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Simon Sinek · YouTube

The AI Skills Nobody is Teaching (And Everyone Needs)

Wharton's Ethan Mollick gives Simon Sinek the rare neither-doomer-nor-zealot playbook for the AI era: experience, taste, and your own point of view are exactly what make you better at using the machine.

Posted
5 days ago
Duration
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Interview
sincere
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96.2K
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Big Idea

The argument in one line.

When AI makes everyone generically excellent, quality stops being a differentiator and your scarce edge becomes the things AI cannot supply: hard-won expertise, personal taste, and a point of view that produces variation.

Who This Is For

Read if. Skip if.

READ IF YOU ARE…
  • A knowledge worker who feels behind on AI and is drowning in contradictory advice about prompts, agents, and which chatbot to pick.
  • A manager or executive deciding whether AI means firing people or making your existing team more capable.
  • An experienced professional worried AI makes your decades of expertise worthless, when it may be your biggest advantage.
  • An educator or parent uneasy about students outsourcing their thinking to ChatGPT and unsure what is actually lost.
  • A writer, creator, or solo builder who wants AI to draft in your voice instead of the interchangeable ChatGPT voice.
SKIP IF…
  • You want hands-on, tool-by-tool prompt tutorials; this is a strategic conversation, not a how-to with screenshots.
  • You already follow Mollick's One Useful Thing closely and want net-new research rather than his greatest-hits synthesis.
  • You are looking for either a pure doom case or a pure techno-utopian pitch; the entire point is that it refuses both.
TL;DR

The full version, fast.

AI researcher Ethan Mollick argues the panic-versus-hype framing misses the real story: we have enormous agency over how AI plays out, and the human traits AI cannot replace are precisely what make us good at using it. Experience beats youth (juniors are worse at AI because they cannot judge the output), prompt engineering is dead, and the highest-leverage move is paying $20 for a frontier thinking model and giving it genuinely hard tasks. As quality commoditizes, taste becomes the scarce skill, the bottleneck inside every job shifts to what only humans do well, and your agency is to build the positive uses of AI inside your own work rather than waiting to be automated away.

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Voices

Who's talking.

00:00hostSimon Sinek
01:15guestEthan Mollick
Chapters

Where the time goes.

00:00 – 02:05

01 · The human competitive edge

Cold open: if AI makes everyone good, variation and taste become the only edge. Sinek introduces Mollick as the neither-doomer-nor-zealot AI expert.

02:05 – 03:30

02 · Why Ethan became the practical AI voice

Twenty years AI-adjacent at MIT Media Lab as the non-technical explainer; positioned to translate AI when GPT-3 and ChatGPT arrived.

03:30 – 05:54

03 · The internet showed up: why AI feels familiar

Both extreme camps eat the world. AI is a general-purpose technology; eating-to-live vs living-to-eat; technology is the most human activity and we keep our agency.

05:54 – 08:52

04 · Overwhelmed by AI advice

Sinek is paralyzed by conflicting prompt/agent advice. Mollick: AI got easier, prompt engineering is dead, all three big models are solid - just use it.

08:52 – 12:14

05 · Pendulum swings: blue collar vs white collar

Knowledge workers now feel what factory workers felt. Guilds (lawyers, doctors) will protect themselves with law; coders have no such protection. Lobbying and disruption ripples.

12:14 – 20:40

06 · Getting practical: use AI better

Pay $20, pick the newest thinking model. Three phases of AI ending in agentic. GDPval: AI matches experts 84% of the time. You underuse it by giving it easy tasks; efficiency is speed of evaluation.

20:40 – 25:48

07 · The voice problem

AI has a voice, just not yours. The ChatGPT-voice tells (staccato, 'not X but Y', em-dashes). Fix: feed it your writing, have it write a style guide. Sinek's Claude op-ed experiment.

25:48 – 29:48

08 · Jobs shift, the apprenticeship breaks

Jobs are bundles of tasks; the weight shifts to bottlenecks AI is bad at. The 4,000-year apprenticeship model breaks because juniors and managers both prefer the AI.

29:48 – 33:57

09 · Art, intention, and the joy of human creation

Sinek is fine with AI art but values knowing a human made it. AI weird analogies; meaning shifts from artist to viewer. Learning is effortful; you must lift mental weights.

33:57 – 37:50

10 · Results obsession predates AI

AI is the exaggerated form of a results-obsessed, effort-avoidant culture. Human systems (school, work, courts) were not built for an AI world.

37:50 – 41:20

11 · The death of movie stars and the rise of taste

Quality commoditizes; we are the last generation with movie stars. Variation is the edge. Taste becomes the new teachable skill; directors and curators matter more.

41:20 – 43:40

12 · Models, apps, and harnesses

The three-layer mental model. Brains are roughly equal across labs; Claude Code and Codex lead on harnesses because they act on your machine.

43:40 – 47:10

13 · Privacy, security, and trusting AI with your data

Turn off training with a paid plan. Open questions on discoverability. The real risk is giving an agent access to your computer, files, and money.

47:10 – 50:10

14 · Teaching when AI does the work

Mollick's viral syllabus. Using AI to get answers gives the illusion of learning. Solutions: in-class work, AI tutors that withhold answers, expertise-anchored projects.

50:10 – 52:40

15 · Your brain on technology

Phone numbers, the Iliad, cursive, slide rules - we give up abilities on purpose. The fear is that thinking itself, not memory, becomes the sacrifice.

52:40 – 55:00

16 · The conversation trick: using AI to learn

Debate the AI by voice at your level. Two prompts: tell it to act as a critic (it is sycophantic), and ask it mid-stream to evaluate your arguments. Persona-readers for editing.

55:00 – 57:50

17 · Fears and your agency in the revolution

Chaos, deepfakes, and underestimating how good AI is. Two levels of agency - societal and personal. Your real agency: build the positive uses inside your own work.

57:50 – 58:35

18 · Close and subscribe

Sinek solo to-camera: it is still really me. Keep the muscles alive. Subscribe to A Bit of Optimism.

Atomic Insights

Lines worth screenshotting.

  • Young people are not AI natives; a BCG study found junior employees were often worse at using AI because they cannot judge whether the output is good or bad.
  • Experience is the real AI advantage: the more expertise you have, the faster you spot when an answer is wrong and why.
  • Prompt engineering is dead - saying 'you are a physicist,' 'think hard,' or offering bribes no longer changes the output.
  • The single highest-ROI AI move is paying $20 a month and actively selecting the newest thinking model, which the app hides behind a weaker default.
  • On OpenAI's GDPval benchmark, the latest models match or beat 14-year experts on hard real tasks about 84% of the time, up from 48% a year earlier.
  • Most people underuse AI by giving it easy tasks; give it the hard seven-hour jobs and you save roughly 3x time and cost even after evaluating the output.
  • Efficiency with AI is not how fast it solves a problem but how fast you can evaluate whether it solved it correctly.
  • AI does not lack a voice - it has a singular ChatGPT voice (staccato sentences, 'it is not X, it is Y,' too many em-dashes) that makes everything sound the same.
  • To get AI to write like you, feed it a large sample of your writing and have it generate a two-page style guide you save as a custom instruction.
  • The jagged frontier means AI is great at some tasks and surprisingly bad at others; where it is bad, the demand and value of your labor goes up.
  • The 4,000-year-old apprenticeship pipeline just broke, because juniors would rather ask ChatGPT and managers would rather delegate to AI than to a slow human.
  • When everything becomes generically excellent, quality commoditizes and taste - your variation, your questions, who you choose - becomes the differentiator.
  • If Claude can run your company well it can run every company equally well, so generic high quality with no variation means no competitive edge.
  • AI is sycophantic and will agree with you in a debate, so you must explicitly tell it to act as a critic to get real pushback.
  • Telling AI it is a physicist does not make it better at physics, but assigning personas (hostile expert, confused layperson, cynic) gives you a free panel of readers.
  • Think in three layers: the model is the brains, the app is how you access it, and the harness is what lets the AI actually do things on your machine.
  • Your biggest source of agency is using AI well in your own job, because the labs are full of coders who do not know how AI is useful in your field.
  • The deeper danger is not losing memory or mental math but outsourcing thinking itself, which experiments show produces the illusion of learning without the learning.
Takeaway

Your edge is what AI cannot commoditize

WHAT TO LEARN

As AI makes competent output universal and cheap, your durable value moves to the things it cannot supply: domain expertise to judge its work, your own voice, and taste.

  • Stop trusting the 'young people are AI natives' myth - experience makes you better at AI because you can instantly judge whether an answer is right and why.
  • Forget prompt engineering; the highest-leverage move is paying $20 a month and actively selecting the newest thinking model instead of the weaker default.
  • You are underusing AI if you only ask easy questions - hand it the genuinely hard, multi-hour tasks where it can save you 3x even after you evaluate the output.
  • Treat efficiency as how fast you can evaluate the output, not how fast AI produces it, which is why domain expertise becomes more valuable, not less.
  • AI writes in a recognizable generic voice; reclaim yours by feeding it a sample of your writing and having it build a reusable style guide.
  • Find your jagged frontier - the tasks AI is bad at in your field - because that is exactly where your labor becomes more valuable and harder to replace.
  • Because AI is sycophantic, explicitly tell it to act as a critic, and ask it mid-conversation to evaluate your arguments so you actually learn instead of just getting agreement.
  • Guard your thinking, not just your memory - shortcutting effortful learning through AI gives you the feeling of learning without the learning.
  • Your real agency is to build and share positive uses of AI inside your own work, so augmentation beats the default plan of firing people for short-term profit.
Glossary

Terms worth knowing.

Jagged frontier
Mollick's term for the uneven capability surface of AI: it is unexpectedly strong at some tasks and weak at others, with no clean line you can predict in advance. Knowing where the jagged edges fall in your field is what lets you use it well.
Agentic AI
AI systems that can independently go and do multi-step work when asked, rather than just answering a single prompt in a chat. Mollick frames it as the third phase of AI, only a few months old in practice at the time of recording.
Harness
The layer that lets an AI model actually take actions - write and run code, search the web, generate images, or use your files and browser - as distinct from the underlying model and the app you access it through.
GDPval
An OpenAI benchmark that has experts build hard, real problems from their own fields and then blindly compares AI output against human output; used in the conversation to show AI now ties or beats experts on such tasks roughly 84% of the time.
Co-Intelligence
Mollick's framing (and bestselling book title) for the prior chat-based phase of AI, where you work back and forth with a chatbot to reach an answer, as opposed to the newer agentic phase.
Sycophancy
The tendency of AI models to agree with and flatter the user rather than push back, which is why Mollick says you must explicitly instruct the model to act as a critic when you want honest evaluation.
Resources

Things they pointed at.

01:15bookCo-Intelligence: Living and Working with AI (Ethan Mollick)
01:15linkOne Useful Thing (Mollick's Substack newsletter) ↗
01:15bookCo-Existence: The Next Phase of AI (Mollick's new book) ↗
12:40productGDPval benchmark (OpenAI)
16:44linkBCG (Boston Consulting Group) study on AI use
41:40toolClaude Code
41:45toolOpenAI Codex
41:50toolNotebookLM
Quotables

Lines you could clip.

00:03
“If Claude is really good at running your company, Claude is also good at running every other company, and there is no variation between them. Generically high quality with no variation means there is no competitive edge.”
The thesis of the whole episode in one tight claim.→ TikTok hook↗ Tweet quote
16:46
“They are not AI native. You are just talking to Claude. They are conduits to Claude.”
Punchy, counterintuitive, kills the 'young people are AI natives' assumption in one line.→ IG reel cold open↗ Tweet quote
12:20
“You have to actively pick the best model available, which gets you the thinking models. You will get huge improvements just from picking the most recent model.”
The single most actionable tip, self-contained.→ newsletter pull-quote↗ Tweet quote
17:20
“AI can write beautifully but it has no voice. If you ask it to have a voice it borrows other published people, not you. So most writing starts to sound the same.”
Names the AI-sameness problem everyone feels but cannot articulate.→ TikTok hook↗ Tweet quote
21:40
“The staccato three-sentence... it is not X, it is Y... this is a load-bearing argument... it loves em-dashes too much. I just delete them all because they are all familiar.”
Funny, meta, instantly recognizable list of ChatGPT tells.→ IG reel cold open↗ Tweet quote
39:20
“We are in the last generation that has movie stars. Nobody buys a ticket because a particular actor is in it - we would rather see the franchise.”
Provocative cultural claim that lands the commoditization point.→ TikTok hook↗ Tweet quote
53:00
“The AI is sycophantic. If you are having a debate with it, it will agree with you - so you have to tell it to act like a critic.”
One practical prompt insight, zero setup needed.→ newsletter pull-quote↗ Tweet quote
33:30
“AI is just the most exaggerated form of being results-obsessed at the expense of the effort, the work, or the journey to get there.”
Sinek reframing AI anxiety as a pre-existing culture problem.→ IG reel cold open↗ Tweet quote
26:00
“Where it is bad - writing perfectly in your voice, getting a joke right - suddenly the demand for your labor is higher there, and your value is higher.”
Turns the jagged frontier into a career-strategy insight.→ newsletter pull-quote↗ Tweet quote
16:50
“The more experienced you are, and sometimes the older you are, the better you are going to be at using AI - if you decide to use it.”
Reverses the conventional wisdom; reassuring to a huge audience.→ TikTok hook↗ Tweet quote
Topic Map

Where the conversation goes.

00:00 – 05:54denseWhy neither doom nor hype is useful
05:54 – 08:52denseOverwhelm, prompt engineering is dead
08:52 – 12:14steadyLabor, guilds, and disruption ripples
12:14 – 20:40densePractical playbook: model choice, hard tasks, evaluation
20:40 – 25:48denseVoice and AI writing
25:48 – 29:48denseJob redesign and the broken apprenticeship
29:48 – 37:50steadyArt, intention, effortful learning
37:50 – 41:20denseCommoditization and the rise of taste
41:20 – 47:10steadyModels / apps / harnesses and security
47:10 – 52:40denseEducation and the brain
52:40 – 58:35denseLearning with AI and closing fears/agency
The Script

Word for word.

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Don't just watch it. Burn it in.

See every word as it's spoken — crank it to 2× and still catch all of it. The same dual-channel trick behind Amazon's Kindle + Audible.

metaphoranalogystory
00:00So when you're interviewing for a job and everybody's good because of AI, how do I stand out and and get a job that's still that they still need to hire for? I'm fascinated
00:11by that. Like, if Claude is really good at running your company, Claude's also good at running every other company, and there's no variation between them. And generically high quality with no variation means there's no votes or competitive edge.
00:24I think humans who bring competitive edge to this one way or another just by providing variation if nothing else Yes. Is a useful way to think about problems. Right?
00:31You start to care a lot more about the taste of that person than you do about the entire organization built to deliver the product.
00:38We're all a little afraid of AI. Even the people who love it are a little bit afraid. Some of us are afraid it'll take our jobs or make us dumber or change everything so fast, we'll never be able to catch up.
00:51It doesn't help the most AI experts fall into one of two camps. There are the doomers or there are the zealots. That's why I wanted to talk to Ethan Moloch.
01:00He's an AI expert who refreshingly is neither. Ethan's a Wharton professor studying how AI, entrepreneurship, and innovation impact our work.
01:10He focuses on how employees actually use these tools rather than how they're theoretically supposed to improve our work. His New York Times bestseller, Cointelligence, and his popular substack, One Useful Thing, have become the go to resources for all those people trying to make sense of AI without losing their minds.
01:29Ethan believes we have more agency over AI than we think. It's our experience, our taste, and our genuine points of view that are things that AI can never replace.
01:42And that's important because the choices we make about how we integrate AI personally and at work as a society will shape what it becomes.
01:52If you like this episode, please remember to subscribe. This is a bit of optimism.
02:04You are very popular right now.
02:10What were you I know you teach entrepreneurship and other things. Before AI,
02:15what was the what were you teaching that was the the the hot thing? In addition to AI stuff, my other thing I really care about is games and educate and and education at scale, related things. I've done a lot of work on using video games for teaching.
02:27So I was I was, as the brand says, not famous but known in that space of thinking about games and, you know, teaching at scale. How do we teach transformationally? So that has been something I've worked on for a long time, and the AI work was sort of in parallel to that.
02:39And was it your own personal curiosity about AI that that sucked you in, or was it that you you were forced to use AI in the work that you were doing because it had to because it made it better? I went to business school and my PhD program at MIT, and I worked with the MIT Media Lab with their AI group. So, um, Marvin Minsky was one of the fathers of the field, and I was the nontechnical guy in the group.
03:00So I was the person who had to explain to other people what AI was, how it worked, when we'd go talk, have technical conversations. I'd come along. I have been AI adjacent or involved for twenty years, but always in the sort of nontechnical, like, how do we use this?
03:14How do we explain it role? And everybody else was technical because it wasn't really working out. Like, AI had limited use cases.
03:19And so when GPT three came along and started to be make a splash little and then chat GPT after that, I was sort of well positioned in this world of someone who'd been thinking about explaining this for a while in in a nontechnical world. The reason I was really interested in talking to you because I I to be honest with you I try not to have AI guests on
03:37and the reason is is because they generally come in one of two flavors. Right? It's the greatest thing that ever happened and it's gonna make the world a better place or it's the worst thing that ever happened we're all gonna die.
03:50And the conversations are for obvious reasons a little lopsided and one-sided and they're usually have some vested interest in one opinion or the other. Yes. And the reason I wanted to talk to you to be honest with you is yours is just more practical.
04:04It's not it's the savior. It's not it's gonna kill us all, but it's kinda like, well, it's here, you know, kinda like the Internet showed up.
04:13What's the best way to use this thing?
04:15And and it's a it's a little more down the middle. Yes. It's nice to be in a place where being somewhat pragmatic makes you unusual.
04:24Um, that's not usually the place where we get publicity for being the non bombastic version. It's true. But also, the the other problem with those two opinions is they tend to eat the world.
04:32Right? If you think Yeah. We're getting a machine god who's gonna save us all, then, you know, all that matters is discussing that.
04:39Right? Just like any other sort of religious belief. And if you believe that we're all gonna die, how can you have a conversation about anything other than, you know, this is gonna doom us all?
04:47And the fact is this is general purpose technology. It's gonna affect everything we do one way or another. It's worth spending some time on that.
04:52And then some of those effects will be good, some will be bad. I do remember the sort of the rise of the Internet. I'm old enough to remember it.
04:59And the conversations were somewhat similar,
05:03maybe less less dramatic on on either side. There was a lot of positive energy at that time. Mostly positive but but there was lots of conversation like I remember people who, you know, they were the zealots who believed that the internet and everything online was gonna replace everything.
05:16You know what it is? It's the difference between eating to live and living to eat.
05:20You know? And if you leave it to the technologist, they think all technology is living to eat. I mean, they literally made protein powder shakes.
05:27I don't remember a Soyent. Were supposed to I remember Soylent. I remember.
05:30For people for people who thought eating was too annoying, are we spending all of our time worrying about eating when we could just get it taken care of? Right? It's a different view of efficiency, but it's also a view that kind of blinds you to the fact that technology is the most human activity.
05:42Right? We're making tools for ourselves, How we use them, how we adopt them, how we regulate them. Those are gonna have big influences.
05:49You know, AI is more self directed than most technologies, but we still have a lot of agency over what happens next. I mean, I know from my own experience, most people are
05:59misusing or underutilizing the technologies that are available to us and I'm already getting to the point where I'm turning on you know social media or listening to friends or reading an article and I'm already feeling overwhelmed by all of the advice of people telling me that I should be using it like this and I'd be she's setting up an agent to run my life and setting up an agent to do my marketing and set up an agent to do my finances.
06:20I'm already overwhelmed by all the advice of how I should even be prompting the machine to the point where I'm almost backing off and shutting down because one minute Gemini's that you gotta only use that one, next one you gotta only use chat GBT, next you only gotta only use Claude. It's all too much already and for anybody who's not predisposed to like be all in,
06:41that reaction I think is pushing some people away, believe it or not. Well, I absolutely I mean, look, I am I am a nerd of the old school, so I like getting into the details of stuff and partially, like, explaining them, which is I think part of why you have me here. But, also, it is overwhelming.
06:54I mean, part of what's actually interesting is AI has gotten easier. Right? Not to be too, you know, too evangelistic about it, but, like, it used to be this stuff mattered.
07:01Like, you had the like, all those little details. Like, prompt engineering mattered. So it mattered how I phrase things.
07:07It mattered. If I said, you know, you are a physicist, it was better physics. If I said, think hard about this, that mattered.
07:13If I offered bribes, that would matter. Uh, we've been testing all that.
07:16None of that matters anymore. The model's gotten good enough that if you're good at giving instructions like a human to humans, you probably do okay with this.
07:23And similarly, all the models are getting good quite quickly. So whether you OpenAI or ChatGePity, they're like ChatGePity or Gemini or Anthropic, they're all three of those are pretty solid. There's, like, one or two hints I'd give people, but otherwise, it's really just use it for stuff.
07:36And don't stress how you're using it because you'll figure it out. Also, when we talk about, like, AI is gonna take away all of our jobs and by the way, those are the technologists saying that. When one of the things that I also love is the technologists are also very fond of saying, you know, things like 80% of the jobs today didn't exist twenty years ago, which means it's fair to say that 80% of the jobs in twenty years we can't even imagine.
07:57And to your point about prompting, it wasn't that long ago where the technologists were telling us prompting is gonna be the thing and people are saying I'm gonna get a degree in prompting and the technology got good enough in just a few minutes that that literally went away. Yeah. And I I think that that is part of what makes this kind of interesting.
08:14Right? Is we can't imagine the jobs where we will keep trying and also not imagine jobs does get nerve racking when, like, you know, AI is here. It's like, what is the job?
08:22Well, I'm I'm not a 100% sure. I mean, I think there's both legitimate reasons to worry about jobs. These systems are very capable and very confident, and they do chain they impact real work.
08:30This is not electricity
08:32in the same way of, like, we need to figure out a way to harness or use this thing. There's a real impact. I've talked about this a little bit.
08:37I actually think that, you know, nature pours a vacuum, markets correct. When we have a bubble, the stock market will at some point not of our choosing correct itself and it it all systems seek equilibrium at some point. I'm fond of saying that in the seventies and eighties, robots started to enter factories and the blue collar world said, hey, we're gonna lose our jobs and the and the white collar world said, it's the future baby.
09:02Progress stops for no one. Reskill. You know?
09:05And you know the pendulum doth swing and and because your plumber doesn't care about AI, the carpenter doesn't care about AI, The mechanic doesn't care about AI. The people who care about AI are the knowledge workers.
09:17Yes. And, you know,
09:19it's the future, baby. Progress stops for no one. Reskill, baby.
09:23Yeah. That I mean, that's a really exciting I mean, there is a come up with but there is another thing. Right?
09:27Like, if you look at the last three industrial revolutions, there's either two or three. I mean, that's all we've got. Right?
09:32And the the reason they worked out wasn't because the technology made everything great alone. It was because there was also labor fought against, you know, capital, and you had a whole bunch of fights happening. Unionization is how the benefits got spread around.
09:46Right? The technology doesn't naturally do them. What's really interesting is we're gonna have a similar fight here.
09:50Right? Like AI, we already have good data. Right?
09:53AI is pretty good at being a doctor. It's getting better being a lawyer all the time. Like, most lawyers I talk to see a trajectory where not too long from now, you will be able to get as good advice for not the most complicated issues from AI if you're not already.
10:05Right? And there's ongoing debate about this. But the thing is lawyers are not going to be quiet about losing their jobs.
10:11And And it turns out a lot of congress' lawyers and a lot of people don't have any money are lawyers. And I'm willing to bet that you're going to see laws passed in every state that you need to have a lawyer officially, a human sign off as even if they're worse than AI. Right?
10:22Yeah. So part of this, like, there is a little bit of, oh, it's your come up in white collar workers, but it's also like, no. No.
10:27They've got the like, their their fields are not gonna go easily. Right? And and, you know, doctors, lawyers, it's gonna be interesting.
10:34Coders really do not have the protection that doctors or lawyers or actors or other kind of guilds or associations do. So we'll see a lot of conflict over these issues in the near future. Lobbying for our own interests is not a new thing.
10:46So for example, for years,
10:49there have been people who try to raise money for the government, you know, where we can get more income. The the average lifespan of a dollar bill is about one year. The average lifespan of a coin is something like thirty years.
10:59And so the proposal to move dollar bills to dollar coins because it would save the government, you know, untold billions per year in printing and all of the rest of it. And the reason we haven't done it is because of the ink and paper lobby because they like those billings being spent on them to make new dollar bills every year.
11:16And so you know we're used to doing things that are not to our advantage because of lobbyists
11:22and this is just another thing where those who have access to power and those who who have influence will protect their interests as you said. And not necessarily badly. Right?
11:30Do we want all lawyers out of a job? Is that open question? A lot of people will be like, yes.
11:33Yes. Please. But like, you know, I I mean, already actually, there's some early evidence that the number of cases being submitted to judges is exploding exponentially where people are pleading their own cases with AI law.
11:45And, like, how do you deal with that? It used to be that we had a filter. Right?
11:48So the secondary thing is you had to convince a lawyer to take your case. And if they did a bad job, they would be punished. And if it you got a 100 page legal brief, a person wrote that.
11:56And that was an indicator of real effort, but now it isn't. How do we deal with that kind of system? So we're gonna have all of these ripples and all kinds of areas that will require policy changes, regulation changes, societal changes even if we don't have sort of a apocalyptic AI event the way we're talking about earlier.
12:11So let's let's go from the theoretical to the practicals. And as we sort of said before, which is a lot of people who aren't technologists are underutilizing or or misutilizing this this remarkable technology.
12:23Some are still using it as a glorified Google. Google to search. This is more of an answer machine, but still it I I mean, we all do that because it is a very simple and fantastic use case.
12:33The more nuanced and complex prompts, I think I know I'm under utilizing. Like, I ask for an answer even if it's something that has some depth, but I don't ask it to write a report or make an interactive, you know, dashboard of the data that I'm not I know that I'm not doing that and I'm already ahead of some in terms of my utilization of the thing.
12:55I have two two questions. One is you're teaching students. You're teaching a lot of grad students at business school.
13:01Is it a false belief that just because people are younger, they're all in on this technology or are they also sort of bumbling and fumbling their way as they as they learn about it? So we actually have a paper on this. Like so I think when people think I hear this term in the Internet.
13:14We're talking about digital native all the time. People talk about this. Right?
13:16Like, kids these days are good at using the Internet. And indeed, like, if you talk to somebody who grew up with TikTok, they will know all these intuitive ways
13:24that, you know, as an older person, you will not understand. Like, oh, that's cringe. There's a bunch of rules and slang and approaches that you wanna take.
13:30And I think that that model kinda carries through. Younger people get the technology. It does not hold for AI.
13:35Like, I talked to, like, a CHRO. Was like, oh, the kids these days, they're they're AI native. I'm like, they're not AI native.
13:40You're just talking to Claude. They're conduits to Claude. Like, if you ask for a report, they'll give you a beautiful report.
13:45They have no idea what's in that report. How could they? They have no knowledge of this.
13:48They're just giving you what Claude says. And we actually found some evidence on this when we did a study of BCG at Boston Consulting Group. We found junior employees were often much worse at using AI.
13:56They seemed like they were using it while they were adopters. But how could they judge whether something was good or bad? I think this is a rare case for the more experienced you are and sometimes the older you are, the better you're going to be at using AI if you decide to use it.
14:08Because you can intuitively grasp how do I give instructions. AI works enough like people that if you give an instruction and you're good at a field, good to be like, no. No.
14:16I understand what went wrong there. You're thinking about this. You should be thinking about that.
14:19Even though the AI is not a person that doesn't think. You'll know what kind of information to expect to get good answers. So I think actually experience really does matter.
14:26If you think about how our education is built, we're we're actually schools are in chaos. I mean, they're always a chaos. Right?
14:30Universities have always been in chaos. This is not new. You know, people are cheating with Chatty Wiki, but we actually know the pathway forward.
14:36Right? Like, it's gonna be a little bit messy. It's been like we'll do in more we did this with calculators.
14:40We'll do more in class assignments. Outside of class, we use AI tutors, which are to be very effective and controlled experiments. We'll make them work better than we do now.
14:47In class, we'll be active learning. We'll figure it out. I'm not worried that we can't figure it out.
14:50I am worried about the next stage. I I teach people to generalists at Wharton, and they become a specialist, same way we've taught specialists for four thousand years, which is apprenticeship. Right?
14:58I send them off to work for whomever. Right? They go work, you know, they go work at, you know, Bank of America or whatever, and they learn the job, and everyone gets a good deal.
15:07They get a little bit of income, but not as much as they would probably deserve. But they get a chance to prove themselves, and they learn the ropes by doing grunt work over and over again. The middle manager assigns them grunt work that they don't wanna do anymore and gets to evaluate whether this person's any good or bad for moving up the ladder.
15:21And it's been a great mechanism, and that just broke. Right? Because every junior person knows less than ChatGPT, and they would rather just use ChatGPT.
15:29They'd be kind of dumb not to use ChatGPT or Claude to give you answers because it's better than what they could do. And every middle manager would rather delegate to the AI than a flawed human who takes forever to give them an answer, and it is as good. And so everyone's just doing AI work to each other.
15:42And I think that that is the only problem that you're talking about here, which is the danger is that we lose the talent pipeline. There are solutions to it, but they're going to require fairly radical change in how we think about talent pipelines.
15:53How much of this is kind of like art? And and and here's where my brain is going. Right?
15:57Which is I am an art fanatic. It's the thing that I love more than most things.
16:02And I am totally fine with AI making art. It doesn't bother me.
16:07I'm totally fine with AI making music. It doesn't bother me. However, when I hang something on my wall, I like knowing that a person conceived of it.
16:16I like knowing that a person made it because when I buy a piece of art I'm not just buying the visual thing on the wall I'm buying the story that goes along with it. Or for example I was listening to some music this weekend, uh, I was listening to John Batiste's Beethoven Blues album which is if you haven't heard it spectacular.
16:32Now could AI make a blues version of a Beethoven sonata? 100% it could, but the joy that I got from listening to that music was not just the music that I was listening to, but I was smiling that a person had the creativity to to come up with this and that was part of my joy.
16:51When we look at the work product, you know, there's two things we're we're neglecting which is I like thinking. I enjoy debate.
17:01I enjoy making my head hurt at difficult things. I enjoy learning.
17:07The same way a painter likes painting and a musician likes playing music and and composing, where is the human desire to want to learn? And then will our schools but especially our places of work allow for that to happen or they all become so obsessed with efficiency that we actually
17:26even if we wanna learn you you see where I'm going with this. There's 10,000,000,000 directions from here. Right?
17:31So I wanna put a pin on the art thing because it's actually really important and interesting, which is, you know, obviously, there might be a rise of our more artisanal human made things. It's more the most direct version by this, by the way, is when you have AI in poetry or long form fiction, there's often a lot of things wrong with it.
17:46But because we're used to if we read something that reads beautifully and it's effortful to read, we assume that there's a purpose behind it. So we spend our own effort figuring out the holes.
17:56Like, for example, the AIs are very famous at weird analogies. Right? So it might say this conversation is like a gap tooth smile.
18:03Now that is not meaningful, but if you spend some time thinking about you're like, oh, how is it like and then you will reach a feeling of meaning. Right?
18:09If that was, you know, Laszlo Krasnikov or someone else writing this set of stuff, and I was reading it, I'd be like, oh, this person thought hard about that analogy, and I should spend the work to do it. If it's the AI doing it, you know, in some ways, it's beautiful, but the meaning comes from me. And am I being cheated because I have to create the meaning that has no intention?
18:26The intention the intention no longer belongs to the artist. The intention now is shifted to the to the listener.
18:32Viewer. Right? And maybe it always has.
18:34Death of the novel stuff. But, like so that's one angle that's kind of interesting. Right?
18:37And then I think the sort of second one is, you know, is I'm thinking about developing some of these kind of you know, how do you develop intuition? And we actually have a way of doing that. We we know how to train people.
18:46Like, we could teach you with the experts, but the problem is it's effortful. And so, you you know, like, there's always been this sort of view that I, you know, I told you early on. I make I make games for education.
18:57And one of the most depressing things you learn is you can make something incredibly fun, but first of all, it's only 80% fun. It's not as fun as actually doing a thing for fun. And second of all, learning is effortful.
19:07And if you're not doing effortful work, then you're in trouble. And now for the few areas that we intrinsically care about for you, you know, it might be art history or music or maybe for some people, it's math and science. Maybe for some people, it's, you know, it's a sport they care about.
19:19Whatever you we are effortful about and intrinsically motivated, you're like, why isn't all learning like this? And the problem is you don't care enough about it. Like Right.
19:26And so but I still want you to learn math even though you don't wanna learn math. I still want you to learn American history. And and if you shortcut that through AI, giving you the answers, you learn nothing.
19:35We we've enough experiments to show that. So making people essentially lift mental weights becomes the problem in a world where you there are shortcuts. You know, I find there's a great irony in all of this, is the problem actually doesn't lie with AI, which is we've been on the steady drumbeat, this this path
19:51to this point where we are, you know, discomfort avoidant. The concept of ghosting is is a thing where you just avoid a difficult conversation or you see it now, uh, particularly among young people where they're more comfortable with quitting a job than having a a difficult conversation or getting negative feedback.
20:09And and then the idea that we become so end result oriented, you know, as as capitalism has become short term focused and more focused on a shareholder supremacy, shareholder value over the quality of the product or customer satisfaction or employee satisfaction, you start to see we become more results oriented and we've left out the work product.
20:30This is not a new concept. AI is just the most exaggerated form of being results obsessed at the expense
20:37of the effort, the work, or the journey to get there. Well, and and just to take another path from that, I mean, part of this is what makes AI at work so challenging. Right?
20:46Because if you want productivity gains, you just you'll get a 100 times more PowerPoint. Right? Like Every day.
20:51If my job is producing PowerPoint, like so it requires you to rethink what the work is. Yeah.
20:56And so what the work product is can't be the same thing. I mean, even the most basic way, coders can write a 100 times more code than they could before. If they are embedded in an organizational process where it takes two weeks to do, you know, a product sprint as they as they often call them.
21:10Right? So each there's stand up meetings every day, and the assumption is the coder will write x number of work. The product manager will do this.
21:17The designer will do this. The marketing people will do this. And suddenly, one person's a 100 times more productive.
21:22What does that even mean for an organization becomes a problem? So part of this is our systems where coming back to that theme we've been developing throughout, which is human systems are not built, uh, for an AI world.
21:33We have we're effort you know, school wasn't built for a place where anyone can write your essays. Right? Like, you know, like, work wasn't built for people to be able to produce PowerPoint on demand without thinking about it.
21:43Right? Fiction wasn't built that I could write as many papers. The law clerks and courts weren't built for anyone to be able to bring up a case.
21:49That's not a problem. That happens in every industrial revolution. It's just all happening at once everywhere.
21:54And sometimes the AI wins, sometimes human systems win, sometimes we both lose,
21:58but that's where I'd watch the adjustment happening. I'm gonna go backwards a little bit here. Let's go back to practical, which based on classroom and in the in the business world because I know you study that as well.
22:10What are better simple ways that we could be using the technology available to us? Like I said, most people are miss or under utilizing the tool and, you know, I'm overwhelmed by the people giving me advice as how I should be doing things and what I could be doing.
22:23But, you know, from a from a just a a basic standpoint, how can somebody level up just one to 10%?
22:32You can get more than one to 10%. I take no money from AI labs, you don't sound like a I don't sound like a shill, but you have to end up paying $20 a month to one of the big three companies is what I recommend. Either Google's Gemini, OpenAI's ChatGPT, or Anthropix Claude.
22:45And you have to actively pick the best model available at that point, which is what you'll have access to what are called thinking models. And those will change over time, but you have to actively select that. It defaults to a lower one.
22:55You will get huge impact improvements just from picking the most recent model and using it. The second thing I would say is AI has gotten quite good. So there's kind of three phases of AI.
23:07There's prior to ChatGPT where mostly we talk about AI, we'll be talking about how you use, you know, data analysis, basically. There's all this color about algorithmic fairness and price mining and all the like, you know, customized pricing. All of that came from prior to ChatGPT.
23:20Then ChatGPT kicked off generative AI and what I will grandiosely call it because it's out of my book my previous book, cointelligence where you'd work back and forth with a chatbot to get an answer. Right? I typed it in a chat, it would give me an answer.
23:31Now we're in a new phase which is called agentic AI. And it's really just three or four months old practice. What does that mean?
23:37What does that mean? An agent is an AI system that can independently go do work if you ask it to. So AgenTic is just the the adjective of agent?
23:45Agent. Right. So AgenTic is an AI agent, and there's marketing terms around it.
23:48But it's an AI that can do work. The most important thing to realize is how good the work is and how long the work is. There's this paper by and test by OpenAI, so you always take with a grain of salt, but I've there's been independent enough assessment.
24:00I feel good about it. Called GDP Valve. And what they did was they took people representing 5% of The US economy, so journalists and product managers and lawyers and private investigators.
24:11And with an average of fourteen years of experience, they had them each create a really hard problem that they face in their field. They hired another set of people with fourteen years of experience to do it. Took them on average seven or eight hours to do the work.
24:21And then they had the AI do the same thing, took about fifteen minutes for the AI. Then they had a third set of experts come in and spend an hour evaluating the outputs from each of these, not knowing whose is whose and voting on which they liked better. And when this came out a year ago, the best AIs in the world were getting about 48%.
24:3648% of the time, they were tying or beating humans. Then the latest models as of when we're recording this are about 84%. So 84 of the time, the work that they do, seven hours of human work are equivalent to or better than a human.
24:49What that means, going back to the practical pieces, you would probably save three times effort and three times cost if every complex job you'd give it to AI.
24:59And even if it took you an hour to put it together and evaluate, even if you had to give up 30% of the time, you would still save time and effort. So one of the things I think you're doing is not using AI and giving it hard enough tasks to do. Okay.
25:11And and so that's the other thing, is the value of the AI that where efficiency is not how quickly it can solve the problem, but how quickly you can evaluate
25:19whether it got the problem right. Which again brings back to expertise. An expert can look at this right away and be like, not just as wrong, but, like, often it's wrong because of a specific problem that you should have either specified better or the AI is stupid about something.
25:32And sometimes you can instantly get, oh, it's never gonna get this because it's too subtle and I can't communicate the point. I'm just gonna do this myself. But sometimes you're like, oh, yeah.
25:39Yeah. This is a rookie mistake, and I should remind it that when it writes articles to not just factually explain everything, but explain it with a story or whatever your thing is, and then it's better. Right?
25:48So evaluation, feedback,
25:51these are things experts are good at and the AI responds really well to that. Here's the other problem which is I remember when I wrote my first book. Right?
25:58Everybody told me, everybody in the publishing world said the most difficult thing for any author is quote unquote to find their voice. Right? To have a voice.
26:07Now it's a very hard concept to understand, you know, what voice is. Essentially it's when you read my words, they are of me.
26:16They might they're my personality. They're they're my point of view. It's not just nicely written but it is it is of me.
26:23Right? And it's very hard to do for an author. And I found that AI can write beautifully but it has no voice and if you ask it to have a voice it's gonna always have voices that are available to it in the in the world in other words published people but not you.
26:41And so most writing will start to just sound the same. I mean I'm already seeing it.
26:46I'm getting AI generated emails in my inbox
26:48and they're all basically the same email. It's not x, it's y. It's doing the heavy lifting here.
26:53The thing that keeps me up at night Exactly. Know, this is a load bearing argument.
26:59The staccato three sentence, but you know, word word word And I started to just delete them all because they're all familiar.
27:05Yes. It's And none of them stand out. Right.
27:08And I pushed back. I'd say it's not that it doesn't have voice. It has a voice.
27:11Right? A singular voice that is It has a voice. A chatty bitty voice.
27:14And it's actually not a bad voice. Like, if I was get if I didn't see it for But it's not your voice. It's a voice.
27:20I know. It's a perfectly good voice. Right?
27:22It's a little dramatic. It's just sometimes it's like it it loves transitions too much. Obviously, loves, you know, em dashes too much, but it's not your voice.
27:29And that is another thing that is, like, developing your voice. Now a lot of people can't. Right?
27:34Like, not everyone's a good writer. No matter how much we teach the writing, they don't get it.
27:38Ghost writers have been around forever. Right? I'm glad, you know, that writing is something I do and have established voice.
27:42I know plenty of people who use ghost writers to do their kind of work. I agree on the AI voice. Now I will say you can get it significantly more like you, not for the kind of long form work of a book.
27:53But a tip here, if you wanna do this, is give AI a large sample of your writing and then say, write two pages summarizing the style of this and the instructions on how to write in the style.
28:06And then you paste that into your custom instruction, you say write in the style. It will not it will be slight parody of you, but it will be infinitely better than if you just say, you know, write like this famous person.
28:17Right. I I mean, I did something recently as an experiment which is I walked around the living room just talking into Claude and said, write an op ed in the style of Simon Sinek.
28:29Here's the idea. And I just walked around the living room for about three or four minutes and then it gave me a pretty remarkably written article.
28:39Then I said fact check it and it said well that's wrong that's wrong that's wrong that's wrong. I said okay go offer me what I could say to make it factually correct. And the thing that I enjoyed about doing it which is you know it takes 80% of my time to make a shitty first draft.
28:58And then editing is reasonably efficient and a lot more fun to really just clean something up. Most of the time is the is the first draft.
29:08Right? And so here I got a shitty first draft in a few minutes and then I sat down and with it, you know, it fact corrects it which is so efficient.
29:17Didn't have to go do all the research myself. Although I did double check all the research just to be sure. As you point out, the error rates of these things would drop.
29:24If you use a modern model it's not making mistakes the way It's not making mistakes the same way. I have to say it was actually kind of fun to edit it in my voice with my sense of humor and the last finishing touches I realized I could put my voice. I was pretty impressed.
29:38I was pretty impressed. Now, I could cheat because I have written enough that it can know my style and I wouldn't say it was perfect but it was it was scary good. Yeah.
29:48I mean there's a few things going in there. One of those is this idea of disruption to writing. And I mean, there's cost to everything.
29:54Right? So one option of writing the crappy first draft is it's your crappy first draft. So I always recommend some crappy first draft because otherwise, the AI's ideas will take over your ideas.
30:02It's very good ideas and you're you like, you will find you can't brainstorm. But with that said,
30:08I find this kind of a similar loop of, like, editing is a weird way of approaching it. But, like, it's not how we used to do it before, which is, like, I can get something written in my form and then I edit it. You know, I'm sure some writers have worked that way for years, but Yeah.
30:19That's a disruption to writing that might be better. Right? It might be where it's hard to know.
30:23It's something you're a factory, you know, producing first drafts that, you know, took all the time. And or maybe some people are just really good at editing, and they weren't good at draft writing, and suddenly they're more productive than they were before. I think this is one of the future jobs that we under appreciate which is not just that jobs are new but that the weight of the job will shift.
30:41Yes. To your point
30:43you know we've always celebrated the writer and editors have always been like just there. If you work for public relations or you work in magazines like the person who's the writer who wrote the press release, they're the person who went to school to write the press release and we just sort of like the editors are just the the lower paid you know Right.
31:00Right. Right. Right.
31:01You know failed writers, you know, quote unquote. But now I think the writers
31:05I think that the balance will shift. I think we're gonna see the cross of lots of jobs, by the way, to come back to the job thing. So jobs are many tasks.
31:12Right? A writer does like, as a writer, you're in charge of writing and editing and fact checking all and the AI does some of that work. Shifts the burden of what you do, but it doesn't take away everything.
31:20And I think what we're gonna see in a lot of jobs is this idea of bottlenecks, that the AI is good at some stuff but bad at other stuff. We I we call this the jagged frontier of AI in our early papers on this, which is it's good at some things, bad at some things you wouldn't expect. Where it's bad, right, writing perfectly in your voice, getting a joke right.
31:37Like, suddenly the demand for your labor is higher there. Right? And your value is higher.
31:42It might have been that your jokes were not what was getting you like, that was not your main deciding factor. But if you're better at jokes now, suddenly there's value. Same thing's happening in coding, by the way.
31:50It used to be that writing really clean code was a really good skill. Now the AIs write most of the code. Being an architect is good.
31:57Being an engineer manager is good. Yeah. The jobs change.
32:00What's important and what isn't important changes, and that changes who's good or bad at it too, creating new opportunities and new risks. You may have instead of a 100 coders,
32:09you might have 50 or 30 working on the team, but there's still human beings with egos and securities, you know, lack of sleep, all of this stuff. And there's still somebody overseeing the project who has to manage all the messy human stuff regardless of how good the technology is.
32:22I for one believe that doubling down on human is gonna become even more important now because we still have to take care of the people who are working on the products with their AI, uh, agents.
32:33Oh, absolutely. And and also when I went to the encoded in the past, I had to hire a company to do it. Now there might be a coder working for every two person team and more software is being created than ever.
32:42Right? So the jobs are unimaginable, and the future is sort of an annoying thing to say. I think it is annoying because I think we actually have some idea of what this looks like, which is not that coders are replaced by, you know, prompt engineers, but that the job of coding changes.
32:55The demand for coding shifts from giant organizations where a thousand people work together programming to now dispersed in your car dealership might have a coder building customized software for you around the what the managers want to the team. You might have two developers working for you rather than outsourcing web development that are, you know, evolving things.
33:13The nature of software and the jobs change. And I think that that is a missing piece of this puzzle also. And I think the other thing we aren't appreciating, which is the more things get good.
33:22Right? Because it used to be that quality would help you stand out. Yep.
33:26That if you were smarter, a better coder, a better writer, a better this, a better that, whatever it was being good at something made you stand out from the crowd. Right? If the quality of let's just say everything gets slightly higher or a lot higher then it commoditizes so many products.
33:44And so what I'm curious about and cannot predict and don't even have a thought about what happens here, but if everything just becomes generically good, then how do you stand out in a market now?
33:56And we've we've kind of seen this with the rise of social media. We're in the last generation that has movie stars. I think it's the death of the movie star.
34:03Nobody's really buying a ticket to go see a movie because a particular actor is in it. Like like one battle after another. You know lots of people went to see the movie, very few went to see it because Leonardo DiCaprio was in it.
34:16You know and that's what the movie stars used to do. They used make people go see the movie. Now we'd rather see the franchise.
34:22We're more interested in Marvel than who's in it And this is what I mean by commoditization. I'm so curious as everything becomes better and commoditized, TV channels, everything's commoditized.
34:34What's the thing that makes companies, products, and people stand out? So when you're interviewing for a job and everybody's good because of AI, how do I stand out and and get a job that's still that they still need to hire for?
34:48I'm fascinated
34:49by that. I think a few things are are there's a lot of things there again. Right?
34:54Part of this, by way, is writ large. Right? Like, if Claude is really good at running your company, Claude's also good at running every other company, and there's no variation between them.
35:03And generically high quality with no variation means there's no votes or competitive edge. I think humans who bring competitive edge to this one way or another just by providing variation if nothing else Yes. Is a useful way to think about problems.
35:15Right? Like, your sense of taste matters. Right?
35:18And presumably, why, you know, why people listen to you. It's like, your sense of taste of who to talk to, the kinds of questions you ask. You know, it's similar to the sense, like, do you like Rothko or do you like Rembrandt?
35:26Like, there's different tastes that have different kinds of outcomes. Yes. The second thing is developing taste, right, is a bigger issue, which is how do we get people to develop taste.
35:34It's usually a casual casual lifetime thing. That might be one of the new talents we teach people is developing a sense of taste, which requires, you know, experiencing broad things and making choices and having the vocabulary to describe your sense of taste and choices. I think that as people become bigger creators and they can do more, their taste matters more.
35:52Like, directors may end up mattering more than ever because I understand what I'm getting with a Wes Anderson experience. Right?
35:58And if he can direct the whole thing the way you wanted to, what would that look like? Yes. And we might find the same kind of thing with all kinds of other stuff.
36:04There's someone who has a particular taste in ice cream styles. Now you can make ice cream on demand because the AI will connect you through the APIs to a, you know, to a vendor that makes that product for you. So it kind of fits in of enabling one person to do much more.
36:17You start to care a lot more about the taste of that person than you do about the entire organization built to deliver the product. So good.
36:24I mean, I have my own biases and opinions, but I'm curious. Is there actually a difference between Gemini, ChatGPT and Claude? I know Claude has a much more b to b focus
36:35business model. That means security is more of a thing because business wouldn't stand for, you know, any lapses in security, maybe like customers might. Is there actually a difference?
36:45So there are. Just a half step back on the boring educational side of this. When you're thinking about AI now, you wanna think about three things.
36:52The model, which is the brains of the bunch. Right? At the time of recording this, that's Opus four seven from Anthropix.
36:58That's a Claude model, Chateappity 5.5, and Gemini 3.1 Pro. By the time you hear this, there will be slightly higher numbers on all of those things based on how things are going. Right?
37:07But those are those are the brains. Right? The better your AI model is, the smarter is it everything.
37:11It's better negotiations, better poetry, it's better math, it's better like, but that's the brains. Then you wanna consider apps.
37:18Apps are the tools you access these. For most people, when I say app, what they should be thinking of is chatgbt.com or claud.ai or gemini.google.com.
37:26That is an app. But the apps that people increasingly talk about when they use AI are things like Claude code, OpenAI's codex, Notebook LM, which you haven't used for, uh, Gemini is free and very impressive for research and gathering data. And those are very specific tools built for specific purposes.
37:41And then finally, there's what we call harnesses, which are how the AI can do things. Right?
37:45So a harness lets the AI write code or do Internet searches or make images for you. So right now, the three big companies all have roughly equally good. We'll probably, you know, jockey from position.
37:55Yeah. They're all making very good brains. The models are all very good.
37:59Right now, Google has a, um, the most diverse set of products of apps, but their main apps are probably weaker than Anthropic or OpenAI. And they have worse harnesses for the main app.
38:12So if you wanna use AI to do things, right now, the most powerful tools are Claude Coder coworker on your machine if you're using Anthropic or OpenAI's, um, Codex tool. And what makes those different is they sit they use your computer.
38:25So, like, you can give it access to your files, to your email. It can, you know, it can do work for you using your machine, your web browser, whether you like this or not.
38:34Right? Um, and and do work. So because of that, those two are kind of jockeying back and forth for the lead, but all three of them are quite good.
38:42The models are good across all of them. So now let's talk about security. Right?
38:45So we're all tired of Meta and all the other companies,
38:49you know, filling our computers with cookies, tracking our every movement on every website even after we've left their website and their product. You know, we've all become very sensitive to turning off cookies and data privacy is now a thing.
39:01You know, do I wanna give any of these AI models? Do I trust any of these companies to have access to all my computer, all my browse history, all my finances, etcetera, etcetera, etcetera?
39:11So it's a hard question. Right?
39:13I mean, there there are more secure versions where you can even run your own version of these tools, but they will not be as good as OpenAI, Anthropic, and Google's. There's a couple kinds of security concerns you might have.
39:24One of them is, are they taking your data and using it to train their next model? If you pay $20, all of them have an option to turn off that training feature. Is that enough privacy for you?
39:33It's hard to know. Right? There's open questions about whether or not someone's AI history will be searchable.
39:39Is is it, you know, is it something that lawyers can demand to look at it, right, discoverable? There's open questions about, you know, what will companies do with this in the long term even though they sign agreements with you. But on the other hand, you have Gmail probably has all your email in it.
39:50Right? Like, these look like enterprise software applications at this point rather than sort of invasive individual tools. So do you how much do you trust, you know, Google with your information or Instagram with your information?
40:01We're in that same kind of boat over again. The difference is is as much as I don't want Google to have access to my Google, my email, I know that it does, but I know that nobody can go out onto the web and and ask a query in in a Google search to read my email and tell me something.
40:20I think a lot of us are afraid
40:22that somebody could just go on to chat GPT or open, you know, one of the others. You can't do that. They are not there you there's no it's just like Gmail in that way.
40:29Right? There's no bleed over where there's just one giant inbox and you're just barely holding it together. Right?
40:35It works the same way. I mean, it looks like enterprise software. So that has its own risk.
40:39Right? But the basic risk of, like, can someone just ask for something and get access to your chat GBT? No.
40:44If they log in with the you know, you have to do all the same things you do. Set up Got it. Two factor authentication.
40:49Don't leave yourself logged on to a computer. But it works. I the analogy I would have is Gmail.
40:53Right? Got it. Like, Google has all this information.
40:56They're obviously processing it and using it for their own purposes, but they're also not going to you know, they've anonymized it in some way to try and create trust. It takes effort to hack into someone's Gmail.
41:06It's the same kind of boat. Right? Now whether or not we want you want a company to have even more power over you, those are choices you get to make.
41:11But I don't think we should put this in a separate privacy category. The actual risk is if I let it have access to my computer and it could use my web browser, you know, could someone convince my AI to send them all my money if it's, you know, if it's reading all my emails?
41:26And that is you know, hasn't happened yet, but it's not impossible. Right. So obviously because you are, you know, you teach this, you embrace this,
41:34you allow your students to use it, I assume. I don't know how to ask this which is how do you ensure that your students are learning if they are allowed to use these tools to learn?
41:47So I went viral first in education with my syllabus right after Chatchiwiki came at the first version, which uses what we call GPT 3.5. And, you know, that was around for a few months. GPT 3.5 was pretty flawed.
41:58Like, would make up arguments all the time. It would obviously hallucinate. It felt like a, you know, like a smart, you know, ninth grader or something like that.
42:05Right? And so I teach college courses. I could tell.
42:08So I my original policy was use AF everything you want. You're accountable for the output. That was great for four months until g p d four came along, um, which is now obsolete.
42:15It wasn't good for a while. And it was as good as my students across some things, not across all things, but enough that a low effort student was was worse than g p d four. And I can no longer tell people, just use AI.
42:25I can tell. Because the AI was giving them the answers, not being the answers. And we've seen this over and over.
42:30There's a lot of studies that show if you just use ChatGPT to get answers to questions, you think you're learning. Even if you're not cheating, you think you're learning and you're not learning because the AI gives you the results.
42:38But turns out we actually know pedagogically how to solve this problem. We did this with calculators, right, within school, which is we could do in class testing. We can make you use the AI for some stuff and not for others.
42:48So for my classes, I'm not going to cheat entrepreneurship. So output is in some cases, like, I I gave all my students, for example, what I called the VoitComp test, which is the name of the Blade Runner human test, but I made my own version of it. And they had to launch their startups using AI, but based around areas they were experts in, experiences they had had, knowledge of the world they had had, a viewpoint they had, which kept them in the picture.
43:12And then they also had to do a lot of in class stuff. Right? We had to have a discussion about these things.
43:16I actually had them use AI tutors that asked them questions. They had to use an AI to build a case study with and I set up the AI so it won't give them all the answers. It would challenge them to come with a case study information.
43:26So there's things we can do, but it does require changing how we teach. But the reality is technology does affect our brains. Like, I mean I'll give you a I'll give you a real life one to one example.
43:37Right?
43:38My I my mind, I used to have a steel trap for phone numbers. I knew everybody's phone number.
43:45You told me gave me a name, I'll tell you their phone. I I didn't have to memorize it. I just heard the phone number and I had a steel trap of phone.
43:50It was just it was just how my brain worked. And I in the early days of I bought a Casio digital diary. I got it for my birthday.
43:57I remember, you know, it had two k of memory. I think I upgraded to the six k when it came out. It was like hardcore.
44:03Right? And it was the most remarkable thing and I programmed all the phone numbers from my memory into the device and then slowly added more and more phone numbers as I learned them. And my brain was like, okay, if that's what you want, fine.
44:17I can't remember a single phone number anymore. And if we have to remember that they're like the Iliad and the Odyssey were oral traditions.
44:25Yes. You know, this book that we were forced to read in school that's that's like in 800 pages, you know, go back a few know a couple hundred years and it was like, son it's time I tell you the story of the Iliad and you will tell your son the story of the Iliad.
44:40It was an oral traditions that people remembered but because the printing press our brains just stopped remembering stuff. So this has to have an impact on our intelligence.
44:51There's no getting around it. I mean, absolutely. I mean, my my grandfather
44:56was an engineer who built like the fire suppression systems for Cape Canaveral and his, like, dissertation was writing doing a single piece of matrix multiplication. I have no idea how to do what he just did, and he did slides rules to do it.
45:08I've known how to use a slide rule. My kids have not learned cursive. Right?
45:11Like, we give up stuff all the time. The whole idea of technology is on purpose. We give up things that we used to be able to do Yes.
45:19To machines so we don't have to do them anymore. And Agree. Every time we face the same choice about what's valuable and what's not.
45:25And what I worry about, like, the the default version of that is bad. Right? I mean, we've seen this happening with, like, you know, you could argue short form video has killed reading because it's more entertaining to do that.
45:34I don't need to spend the effort reading the book to get there. Okay. That was a bad choice.
45:38We are going to have a ton of these choices, right, around AI. It doesn't hurt your brain, but it is a choice that you can hurt your brain with.
45:46Right? As an educator
45:47Yeah. Part of my job is to get around that problem anyway. Yeah.
45:51People could survive a lot without reading very well. They could survive pretty well without doing math. They don't have to learn American history.
45:56Like, there's some degree of of making this a requirement. But but but this is a slippery slope. Right?
46:01Because now now we go down the path of, oh, you don't need university. There's a whole movement that you don't need to go to college. And what we forget is you may not need the subjects that you learn at college, but going to higher ed teaches you to think critically.
46:15It teaches you to to argue with people who have way more education than you and form strong arguments to take them on. It also teaches you adulting and so my problem isn't that technology replaces that that there are sacrifices.
46:29Like I accept that I don't have to have a memory for phone numbers because of technology anymore. That that that I accept that.
46:36My concern is that thinking, the ability to think is the sacrifice here and that's way more damaging
46:45than than remembering phone numbers or the, you know, remembering the Iliad. So I pushed back. I don't think it destroys your ability to think.
46:52I mean, I think for a lot of people, it gives them even more ability because they have a conversation partner at their level who's willing to discuss a topic. As long as people have any curiosity about the world Okay. All of this is prosthesis for the game.
47:02I mean, books were Yeah. Yeah. Yeah.
47:03Someone else came up with an argument for me and opinion. That doesn't mean that there aren't negative effects on that. It doesn't mean we won't give up things we shouldn't give up.
47:10Part of what hearkens me is like we've got twelve to sixteen years of school, you know, schooling to try and get some of this right.
47:18And if we do it right, AI accelerates some of that. And if we get to make choices as a society now will people make bad choices? Yes.
47:25And so I do worry about this. Right? I'm I'm thinking a lot about how we what do we give up?
47:29How do we stay human? It's gonna require effort just like a lot of other things. And there is danger there.
47:34But I guess I feel like that feels like a big leap to we're not gonna think anymore. The AI will tell us what to do. We'll just obey its instructions.
47:42I don't think it will stop thinking. I think it'll hurt thinking. Like, the quality of thinking, critical thinking gets hurt.
47:47And I mean look, you know this as as somebody who studies education. You talk to any college professor and they'll tell you forget about AI. Just the introduction and distractibility of a phone, you know, that they'll say that, you know, the writing is abysmal these days.
47:59College professor is complaining about the writing being abysmal so kids don't know how to write. And when I say write, don't mean like but I mean form an argument and they'll say like the first paragraph was fantastic, second paragraph was fantastic, the third paragraph was fantastic. The problem is the paragraphs have nothing to do with each other because it's clear that they're like getting distracted in between paragraphs.
48:19I guess I would say, on one hand, you're right, but we've been very bad at education for a long time. Like, a bad way to teach is stage on a stage where I go up and give a lecture, Right? And a 100 people write things down.
48:28But we've done it for a couple thousand years because there's a lot of other constraints that make it the way we do work. There is a negative side, but I like, one of the things that really excites me is AI tutoring. We have some early evidence that has big effects on learning.
48:38Right? Mhmm. Like, instead of me lecturing to a classroom and assuming the height of learning is I lecture to what?
48:44The upper part of the classroom, people who really know is it the middle. I, you know, I I lecture to the person who doesn't know things as much. Personalized education is now an actual possibility.
48:52Like Yeah. For there is a cure as well as a poison in the in this thing. And I think that it's worth paying attention to both.
48:59Like, if we don't change anything, the effects will be bad on education. Right? But that implies that we're all gonna sit down and just be like, I guess it's done.
49:07You know? Like Yeah. And I don't I think for the first time, as opposed to short form video where you had to do this very elaborate thing of like, we'll do TikToks for education, and that never works.
49:15We actually have a tool that is a pretty good tutor that can talk to you at your level, that can make you get into an argument. That's part of why do my classes. And we see schools adapting.
49:24Right? First, they put computers in all the schools and now they're slowly taking them out. And it was partially because we just like, it comes back to the human thing.
49:30It's like, the thing that makes AI interesting Yeah. Is it understands understands in quotes.
49:35Right? Uh, for those who are just listening to this, I'm making air quotes in my It it understands humans.
49:40It has theory of mind effectively. And that's what the other technologies don't.
49:44Like, it can teach to your level. It can understand what you're confused by.
49:50It can help you make this interesting for you if your only interest is basketball or, you know, basket weaving. It can give you basketball and basket weaving analogies and problems.
49:59This was the holy grail of education. And I think it's one thing to say, yeah, technologies have lit risk and everything else. I also think we undersell some of the impositive impact that we can get from this.
50:08The strong argument that you're making here is and I don't know how many people have done this, which is where you use the talk function where you can actually have a conversation backwards and forwards with the AI as opposed to typing. And I think the case you're making is the idea and I like is that you can debate with someone at your level.
50:22So you're not explaining to somebody who's not at your level. You're not feeling dumb or trying to keep up with somebody who's more experienced or smarter than you but rather that you can go backwards and forwards and and learn it the way you like to learn. And I I've tried this where I I'm having a debate or conversation backwards and forwards backwards and forwards backwards forwards and I'll say things like, oh wait, or is what you're telling me this?
50:43But I think this, that I think is really really interesting to your point. There's two other tricks there. One is the AI sycophantic.
50:50So if you're having a debate with it, it's gonna agree with you. So you have to tell it to act like a critic. Right?
50:53Like Yeah. If you say and then the second is you wanna take advantage of the meta piece also. The learning piece of saying, actually, halfway through tell me what I'm doing wrong with my arguments.
51:01How can I be more persuasive? What patterns am I missing in discussion? Give me some examples of those patterns and how I could have used them.
51:08So, again, pack the effort piece. If you're willing to do the lifting yourself of asking the questions Yeah. Like everyone always says, they wanna come to office hours and have this debate with professors.
51:17That's most people don't come to office hours. You sit as a professor, and you're waiting for somebody to come and debate to you in the great issues of the day, and you sit alone in your office during the hour that people are allowed to come to you because they have other things to do. I think that we overestimate how this this sort of shining city in a hill where we'd sit down and debate and have these discussions.
51:34Like, that's not how most things work. Now we have a tool that can do that. If you're interested, you can do that without having to come to my office hours.
51:41I wanna double click on the two points you made because I think they're really valuable, which is remember that the AI is a sycophant and you've got to tell it to criticize or critique
51:49and
51:50ask it to evaluate your thinking and help make your thinking stronger. Those are two brilliant brilliant prompts that I think more of us should remember to improve the quality of our our interaction with the technology. We're talking earlier about AI and writing.
52:01A piece that was missing in your conversation, you're talking about user fact checking. It's very good at that. I would use it more for initial research.
52:06All of the AI models have a deep research mode that's quite good, um, and we'll actually do research for you. But the thing you're also missing from that is when I write something, I have the AI evaluate from different perspectives.
52:17So I will have the AI, like, read it through as a reader who doesn't understand much about this topic and tell me what I need to change. Read this through as an expert who, you know, who's out to get me on social media. Where would they nitpick my arguments?
52:29Right? Am I being irresponsible anywhere? Did my humor fall flat?
52:32So giving the AI the personas don't change the AI's ability. So you say you're good at physics doesn't make you good at physics saying you're a physicist, but it does make it talk like a physicist, right, or parody of physicist. Talk like a cynic.
52:44Talk like a critic. Talk like a naive person. You will get answers you couldn't get without going to a wide range of readers.
52:50Also true in entrepreneurship, by the way. Get feedback from the AI in different personas about your idea. This is very practical and very good.
52:57What are you actually afraid of? I think we're in for a period of chaos. Right?
53:01And does like, let's say the industrial revolution works out like the last three did, like the AI revolution. Yeah. Living through it still sucks.
53:07Right? Like, Charles Dickens is basically just a story about how miserable the industrial revolution was. Right?
53:12Yeah. Like, you have haves and have nots. You have social change.
53:15Even if everything works out fine, now we have better tools as society, but I don't see a lot of action. You've led this conversation by saying that, you know, people either doom and gloom or, you know Yeah. Or everything is gonna be great.
53:27I find policymaking is in the same place right now. Either it's all gonna work out great or we have to stop this whole thing. And neither of those are realistic outcomes.
53:35How do we help cushion people in on a way if they're unsure? Turns out training programs for new jobs never really work. Is there something we could do better this time around to, you know, reskill people?
53:44We're going to have negative effects on inform on, you know, deep fakes are going to be everywhere. How do we deal with who we trust for information? There's a thousand little good and bad things that are gonna be happening all at the same time.
53:56They're gonna be very complicated, and they're gonna get boiled down because of how social media and everything else works to either AI or bad, in which case you have a list of all these things that are a mix of real things, you know, and fake things about AI water use or whatever it is that and it's gonna be AI is bad or AI is great.
54:11And it is a thing. It's a technology and interacts with people. You know, technologies are neither good nor bad nor are they neutral.
54:17They have effects on our world, and I worry that we're not taking this seriously. The other thing I worry about is people don't know how good these systems are. They are better than you think.
54:24Right? I'm a I have a doctorate. I, you know, I'm a professor for a while.
54:28I published journals. Like, the AI writes a pretty damn good academic paper now, not just a parody of an academic paper if you give it a dataset to work from. It is proving math at a level where you really need to be one of the best math professors in the world to know whether the system is right or wrong.
54:41It's often right at this point. It is doing really good images and marketing work that beats most marketers and studies that we have of this. It'd be like, these are really good systems.
54:50Their development is not slowing down. So we have to start thinking about what we want the world to look like rather than just assuming it's all either gonna work out or not. And how much agency do we as the general population have or are we just the subjects?
55:02Are we just the pawns in this game between these three major companies, Microsoft OpenAI
55:07and and Anthropic?
55:09So I think that we have there's two levels of agency we have. Level of agency number one is societal. Right?
55:16Like, there's a reason why people are floating, you know, data center bands. Right? Because they think that'll be popular.
55:21The usual mechanism of policy making of of organizing, of of, you know, writing letters to your congresspeople, those still work. The second is where I think there's even more agency.
55:29The AI labs are full of coders, and they have found an unreasonably effective way of making a tool that mimics human thought. Like, it's weird the large language models work as well as they are.
55:39Like, we have we know that we're technically we don't know why this is so unreasonably good. Like, how can it do poetry and offer, you know, and, you know, interior decoration and write you know, and discounted cash flow analysis and, you know, a pitch deck about, you know, the Gettysburg Address.
55:53Like, it shouldn't be able to do these things. It does all of this stuff. So we give them too much credit.
55:57They don't actually know much about how AI is useful in on your field. Remember, there's a jagged frontier. It's good at some stuff, bad at some stuff.
56:03Your biggest source of agency is actually using it to positive use in your own job and work. Like, a large part of what I post about is, like, this is a way to help humans thrive with AI if we use it this way rather than just automating away human work. And I think our biggest sense of agency is, okay.
56:18You have access to these tools, you know, Simon. How do you use that to expand your business to make sure that all the people who work for you have spoken to some amazing folks. They're all really smart.
56:25How do they do more than they did before? How do they do more satisfying jobs?
56:29There's a lot of agency there. And then if you talk about it through your platforms, that changes things.
56:34And a lot of what I do is talk to executives and leaders of companies where I'm like, we have you have to show people how augmentation, how this can be used to make humans thrive, how it can make your business thrive rather than the default plan of, like, if I fire everyone or replace it with AI, profits will be higher. Like, that's the dangerous thing.
56:49So to me, the real agency right now is let's find positive examples, and there are tons of them out there. Use them and build them, uh, to make AI make the world a better place and not worse.
56:59I really appreciate this. Like, you've given me you've enriched how I can use this product. I I'm gonna take you on.
57:04I'm gonna have the the agency that you recommend.
57:07I think this is a moment for transformation. Yeah. And I don't and I think people aren't being ambitious enough.
57:12Everyone's like, what if I record my like, it's not, you know, how would you reach every one of your audience members separately if you could do that? And why don't you just build it rather than waiting for it to happen? Like, what is the gonna use it that way because I, like the artist,
57:25I take pride in the fact that when somebody's talking to me
57:29that it is actually me, my opinions. Oh, I I don't I don't think it's about automating Simon, like creating a Simon clone. I I never liked that.
57:37Like, there's people who create Ethan bots. I don't I don't think that's the way to as you're talking to a, you know, a fake version, a parody of yourself. I'm saying, what do I want people to accomplish in this world?
57:47Like, how do I build a tool for everybody? Yes. Based on my belief.
57:50And I I like I said, I would do assignment AI with a very specific application that it lives alongside. But I like people knowing that when they see me and they think it's me, it really is me. And that's I agree.
58:00I mean, it's the same thing with my writing. I write all my own, you know, my own Twitter posts and everything else. And Yeah.
58:05You know, it's important to keep the muscles alive if nothing else.
58:08Ethan, such a joy. Thank you so so much for taking the time. I really appreciate it.
58:11Thank you. It's a pleasure. As always, thank you for watching.
58:16If you liked this episode, please subscribe to Bit of Optimism for more interesting guests and even more interesting conversations. New episodes drop every Tuesday. But if you'd like more optimism right now, click here to watch another episode.
58:30Until next time, take care of yourself. Take care of each other.
The Hook

The bait, then the rug-pull.

The cold open is a question disguised as a worry: if AI makes everybody generically good, how does any single human stand out? Mollick's answer - that variation, taste, and point of view are the only edge left - is the spine the entire 58 minutes hangs from.

CTA Breakdown

How they asked for the click.

MENTIONED ON CAMERA
01:15linkOne Useful Thing (Mollick's Substack newsletter) ↗
01:15bookCo-Existence: The Next Phase of AI (Mollick's new book) ↗
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