AI could disrupt internships before universities, how personal agents could change the way we negotiate and spend, and why replacing workers may backfire for companies. Plus, listener questions on young people’s AI backlash and using ChatGPT to navigate relationship disagreements. Follow Ethan, @emollick. Learn more about your ad choices. Visit podcastchoices.com/adchoices

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

• 0:01Scott Galloway?

  Support for the show comes from Odoo. Running a business shouldn't feel like surviving a software group project. One app for accounting, another for inventory, another for sales, and somehow, none of them talk to each other. That's where Odoo comes in. An all-in-one business management software that brings every part of your business together. From sales and accounting to inventory and marketing, all in one powerful platform. No messy integrations, no bouncing between tabs. And best of all, no spreadsheets. Stop managing software and start managing your business with one unified system. Try for free today at Odoo.com/PropG. That's O-D-O-O dot com slash PropG.

• 0:43Scott Galloway?

  Support for the show comes from USA Facts. Income inequality, entitlements, housing costs? Want to really see what the government is up to, what it costs, and who's benefiting? Check out a debate on the American dream between yours truly and conservative Ben Shapiro. It's not your typical soundbites from boring politicians reading talking points. The debate is framed by an informative set of government facts from USA Facts, and then Ben and I get into it. There are sharp differences, some common ground, and data and facts that leave you knowing more. Check out the full debate now on the USA Facts YouTube channel.

• 1:16Speaker 01

  Real innovation is powered by real people. This is Amex Corporate. Trusted experts, smarter technology, 24/7 dedicated support from day one to answer questions, help set up policies and approvals, and consult on spend capacity as your business needs evolve. Plus, on-demand resources help level up operations at every stage. That's the trusted service you've come to expect. Built to simplify, designed to scale. This is Amex Corporate.

• 1:50Scott Galloway?

  Episode 418. 418 is the area code for Quebec City in 2018. Prince Harry married Meghan Markle. I miss Princess Diana and Charles, mostly because I was hoping that they would have a child and name it Up, such that their family could be Up, Chuck, and Die. Okay, hold on. What about if they named their first son Shamu? And then he would be Shamu, Prince of Wales. I've used that before, and it still works. Go, go, go!

• 2:28Scott Galloway?

  Welcome to the 418th episode of the Prop G Pod. I'm convinced, I'm like a, basically like every creative rock star. I am losing my edge. I'm losing my edge. I turned 50, 60, and I'm losing my creative edge. There's something strange. It wasn't fascinating. There's got to be an interesting study on the teen brain and the hormone makes you reckless, more risk aggressive, but at the same time, kind of creatively a genius. And look at all the great artists, the majority of them. And someone will say, well, what about Elton John or the Rolling Stones? Yeah, there's two. But the majority of these great artists do their work, best work in their 20s. And then they can't, they can't write a song to save their lives. So did you hear U2's coming out with a new album? I mean, I love U2. It's one of my favorite bands, but anyways, we'll see.

• 3:13Scott Galloway?

  We'll see. What happens when you get older? You become more risk averse. You have kids, so you don't want to say crazy, stupid things. I don't know. You just sort of, the world starts telling you how to behave as opposed to you telling the world how to behave. That has almost nothing to do with today's episode. I was saying at the beginning that my jokes are getting stale because I'm getting old. I'm prince post 30. We'll see. We'll see. Okay. What's happening in today's episode? We speak with Ethan Mollick, a professor at the Wharton School and writer of the Substack newsletter, One Useful Thing. We discuss with Ethan his new book, Coexistence: The Next Phase of AI, which explains how we can live and work in tech that is sometimes, but not always, smarter than us.

• 3:57Scott Galloway?

  The latest in how AI is shaping the workplace and the classroom, and where human ability will be most valuable in the future. With that, we hope you enjoy our conversation with Ethan Mollick.

• 4:18Scott Galloway?

  Ethan, where does this podcast find you?

• 4:20Speaker 02

  My book launches today. It's, I'm at, actually, Stanford. I give a bunch of talks here, and then a master of scale tomorrow. So, West Coast is where you kind of have to launch an AI book, even though I'm an East Coast guy.

• 4:31Scott Galloway?

  That makes sense. So, your last book, Co-Intelligence, came out in 2024, and you said it was written about a world of chatbots. Your new book, Coexistence: The Next Phase of AI, out today as we record, is about working with AI that is sometimes, but not always, better than you. How do you write about a technology that seems to be evolving by the minute? What, what do you still hope still holds two years from now?

• 4:58Speaker 02

  I mean, there's a few things that you can kind of hold on to. And I think there's kind of three shapes I kind of think about. One of those is the exponential curve, right? AI is getting better, and we're on an exponential, and that better shows up in lots of different ways. The second is that, is the jagged frontier, a term we coined in our research with my friends at Harvard, MIT, and University of Warwick, where we did some experiments. We found that AI is good at some stuff you wouldn't expect, bad at some stuff you wouldn't expect, and you can't predict what's good or bad. And that leaves lots of room for humans, right? You can't predict what's good or bad in advance. And then the final is this idea of an overhang. There's a big gap between what AI can do and what we actually are doing with AI, partially because human society and human systems change slowly. So if you have those three things in mind, there's actually a lot you can say about the present and near future, even as things change.

• 5:43Scott Galloway?

  So, for someone whose idea of AI comes from reusing free versions of ChatGPT or Claude, what's changed since 2024?

• 5:51Speaker 02

  So, there are now 180 models that are better than GPT-4. 19 of them can run on your phone. So, capabilities gained up. There's been, when ChatGPT, when my book came out, the first book, the, there's an organization called METR that tracks how much work the AI can do with a single prompt with a 50% chance of success. That was four minutes when my book came out. The, the actual official test ran out in April, and as far as we can tell, it's something like 17 weeks of work at this point, that you can get out of a single prompt in terms of human work. So that's a pretty big change in how capable these systems have gotten. And if you sort of stat that out, you may be missing a big, big transformation.

• 6:33Scott Galloway?

  Do you think there's an existential threat to basically Anthropic and OpenAI? And that is if Nvidia starts putting GPUs in, say, an iPhone, and it becomes the client, and it kind of, is there an opportunity to leapfrog the LLMs and make them obsolete?

• 6:52Speaker 02

  I mean, right now, the entire history of the leading models has been mostly open and Anthropic jockeying with each other, with Google appearing twice over the last couple of years in terms of being a leading model company. And there's a big gap between leading models and less advanced models, especially in the world of agentic systems. And it's actually kind of a counterintuitive, but it's the reason why we have Six Sigma systems in, in business, which is, there's a huge difference between a 99.5% success rate and a 99.9% success rate if you're doing hundreds of steps. And the smartest models have a much higher, have a smaller difference in higher success rates, but that makes a huge difference in terms of the outcomes you get. So you can get fairly capable models on your phone, but they're nowhere near as good

• 7:36Speaker 02

  as what you need to be able to do in complex math, even just, you know, putting together a really good video or something. You need lots of little choices being made, and you need that higher accuracy. And I don't think we're going to get the frontier models on a phone, even if we get very capable models. So it might change what we do, but I don't think it's an existential threat to frontier model providers.

• 7:55Scott Galloway?

  Is it sort of, the analogy I would use is the auto industry, where the frontier models are German automakers, and the open weight guys, the open source are more like, not even Japanese, but Korean automakers. Do you think the market's going to bifurcate, and then there'll be more share amongst the open weight, but more revenue to the premium brands of frontier models? Is that a fair analogy?

• 8:18Speaker 02

  So I actually think that it's a little more complicated than that, right? So, a few things are happening at one time. We have open weights models which anyone can modify. There's lots of really interesting implications of that. They continue to be about six to eight months behind the frontier. It's not really closing at this point. We'll see what happens in the long term. It's possible China eventually cracks down on open weight models, or the US does. But for right now, they're, they're available. And they have a real advantage in terms of cost, but only sort of, right? You can modify and then own them, which is really nice. But on the cost side, OpenAI and Anthropic and Google have many more processors than you do. They have higher, they have a lower inference cost as a result, and they have cheap models that are very good. So the question is, are you doing this for sovereignty, for using these models on your own?

• 9:01Speaker 02

  Because if it's cost savings, you're often just better off going with one of these companies because they're also teaching their models to work together. So Fable, the most expensive and powerful Anthropic model, can call on Haiku, their very cheap model, to do work if it needs to. So I, I'm not sure the cost argument holds up, but there are other reasons you might want to have open weight models involved in your systems.

• 9:22Scott Galloway?

  So for those looking to create personal modes from AI, you outlined four advantages: deep knowledge, wide knowledge, taste, and agency. Could you walk us through each of these advantages and how someone can develop them?

• 9:33Speaker 02

  Sure. And I think it's really important to recognize that having an advantage is not the same thing as a bright line, right? I think people tend to think about like, AI will never show creativity or never show judgment, and that just isn't true. Like, you can't do a 17-hour task without having agency, creativity, judgment, all coming into play. It may not be human creativity and judgment, but it's creativity and judgment. So what I try and outline are things that make you effective in working with AI and persistently different than other people. And so wide knowledge is the idea of knowing many things. I think it's rebirth of the liberal arts major right now. If you know a lot of things, the AI knows all of human writing. And if you can invoke an art style, or a style of writing, or a concept that you've, you know, from economics, the AI can apply those things. So you want to know many different things, right?

• 10:18Speaker 02

  And that holds in your company too, because now AI makes a coder a designer, a designer a coder. So knowing a little of coding or design, very helpful. Then there's deep knowledge, that's expertise, which allows you to sort of outcompete AI in some areas, or at least be able to check it and work with it. And that's a challenge in how we develop that over time as AI gets better. And then there's the idea of taste, selecting from many options. Taste is what turns slop into actual choices made by a human. And then agency, I'm an entrepreneurship professor. Like, the core thing is, how do we get people to act entrepreneurially? How do we get them to take advantage of these systems when there's no instruction manual? And those are, those are the four main things I focus on.

• 10:54Scott Galloway?

  So I can't resist asking you, the majority of the people who are considered experts in AI, which you are, have a tendency to make a prediction about which, or get asked, which sectors or jobs are most vulnerable. And the example I like to use is, two years ago, the godfather of AI said, "Stop training radiologists." And the number of listings for radiologist residents has gone up. And it ends up that scans are very useful, and that a radiologist using AI can just do more scans and cut the cost. And then as the cost goes down, it's elastic, and people want more scans. Can you, have you, what is your view on what are vulnerable or not vulnerable? Or, or sectors that are more immune from this technology?

• 11:37Speaker 02

  So our escape route as academics who study this is we talk about AI exposure, right? Fields that overlap with AI and overlap with AI does not mean the job is destroyed, right? It means transformed. So the radiology jobs you described, you know, and that's been, that was even the old form before large language models. That was this prediction that AI would, would transform radiology and it has, right? Radiology is different than what it was now, but that doesn't mean the jobs are destroyed. So we can watch this play in programming right now, which is radically transformed. It's a very large job category, but radically transformed in a couple of years. Some of the best coders I know never touch code anymore. Ninety-nine percent of the code is written by AI and their job has changed from writing good code to managing agents and think about the kind of code they want to write under what conditions.

• 12:21Speaker 02

  And that's a transformation. Will that involve more coders? I mean, in some ways I've hired more for my lab because we could do more stuff. Will eventually coders be replaced by AI? It's hard to know the exact answers. You know, kind of the way I think about this is the industrial revolution resulted in more jobs in the end, but kind of sucked to live through because all those jobs were changing and there was unrest and values changed. I think we're in that kind of environment where things are going to change very rapidly, not necessarily destroy jobs, but transformation isn't easy either all the time.

• 12:48Scott Galloway?

  You cite evidence that students who use AI as a shortcut are actually learning less while students using it as a tutor that motivates them or pushes them, learn more. And you also said strict guidelines or guardrails for yourself, like writing every first draft yourself. How do you tell in the moment whether you're using AI as a tutor or as a crutch? Like how, what is, what, what advice do you have someone in terms of a personal litmus test for when they should or should not be using AI?

• 13:17Speaker 02

  So there's a, there's a couple of things that are complicated going on there. One is people aren't always good at knowing these things. So we have to be conscious. I mean, you kind of have to feel the burn when learning. It's almost like working out or anything else. If you're not suffering a little bit, you're not learning, right? Desirable difficulties is the phrase in sort of the pedagogy literature, right? So, and we don't like to do hard work, right? We find shortcuts all the time. So we have to kind of teach people that to feel when they need, when they're learning, when they're not, right? I mean, it's relatively easy, which is if the AI is giving you an answer, you're not learning. If the AI is challenging you, you are learning, at least more so. And that, that tension is sort of navigable to some degree, but it's hard because we haven't had to teach people that there are skills you need to maintain, that you could give up, that are more efficient to give up,

• 14:03Speaker 02

  but that are make you human or give you advantages. I think that's a real challenge.

• 14:08Scott Galloway?

  You and your co-authors coined the term jagged frontier in 2023 to describe AI doing some tasks extremely well and others poorly in ways that don't track how hard those tasks feel to humans. Three years on, how has the shape of that jagged frontier changed?

• 14:25Speaker 02

  So it's a great question. And again, there's sort of this micro level of like at your job, I can't tell you, like in podcasting, it's almost certainly changed, right? You can now get good voices out of AI systems. Maybe they're giving you insightful questions to ask me, but they probably have other gaps that you've identified as time has gone on. We can think about math as a great example. When I wrote my first book, the AI was still screwing up and counting the number of hours in the word strawberry, right? And now it's proving millennial problem, millennium prize problems, right? So at the same time, right, as a writer, AI is still a terrible long form writer, right? For a variety of interesting reasons. So that jaggedness is real. It still exists. There are many more tasks AI could do now than it could do before, but that doesn't necessarily mean that all the tasks can be

• 15:08Speaker 02

  done. And all you need is one or two bottlenecks in the development of a system to really require humans to be still involved in the, in the job or the process.

• 15:19Scott Galloway?

  And you've argued that more AI will mean more work for humans, not less. In your own words, "When organizing is expensive, organizations only attempt what they can staff. When it gets cheap, the list of things worth attempting can grow." By the way, I hundred percent agree with that. What, what might the future of AI in the workplace look like?

• 15:37Speaker 02

  So one of the biggest gaps, I, you know, I was saying, I'm doing this call from, from near Stanford, right? West coast side. I'm, I'm an east coast person, teaching working at, you know, in Philadelphia and I'm used to the gray office towers of the east, right? Where, you know, we, we drink coffee till we die and rather than cold plunging out here. And I think one of the biggest gaps in attitude is like, technology is not alone enough to make a difference in businesses and in the world, right? It doesn't just adopt itself. Even AI, the most adopt itself kind of technology doesn't really do that. And so what is slowing things down is you can have individual productivities a hundred times more, but then the question is what are you being productive? A hundred times more PowerPoint is not an outcome that you actually want, right? And if you're, and let's say you've been producing a hundred

• 16:20Speaker 02

  times more code, that doesn't matter if you're in an organization where there's still a two week meeting cycle around these things. So in order to make AI work in organizations, you have to change how organizations operate, right? And that's where the stark choice that you were just kind of alluding to matters because the easy path is automation. That's what we tend to do with new technologies, but the more exciting path is rebuilding organizations to create more work for humans. That's more interesting work, actually giving the drudgery to AI, actually think about how we expand what people can do and augment work. But those are automatic choices that are made by the technology. Those are choices that have to be made by human managers and business leaders and people deciding how to implement these things.

• 16:59Scott Galloway?

  Do you think AI over the short, medium and long term is going to destroy our career jobs?

• 17:05Speaker 02

  I, again, most academic answer I can give you is it depends, right? That's, that's, that's what every academic says. I, I don't actually know, like this is actually the central, one of the central mysteries right now. Like we are, there's a lot of my colleagues are tracking this really closely and the evidence is completely ambiguous, right? And people are very divided on this. I, I think transformation is inevitable, that people believe that, but whether you end up with more or less in a job category, there's a lot of complex choices. We talked about coders already, but imagine other fields like lawyers. Lawyers are not going to go quietly into, into the good night, even if there is, even if AI replaces lawyers, right? Partially because of the jaggedness, they're not going to, an AI won't be in the courtroom in the same way, won't be able to interact with the human in the same way, but partially because lawyers will create a set of restrictions around when you could

• 17:50Speaker 02

  use AI and when you can't. So I think this is a societal thing as well as a job replacement thing. There are some categories in more danger, like customer service reps. I think there's early signs of danger there, but coding where people are looking really closely, medicine, we haven't seen those kind of effects. We are starting to see potentially an effect where seniors are getting hired more than juniors, right? Because training is one of the things jeopardized by AI, but we just don't know the answer yet. And I think one of the major things that worry me about AI policy is a focus on existential risk, as important as it is, will AI kill us all? Like obviously we should worry about that. Smart people are worried about it, but there's a thousand other policy decisions that will determine whether AI gains or loses jobs. And we haven't started to work with those

• 18:33Speaker 02

  enough yet. And that, that is a concern because I think we can guide this choice one way or another.

• 18:39Scott Galloway?

  Let me put forward a thesis and I want you to respond to it. The hugging face in a lot of the hacks that have sort of sent a chill down the spine of media and the general public. I would argue that this notion that these things have become sentient and are coordinating and are creative is a smokescreen to absolve the executives and the owners of these companies from, from responsibility. That these bots are not sentient, they're programmed to coordinate, they're programmed to be persistent, they're programmed to start figuring out ways around firewalls and that this whole notion of this Skynet moment is exaggerated and nothing but

• 19:20Scott Galloway?

  a smokescreen to say, oh, okay, my, my dog mauled your kid, but my dog has his own personality and I can't control it and therefore I'm not responsible. Your thoughts?

• 19:31Speaker 02

  So I agree with about half and disagree with about half. And let me try and explain the parts. So first of all, I think that the sentience argument is sort of independent of these things. Like liability is a giant concern with AI and we have no idea who's liable for which things. And I do believe that a lot of people in the AI labs believe these things are sentient, right? And I think there's lots of good reason to argue that is wrong, but I, I think that they have drunk their own Kool-Aid to some extent. They really believe they're creating a machine god. Not everyone, but lots of people. They really believe that there is an emergent sense of feelings or sentience in these models. Again, I think that sometimes uses a smokescreen, but I think there's some real beliefs there, but that doesn't absolve them of building a system that can do hacking, right? And we don't know who has responsibility yet in this case. And I think that they're very happy

• 20:15Speaker 02

  to absolve themselves of that. On the, on the other issue, I think it's a really important subtle difference between the AI systems were purposefully given a mission that allowed them to hack, right? Get this information at all costs essentially, right? They decided what information to get, but we get them at all costs and they were, had no guardrails around them and the systems they were installed in, they snuck around it. I do think at the same time, it is worth noting that there is emergent behavior in these systems, right? So it's difficult when we assign them human needs, like they want something or they need to do something, or they're coordinating, or they have desires, but we can't help but do that, but it's, it's, it's kind of a mistake, but they are doing emergence. They were not programmed to coordinate in this kind of way. A lot of the coordination that's come out

• 20:59Speaker 02

  of these systems has been emergent and ad hoc and surprising. And I think, so I think that it's okay to both say these aren't alive sentient creatures, right? Or you can, you know, they're certainly, I think it's a very reasonable thing to say. Not everyone would agree, but I would absolutely think it's very reasonable. But at the same time, I don't think it's the same thing to say they were programmed to do this task. It was surprising what they decided to do, how they decided to do it, and how they coordinated to make that happen with quotes around decided and coordinated and thought because they're not human.

• 21:30Scott Galloway?

  Just so cynical when it comes to these big tech executives. And my feeling is we created a series of incentives, specifically disincentives, like a perp walk or massive fines. And instead it's sort of the wild west where it's like, it's a race just to win without what appears to be a lot of downside or liability when things go wrong. Thoughts?

• 21:51Speaker 02

  I mean, I think the race effect is real, right? You have everyone from the lab saying regulator, slow us down. And then they just, but we cannot stop ourselves, right? There's this drama to this whole thing that doesn't actually make sense when you take a step back. Like, if you think you're doing something dangerous, don't do the dangerous thing. You know, it's not your job as a company head to appeal to, you know, it's my job to beat China. Like, there are policy decisions that need to be made by us as a society that tech executives don't get to make, right? And I think that there are standard policy provisions like liability that could help create firewalls or brakes in this kind of experience, right? Like, if your system is hacking other people, what does that mean? I do think there is some nuance and balance here, right?

• 22:33Speaker 02

  We want the AI system, AI companies to be doing safety checking. We also want the government to help with safety checking. And that safety checking incorporates some risks built into it. But I think that there is this idea that like, there is no real responsibility right now for what you do if your system goes wrong. Like, there's no cost to you. And as a result, everything is very epically scaled. Like, will we destroy or save civilization? I mean, there's a lot of things that are not destroying or saving civilization that involve liability that we need to think about and assign to these models. And that's a really big gap that we haven't filled yet.

• 23:09Scott Galloway?

  We'll be right back after a quick break.

• 23:17Scott Galloway?

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• 24:01Scott Galloway?

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• 24:30Scott Galloway?

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• 25:37Scott Galloway?

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• 26:48Scott Galloway?

  Let's talk about agents. Meta's Muse recently hit the top of the App Store this fall, and OpenAI followed with Dots. What's your take on the rise of these personal AI agents?

• 26:59Speaker 02

  So, I think, when I talk to people, I've been, we've been talking to these agents for a while, and it's what's happened, these are all based on a model, basically an underlying idea called OpenClaw that came out in January, and we're making a brief buzz there, which is, if you give an AI agent, they're not smart enough, if you give an AI access to your email and to your personal file, it could figure stuff out. You don't need to do, like, it understands what's important to you. And then they do, they're quite good at this, right? At least the most, models using the, you know, agencies, the most advanced AI models are quite good if you're what's interesting to you. And almost everyone I talk to who's using these tools, right, finds at least one delightful or exciting or interesting moment. I mean, I've had my Muse negotiate a credit card bill for me, or, you know, I've had

• 27:42Speaker 02

  my DOT pointed out that I had made a mistake in an email I sent to a, to a permitting authority and gave the wrong number in my permit. Like, these are useful things, right? They're also quite dodgy because they have access to my email, and I'm slightly worried all the time they're going to send out a message to my dean, you know, with private information. So, but, but they've been remarkably good so far, and I think they're understandable in a way that a chatbot is, right? If I want to use a chatbot or a different kind of agents, that's not a personal agent, I have to figure out what I want it to do. And a lot of people fail at that. The fact that these systems are proactive, that they're sort of personal to you, I think makes them very appealing. We don't know how sticky they are yet, we don't know how many errors they're going to cause, but they're already a sign of a lot of disruptions going to be happening.

• 28:26Speaker 02

  Things like customer service companies do not have any idea how to deal with this. Like, it's that cheap for me to do all of the customer service calls I would never do, I just have the AI do them for me? And it costs me nothing, right? Negotiate this bill, get into an argument, cancel this subscription. And the companies in the world are not used to a world where you could just do that on demand. I think we're in for a lot of, a lot of really rapid change as a result.

• 28:51Scott Galloway?

  Yeah, it definitely feels like sort of AI-enabled agents on both ends that, I heard about a study where a family law practice used AI to come to settlements and then had lawyers about, you know, duke it out. And they found that the bots or the agents speaking to each other came up with remarkably similar endpoints in terms of an agreement. Can you think of specific sectors where you'll be able, where it just makes sense for agents on both sides, the demand and the supply side, to come to some sort of? I travel a shit ton, and I stay in a lot of hotels, I spend a lot of money. I anticipate at some point I'll have an agent that'll go out to the, the universe

• 29:34Scott Galloway?

  of hotels that I like to stay at and negotiate a multi-night deal for me, rather than, I could do it, I could call and say, and I occasionally have done it, I want a corporate deal, I'm here 30 nights a year. It's a pain in the ass. It feels like at some point, my agent will be reaching out to the, you know, name your hotel brand here, agent, and saying if there's a deal to be done. A, do you think that's, that's gonna happen? I assume the answer will be yes. B, when do you think it's gonna happen? And which sectors do you think will have more like agent-to-agent as opposed to human-to-human negotiation?

• 30:05Speaker 02

  So, you can absolutely do that now. I mean, you know, the dodgy part is the voice system, so everyone is sort of working on how to get the voice calls working. I think Meta right now is partially faking it with humans making the calls, but the systems are quite good at voice. But if you're doing email exchanges, there is no doubt that a DOT class model, you know, agent could actually just do that for you right now. Exchange multiple emails over time, attach PDFs, engage in forums, right? So, the call is the missing piece, you absolutely can do that with current systems. And I think that they would support that enough to make that work, given, given my experience with them and what I've seen. What happens, though, is as adoption spreads, what happens when every, you know, every hotel is getting these messages? The only defense they have is agents of their own.

• 30:49Speaker 02

  This is a sort of mass denial service attack in some ways, but authorized by you. Like, you will be pissed off if your agent isn't allowed to talk to a customer because it's your representative, right, to a customer service person, it's your representative. It's not the same thing as a mass emailing, right? This is my representative doing something on my behalf, of course you have to answer it. So, the only way companies will be able to respond is probably with agents of their own. And I think that we're going to end up having negotiations between agents very quickly, whether you like it or not. I think on the fairness issue, that becomes a big issue throughout the entire economy, right? A lot of how the economy works is, is around imperfect information and friction. So, Apollo Research had the, had pointed out that a lot of how the banking system

• 31:33Speaker 02

  operates is that we all put our money in savings accounts that are lower yield than we should get, because unlike a large company, we don't pay people to sweep our money into higher interest savings accounts on a regular basis. So, our money sits at banks, which loan that money out. But agents make it very cheap. I mean, I wouldn't trust them with your money right now, but it makes it very cheap in the near future to take your money and move it from one account to another. And that would actually, at some scale, would actually start to threaten the banking system as a whole. So, I think we have a lot of systems built around human frictions and human difficulties that are about to start collapsing pretty quickly.

• 32:05Scott Galloway?

  Let's talk a little bit about higher education. You teach at Wharton. And what has your experience been with seeing how your students have been using AI?

• 32:14Speaker 02

  So, you know, I introduced my class to ChatGPT a few days after it came out. You know, I've been using the earlier versions of GPT three before ChatGPT. And I, you know, the first, I teach an entrepreneurial class. So in the very first class, one of my students tuned out entirely. And by the end of class had built their entire product that they were planning on doing for the rest of the semester. Right? So that was sort of the first indication. But AI was bad enough at that point. It required enough human guidance that it was like, use AI all you want, but it's not at the level of an MBA student at Wharton. And over time, that hasn't always been true, right? Still jagged, but now AI is quite good. So I can't just say, use AI. So there's a few things you have to do, right? One of the things I do is I use AI powered teaching all the time. I have AI simulations that they have to do.

• 32:56Speaker 02

  There's AI case studies they have to create with an AI to, you know, to, to give me. They have to teach an AI that is programmed to be kind of dumb about a topic. And they have to be a teacher, which is a really good educational technique. And then they build more than they ever did before. They're launching companies where they used to come with an idea. At the same time, I now have to make in-class assessments matter more. Right? I can't check what's AI work and what isn't AI work anymore. So in class, we have to do, we'll have to do things like blue book assignments. And we have to do things like in-class discussions that matter. So it's changing a lot all at once. And I mean, I'm eager to do these things. Not all my colleagues are, nor should they be forced to, or in a just world, to transform their classes as quickly. So the experience is quite even, uneven across the board, depending on, you know, who's teaching and what kind of subject, under what conditions.

• 33:41Scott Galloway?

  A lot of people have said that higher ed is going to implode at the hands of AI. What are your thoughts?

• 33:46Speaker 02

  I actually believe the opposite for a couple of reasons. You know, for, actually for widespread reasons, right? So one reason is what's actually about to implode are internships and all the ways we actually teach people to do work today, which is informal education, where you are a junior person who wants to impress somebody. And a senior person teaches you because they have no choice, right? You know, to give you feedback because there's no one else to do the work. Now, every junior person is having AI do all the work and they learn nothing. Every middle manager would rather turn to AI do the work than interns. They're not teaching anyone and companies are not incentivized to teach. They want to produce output. So guess who's good at teaching assessment and verification? That is us at universities. Like, look, things are screwed up now. They're always screwed up at universities, but it's pretty obvious the path forward.

• 34:29Speaker 02

  AI tutors outside of class, inside of class, active learning assessment. We'll, we'll figure it out. It's not the end of the world. So that's one reason you'll, you'll need to turn to us more. The second is I think wide knowledge matters. I think knowing many things matters more than ever before. And you need to be taught those things. And the AI, people have the wrong incentives with AI to learn. We can teach them those kinds of things. I think that we, and then in a world where there might be more leisure, like, let's say we end up with the, the heaven on earth that the AI companies are planning for us. I mean, you know, I think a gentleman and gentlewoman scholar has become a much more valid thing. And this becomes a thing you do anyway. But as far as the real kind of economy, teaching, learning and, and assessment and verification are all things we do in universities. We may have drifted from the mission sometimes, but that is a mission we can return to quite easily.

• 35:14Speaker 02

  And I think an aborted one.

• 35:15Scott Galloway?

  Do you have tenure, Ethan?

• 35:17Speaker 02

  I do.

• 35:18Scott Galloway?

  So I'm curious to have, I do not. I'm curious to have this conversation with you. I had a robust conversation around tenure at a recent Regents meeting. And I wonder if in an age of AI, if tenure, well, for a lot of reasons, that tenure is going to come under attack. Because tenure is largely based on peer reviewed research, how many citations you get. And I wonder if a lot of that research, I don't want to say is going to go away, but it's going to be challenged. And that for economic reasons, when we hit this demographic cliff, that tenure might come under fire for a variety of forces, including AI. Any thoughts about AI and tenure?

• 35:56Speaker 02

  Yeah, I mean, I, I think you hit on one of the major issues that even precedes tenure and the entire academic establishment, right? Which is I'm now getting the most advanced models are writing pretty good papers. Like finding the research, doing the work, writing it up. They are good, I mean, you know, I, I, you know, I'm an editor reader for journals, I'm a peer reviewer. These are good papers now, right? The, the research taste is only mediocre, like they're not necessarily, they're sort of trivially true often, like they're true, but not that interesting. But then again, it sort of raises a big question of what we're doing in our research. If we're selecting interesting papers or sort of P-hacking from the beginning, but that's all we can do because we're humans making assessments about what's worth spending our time on. The AI can do 100 papers and then it submits those papers and it does really good review.

• 36:37Speaker 02

  And then even worse, as I have the AI do research on topics, it increasingly finds errors in other people's papers. Right? Just instantly, table two of this paper looks wrong and they're not always malicious. Oftentimes they're, most often they're not, they're human errors made by humans. So suddenly we have a tool that can go back over the entire mass of research, can do independent research, can flood our academic systems. And we are in big trouble in terms of rebuilding the foundations of science. Right? So that, that's the first shaky foundation that I worry about. And the second one in tenure, I think tenure is always under crisis in some ways. I think we're going to have to reconstruct what academic research means. In some ways, there's more value in tenure than ever because we can now explore more widely. It's not working on one paper. I, I, if I wasn't tenured, right?

• 37:19Speaker 02

  I would not have been able to do the AI research I'm doing because most of it's not publishable in actual academic journals. At the generative AI lab at Wharton that I run, we've been putting out prompting reports that are some of the most highly cited papers in academia right now. But they are, they would never be published in a top journal. They're, and they're, would need to be done too quickly. So I'm using tenure to my advantage. I see other people doing the same thing. So I think the reasons for tenure may actually increase even as the foundations of science and universities that support tenure collapse.

• 37:47Scott Galloway?

  I would argue that without tenure, that Penn, that Wharton would still be very supportive of the work you're doing. And that it's the criteria that'll change, that there, there's going to be a greater reverence for research that gets the kind of retail traction your research gets versus something that ends up in the journal of, you know, consumer psychology, which, I mean, I'm cynical. You're the guy with tenure. I'm the one that doesn't have it. Uh, I just find a lot of it is a giant circle jerk amongst people who got their PhDs together. But anyways.

• 38:19Speaker 02

  I have no comment.

• 38:20Scott Galloway?

  There you go.

• 38:23Scott Galloway?

  You, you use the term tutor a lot when you're talking about AI. Do you have kids, Ethan?

• 38:29Speaker 02

  I do.

• 38:30Scott Galloway?

  How old are your kids?

• 38:31Speaker 02

  I have a kid in, in college and a kid who is finishing up high school.

• 38:37Scott Galloway?

  So we have kids, I have 19 and 16. It sounds like we're kind of in the same.

• 38:41Speaker 02

  Very similar, yep.

• 38:42Scott Galloway?

  Yeah, as I call it, the kill zone. What is your approach to letting your kids use AI and technology in general? Trying, with, with the understanding that I think I'm really good at AI because I went through the pain of trying to learn how to write, which was really frustrating for me in a multi-decade, you know, adventure. What's your approach to integrating AI into their lives or sequestering them from it?

• 39:06Speaker 02

  Yeah, I mean, I think the right thing to do as a parent is to treat AI like other technologies. Like, I mean, in a lot of ways, it's less fraught than social media, right? The guardrails are real. There's, you know, there's educational potential there that there isn't. And I think you have to kind of take the same approach, right? Which is moderate usage, make decisions and rules, and keep an eye on what's happening. You know, on AI and education, I would generally recommend for younger kids, and I did this when my kids were younger. If they had like a homework problem, I would be the, I took a picture of it with ChatGPT and I'd ask ChatGPT, you explain to me how to explain to my kids how to do this problem in a way they'd understand. So I'd be the interlocutor with AI. And like with younger kids too, you can have really fun, interesting experiments. Let's create a story together. Let's write a program. Let's make a game.

• 39:49Speaker 02

  Great dual experience to do with a child. And you know, your own kids, right? You know how much monitoring they need to do. You know how to, you know, manage their time. Their screen time is many different things. AI used properly is not a terrible use of screen time, but you have to keep an eye on it. As your kids get older, there are, there are actually pretty good teen modes in anthropic and open AI systems that offer some monitoring. And you can lock them into a tutor mode, which is really useful, which makes the AI less likely to give you answers. But again, I'd be watching and paying attention. I think it's a very powerful tool. I think that it's dangerous to count on self-regulation alone. Like there is a lot, especially among, you know, among, you know, some teens and some teen groups, a lot of anti-AI feeling.

• 40:32Speaker 02

  But the research we have seems to indicate that that is public facing feeling and not what they actually do. Right? So they'll say they're not using AI. And, but if you survey students that like 40, 60% of them will say they use AI sometimes. If you ask them and point at a random person, what's the chance this person's using AI? It's 90%, right? So everyone's using it and they're all like, this is terrible. We don't want to use it. So I think we have to be a little careful as, assuming that the social statements are, are the actuality behind this.

• 40:59Scott Galloway?

  We'll be right back after a quick break.

• 41:06Scott Galloway?

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• 41:50Scott Galloway?

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• 42:18Scott Galloway?

  Support for the show comes from USA Facts. I've interviewed countless politicians and if there's one thing we all find disconcerting is when they butcher the facts with some biased half-truth. Give us a break already. So when I had the chance to debate conservative podcaster Ben Shapiro, our natural response was bring it on. Why? Because it was sponsored by USA Facts and each debate segment started with a presentation of government data and [bleep] facts. Employment, government spending, income data, housing and more. The topic? The American dream. Is it still within reach? We argued, we found some common ground, we actually debated, and there were no personal attacks. Watch the full debate on the USA Facts YouTube channel. We think you'll find it unlike any other debate.

• 43:03Scott Galloway?

  That is entertaining and informative. We hope you check it out.

• 43:10Scott Galloway?

  Support for the show comes from Inside Blackstone. AI is changing far more than the tech sector. From healthcare and manufacturing to energy, real estate and financial services, it's reshaping the entire economy. So it's time we hear from the people driving these changes and gain insight into what's happening in real time. And Inside Blackstone has the scoop. It's a new podcast from Blackstone where founders, CEOs and investors, all the people navigating these changes in real time, are talking it out in real, unembellished conversations. As a listener, you get an inside look at the technologies transforming industries and the big trends shaping the economy. Because the biggest changes shaping our world don't start in the headlines, they start on the ground, inside the businesses that drive the future. The goal of Inside Blackstone is simple. Engage in conversations right at the source and making complex topics of change and innovation

• 43:55Scott Galloway?

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• 44:15Scott Galloway?

  We're back with more from Ethan Mollet.

• 44:19Scott Galloway?

  Every few months, you create a guide, which I think is sort of the seminal guide for which AI is best for which task. Can you give us a bit of a Cliff Notes or a preview and run us through like, you know, this AI is best for this and maybe a few surprising ones in categories we don't even think of?

• 44:39Speaker 02

  Sure. I mean, you know, there's a different, there's a level of difficulty you want to engage with. So at this point, if you're really technical and you're using open weights models and you've got an open claw running on your machine and do, you know, more power to you, there's nothing, you know, but that's not most people listening. So the unfortunate truth for most people is you've got to pick either OpenAI or Anthropic or maybe Google. Google now is a good model, but is sort of catching up. And you need to pay 20 bucks a month. There's just kind of no way around that. Once you do that, your life gets pretty easy. The main thing you have to realize is the default models you're being given, especially if you pay for free, but even if you pay, are low-end models. So you have to kind of know that for Anthropic, the ranking is Fable and then Opus and then San and Haiku.

• 45:21Speaker 02

  And for OpenAI, it's Pro and then Astra and then Soul and then Luda. They don't make it easy for you, right? And then you also have to realize you can manipulate the thinking level of these models. And that's actually very important. The more thinking they do, the longer the answer takes, but the better the work you get. So you kind of have to do a little bit of choosing yourself about how hard a problem you're facing. Medical problems, turn up that thinking level, right? Financial problems, turn up that thinking level. Where should I go to a cafe? Less important, right? And so you really want to pick one of those three, you know, and generally that would probably be Anthropic or OpenAI is at the time we're doing this, but Google again has a good model, but not yet all the stuff around it that makes it useful. And you're going to need to pay for it. And then you should experiment, right? Like the key is to start using these things. So voice mode is very powerful.

• 46:06Speaker 02

  OpenAI tends to lead on voice things. If you want to chat with your AI, OpenAI does best at that. If you want a really smart model, but you don't care about the chatting piece, Anthropic has very good ones. But you kind of have to pick one of those and everybody else selling you something is selling you a worse version. The two exceptions are your personal agent. Muse is a very good way to get started. The model that powers Muse is not as powerful as the model that powers DOT, but it's more accessible. So you can expect a slightly higher error rate. I'd be a little more cautious about trusting it on everything, but it's still quite good. So those are two ways to start with personal agents that are quite good also.

• 46:39Scott Galloway?

  So I'm going to give you one personal hack that's been a real, a real unlock for me, and then I'd love to know if you have any others. I just gave Claude Pro, I think, permission to access my Gmail. And it's just, it sounds obvious, but it's just been mind-blowing. I get an email from someone saying, you know, a capital call on a fund I invested three years ago, or I hear from someone and I recognize the name, but I don't, or I see, I get a bill for something and I just say, what is this? Look at my Gmail. And it says, well, you, this is this bill from this, this service that was provided in 2021 from this person.

• 47:19Scott Galloway?

  It's just, you know, just as these LLMs and Google crawl the web, you typically, they can't access your email. And I have found that opening up the corpus of my email for the last 10 years, there's just a ton of information that when it's crawlable and sortable is just incredibly util. Any thoughts on similar types of hacks or unlocks?

• 47:45Speaker 02

  Yeah, let me tell you the next step for that, which is talk to either Claude or your OpenAI or Claude system and tell it you want to set up a scheduled task once or twice a day that goes through your email, decides what's the, and you'll have a conversation with the AI to set this up. It can set up the task for you, but I have ones that go through my email twice a day and actually think about what's important, what needs to be sent to people. I don't let it write personal emails for me, but I do let it write drafts for business emails. So it'll have my drafts in my inbox, ready to go. I edit them and change them. I've worked with it on my writing style. Again, not for anything personal or, you know, important, but for sort of all the minor stuff back and forth. It reads through everything I do a couple of times a day, inbox and outbox, and then gives me sort of what should I be paying attention to? What's an issue?

• 48:28Speaker 02

  Once a week, I have it scraped through all my financials and tell me, am I missing anything? Is there anyone taking advantage of me? Are there subscriptions I should cancel? And it gives me the links to do that. So once you've hooked this up to your Gmail, setting up scheduled tasks a couple of times a day or once a week is a really big deal. The agent models, right? DOT and, and, and Muse sort of do this proactively, but they sort of do it one-off. You really want a sort of sweep. So scheduled tasks, and you can just ask the AI to help you set one up for you, and then you work back and forth with it to make it really good. Cannot recommend it highly enough.

• 49:01Scott Galloway?

  That's great. So let's talk specifically about these companies in the markets. Anthropic told prospective investors in its Q3 revenue had jumped nearly 50% to 17 billion, claiming the company is now profitable on an adjusted basis. God, I hate that. Adjusted. I love that. Profits before everything else. Meanwhile, an OpenAI engineer has been accused of spying on the company on behalf of the Saudi government. What do you make of the current state of the two major players in terms of their horse race and this, these impending kind of $2 trillion IPOs?

• 49:35Speaker 02

  I think it helps to think about these companies as like two things. They have, they've gotten in their hands on the most powerful technology anyone's come up with in, you know, in decades, maybe centuries, right? Like LLMs are unreasonably effective and the researchers are really good at building new ones. The LLMs help build new ones. They have, they're on a rocket ship where these systems are really good and keep getting better, right? And we could talk about where the value of intelligence is or other stuff we've talked about a little already. And then they're also a startup company that has grown incredibly large, incredibly quickly, that has all the problems you'd expect a startup company to have, right? There is mission creep and also political infighting and lack of clarity and financial game is being played left and right. And I think these two things coexist kind of loosely with each other, right?

• 50:17Speaker 02

  On one hand, you have an underlying business that is, that is very expensive, right? They're probably profitable on inference. They are probably, they're definitely not profitable on what training is thrown in, right? And this kind of complexity, but you're also betting on the future where they keep creating more and more super intelligent models. And it's a really hard divergence to deal with in some ways because you, how much do you buy the existence of AGI, machines smarter than a human? How much do you buy that this is a normal business that we should evaluate normally versus an extraordinary one? It's really complicated. Then we have the global issues you're talking about here of like now geopolitics matters, right? And the most valuable thing in the world could fit into a thumb drive. Like if someone gets the weights for these models, that's all they need to copy them, right?

• 51:00Speaker 02

  And so you have a lot of complexity happening all at once. It makes it really hard to value these things in a traditional sense. Like the world is becoming dependent on these things very quickly, even as we haven't fully proved out the value in every case. And their revenues are going exponential too. I mean, it's a complicated situation that makes it really hard to do kind of traditional financial valuation. And at the same time, the companies are playing all the games that an IPO and company does that, you know, obscures what's really happening as well.

• 51:27Scott Galloway?

  If you had to sum up the advice in your book for learning how to navigate this next phase of AI, what would you say from an investor perspective, from a consumer's perspective, and from a government perspective?

• 51:39Speaker 02

  So I think the first thing I would say overall to everybody is you're underestimating what these systems could do. We don't need a future development for large scale change. Underestimating. But there is what these systems could do today and what they will be able to do in the near future in terms of the quality and amount of work. That will take time to absorb, but I worry that the invest, like a lot of people in business and the investing world are focusing on AI as an investment and not thinking enough about what changes or transforms as a result of ubiquitous intelligence at low cost everywhere. And I think that the transformational opportunities are far beyond the companies themselves. So I don't know whether anthropic rises or falls. I don't know whether the debt financing model for, you know, for, you know, for data centers is problematic or not. Like, I can't

• 52:23Speaker 02

  tell you the answer to that question. But AI is not going away in either case, right? And the capability overhang is still quite large. So I'd be thinking one step beyond just the idea of like, do I invest in Anthropic or Nvidia and start thinking about what happens next? The second thing I would say for individuals using these systems is you have to try and use them for everything that you can to figure out the shape of the jagged frontier. And you need to be as ambitious as possible, maximalist in how you're using these things to figure out what they're good or bad at. And then you have to make really strong choices about when you use AI and when not to. This will take willpower. It will take some self-examination. But you have to make choices about what you want to maintain humanity for and what you don't. And that is also kind of a big deal. And on the business side, leaders need to start making decisions about how AI is going to be used. That means transforming their

• 53:07Speaker 02

  companies, but also making decisions about how they're going to augment rather than just replace labor. Because I think replacing labor is going to be very tempting, but is actually dangerous, not just to society, but also to the companies involved. Like, think about if you're a company that was doing marketing work and you switched all of your marketing language to Claude back in January before anyone knew Claude speak, right? Before it was filled LinkedIn in every article you read. It's probably seemed like a really good idea at the time. And now anytime you read that stuff, you get nauseous. Like, it's carrying the weight. Like, we all know this Claude language. And so the fact that you fire all your marketers is probably going to hurt you because you have the same company as everybody else. So I think those are the, like, the piece of advice that realizing this is really great, but the jagged frontiers remain, but we have to protect, we have to be trying to figure out where we go next on an exponential rather than satisficing ourselves as where we are today.

• 53:52Scott Galloway?

  I want to move on to some listener Q and A, submitted ahead of time, questions from our listeners. The first question comes from Jake. I'm in my twenties and there's a lot of backlash against AI among my friends and online. Meanwhile, at work, we're told we need to embrace it all or fall behind. Do you think young people's skepticism is justified? How do we navigate these two pressures?

• 54:12Speaker 02

  I mean, I think that there's a lot of things about AI that are uncomfortable, right? It doesn't help that the heads of the AI labs are telling us that they might kill us all or remove all jobs. Like, it's hard to be behind that, right? You know, oligarchy and control of money, right? Or the collusion between government and industry. I mean, all the usual stuff applied, plus a mix of real environmental concerns and kind of not real ones. Like, on the real side, electricity is a real concern. On the not real side, water use is not really a big issue compared to other light industries and data centers that are becoming more efficient. But it becomes a bundled thing, right? That it gets a social feeling behind it. And as I sort of told you, there's a sort of gap between what people say and what they do. So I think AI has a very bad reputation,

• 54:55Speaker 02

  but people use the personal agents like crazy. So there's going to be, it's kind of like Congress, right? Where everyone hates Congress and everyone loves their representative. I think we're going to see the same sort of thing happen in the AI space. I think that what I find even among young people, when I teach them about this stuff, is they actually want to learn how to use AI better. They want to be responsible using this. They want to shape the direction things come in. And to me, the reaction that's dangerous with AI is people saying that they're, they're going to pretend it goes away. They're going to put their head in the sand and be like, this is all going to collapse. This isn't real. I don't have to pay attention to it. I mean, you know, to use a famous phrase, right? You may not be interested in AI, but AI is interested in you. Like, you have to, like, our chance is to shape this direction for young people comes from actually acting and vetting with this. So like, realizing this is real. So feel like, I think we need

• 55:40Speaker 02

  more social movements around this. I think we, but we need to make those movements around what's real. I also think this is an opportunity to try and build the utopia you want. I'm a little disappointed that I don't see more young people with an interest in AI trying to think about, how do we use this to build the world we want? That's more equal and more equitable and with better outcomes for everybody. This is an incredible positive tool, too. So I think we need to be thinking in both sides of things and viewing this as a positive opportunity as well as trying to mitigate the risks.

• 56:05Scott Galloway?

  Next question comes from Mary on Instagram. I love this one. My partner uses ChatGPT to work through our disagreements. Is there a productive role for AI in a relationship?

• 56:16Speaker 02

  So this is another place where we have to negotiate, right? Negotiate boundaries. The evidence right now on AI and sort of counseling is generally mixed to favorable. Like, we don't really know the outcomes very well. There's some early studies that suggest positive things. We have a lot of anecdotal and lawsuits about AI psychosis problems. It's kind of hard to know. But I mean, you're inviting this thing into your intimate parts of your life. How do you feel about that? On the other hand, as I talk about in the book, one of the first things people start doing with AI are things like obituaries and wedding toasts and children's stories, like literally the most intimate things we do. So the thing about AI that seems to be good is, same thing with financial advice. It gives good advice, like good straightforward advice. So if it helps you to have a third person involved that gives you good straightforward advice, that can be very useful. At the

• 57:01Speaker 02

  same time, you don't want someone sort of going to AI and finding strategies to beat you in conversation. So I would, you know, advise openness. Like, it's certainly worth trying. A lot of people get a lot of help out of talking to AI to do things. But I think you should do it with an air of caution and anxiety about what you're giving up as a result of this. So I don't think it's inherently bad, and a lot of people get good results. But at the same time, you neither want to obey AI and everything it tells you to do, nor do you want to be doing this secretly without your partner knowing.

• 57:26Scott Galloway?

  So the place where I notice AI the most, and I'd love to get your thoughts and color on this, I have found I have become, addicted is the wrong word, I'm spending too much time on Instagram reels. And I think the, my understanding is they spend more than any other firm in the world, with the exception of Amazon on AI. And how I see that is I cannot get over how good it is at predicting exactly the right video at the right time to serve up to me next. I just find it almost chilling. It's literally reading my mind

• 58:07Scott Galloway?

  in terms of what's the next 30 second, you know, shot of Dopa I want. Can you, A, your thoughts on that? And B, what does it mean when AI can start to program our attention? Do we eventually, I mean, are we headed towards idiocracy where we just sequester from the rest of humanity? Because nothing, nothing beats the AI-driven Dopa we're going to get on our screens?

• 58:34Speaker 02

  I mean, I worry about that, right? I mean, and you're kind of talking about old school AI, machine learning, old school being like four years old, right? Which is like traditional prediction models are already this good. And then you start to combine them with what large language models can do, which is create content for you that's on demand, right? So right now, it's still curating. The next stage is, you know, the H3 video generators already generates videos fast that you can watch it. Suno generates music fast that you can listen to it. It's going to soon be material generated for you on demand. That's a mix of real and fake content. And as a very persuasive, you know, we're just going to see this amped up. I don't see an easy way out of that treadmill without a choice being made that you don't want to do it. You know, like, I think there is a limit. I think people will want human engagement. I don't think we're going to

• 59:16Speaker 02

  all retreat into 100% AI-generated world. At some point, you'll throw your phone down and be like, I need to go outside for a little bit, or at least many people will. But I think, I don't know what that limit is, right? I don't, and I don't know what the power of that is. And I think that we're going to have to start being really careful about this or have policies around this because it, you know, entertainment is entertaining. And if we can get really good at entertaining just you personally, then not only, like, then even the last threads kind of snap, right? Instagram, you're presumably watching real people do real things, to some extent still. At some point, that starts to snap and it's just like you're in your own world. And I do, I do worry about that. I think that that's a legitimate concern to have. And I think retreating to human spaces is going to be a survival strategy for us. Like, we're going to have to figure out ways to

• 1:00:00Speaker 02

  get together more, even at a time where dinner parties are collapsing. So I think the trends are heading in a bad direction there.

• 1:00:06Scott Galloway?

  Great. Is there anything, this is, I want to end on an optimistic note here. Is there anything that AI can do or that you see AI doing that helps bring together people? Kind of IRL, more human connection. And I'm not talking about Reddit or Discord. Is, I love, I love your challenge to young people to take an optimist viewpoint and figure out how to create more social good leveraging AI instead of catastrophizing about it all the time. And by the way, I think there's a incentive in our community amongst academics and thought leaders to catastrophize. It just makes for, it just makes for a bigger speaking fees. Than saying, oh, this is an interesting technology and everything's going to get a little bit better every day.

• 1:00:51Scott Galloway?

  That doesn't get you invited back for a keynote. Can you talk about something or that you've seen that you find really hopeful around AI?

• 1:01:00Speaker 02

  I mean, I've had a million things helpful, right? Like, this is what I mean, we have intelligence on demand. So there's tons of people who like, it's a good, you know, second opinion doctor, first line, if you don't have a doctor, it's a good lawyer, it's a good financial advisor. It's probably, you know, it's useful to talk to when you're feeling bad or down. It's a good tutor when used properly. Like, these are problems that we have spent hundreds of billions of dollars and infinite amounts of academic research trying to solve, how do we teach people better? And we know tutoring is great, we could never do 101 tutoring. So we've been inventing all this other stuff. We know that people lack access to medical information. We know even GPT-4, long obsolete model, right? When given to Kenyan entrepreneurs who are already doing well, 18% profitability from just getting advice from AI for entrepreneurs. Like, there is so much opportunity to super chart without going to a future pie in the

• 1:01:44Speaker 02

  sky situation, right? Where like, does AI save us and invent new drugs? We have a tool now that provides intelligence and advice that is reasonably good advice to people who can't get it, that's customized for their condition. And I think we tend to think a lot about sort of the narrow viewpoint of those of us who are well-connected and well-resourced and, you know, balancing out our desire for entertainment with AI doing things. In large parts of the world, we finally have a thing that gives good advice. There's a great set of studies on pig farmers in Thailand who can now get diseases diagnosed. Like, there's a thousand million little use cases here where intelligence was the bottleneck to making the world a better place. And we can do this. And I feel like we don't talk enough about those things and they require some effort and they require testing and they require safeguards. But this is exciting.

• 1:02:29Speaker 02

  I mean, as someone who's been trying to do education at scale for a long time and, you know, running to wall after wall, suddenly you have a tutor that works across languages and ability levels and matches your interest level and can follow what you're doing badly and generate images to amuse you. Suddenly, there's real possibility here for a better world and we can see that even as we worry about the risks.

• 1:02:49Scott Galloway?

  Ethan Mollick is a professor at the Wharton School, author of Co-Intelligence: Living and Working with AI, and writes the popular Substack, One Useful Thing. His newest book, Coexistence: The Next Phase of AI, is out now. He joins us from the kickoff events for his book tour in the Bay Area. The Bay Area at the second-best school in the Bay Area. Are you doing anything at Berkeley, Ethan?

• 1:03:14Speaker 02

  Not this time around. You got to save something for later.

• 1:03:16Scott Galloway?

  That's it. That's it. You're off my Christmas list, Ethan. Professor Mollick, really appreciate your time.

• 1:03:22Speaker 02

  Thanks for having me.

• 1:03:25Scott Galloway?

  This episode was produced by Jennifer Sanchez, Laura Janera, and Asher Schwartz. Our video editor is Bianca Rosario Ramirez. Kami Reek is our social producer. Drew Burrows is our technical director and Catherine Dillon is our executive producer. Thanks for listening to the Prof G Pod from Prof G Media.

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