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Godfather of AI: I Tried to Warn Them, But We’ve Already Lost Control! Geoffrey Hinton

16 Jun 2025 · 1h 37m · Steven Bartlett, Geoffrey Hinton · 25 quoted facts

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In brief

Geoffrey Hinton, a founding figure of modern AI, argues that AI is both hugely useful and dangerous. In the short term the biggest risks come from people misusing it: cyberattacks, engineered viruses, election manipulation, echo chambers and autonomous weapons. In the longer term, he says, machines smarter than us might decide they don't need us. He thinks nobody will stop its development, so the real task is working out how to make it safe.

The main tension is between Hinton's belief that AI will be wonderful in areas like healthcare and education and his fear that it will be uncontrollable and economically disruptive. He puts the chance of AI wiping us out at roughly 10 to 20 percent, calling that a gut guess. He is uncertain whether safe superintelligence can be built, but says the possibility justifies enormous research effort and strong regulation of profit-driven companies.

Key insights

  1. Most near-term AI risk comes from misuse

    Hinton separates risks from bad human actors, which he says are most of the short-term risks, from the risk that a superintelligent AI decides it does not need us. His misuse examples are phishing, engineered viruses, election manipulation, extreme-content feeds and lethal autonomous weapons.

  2. Digital minds can share knowledge far faster

    Copies of one neural network can average their connection strengths, so they pool what each has learned, at trillions of bits per second. People pass on roughly ten bits per second through speech, and Hinton says this makes AI billions of times better at sharing information.

  3. Hinton expects mass white-collar job displacement

    He argues that, unlike earlier technologies such as cash machines, AI can do mundane intellectual work, so one person with an AI assistant does the work of several. His example is a relative who answers complaint letters five times faster, which means five times fewer people are needed.

  4. Profit-driven companies need strong regulation

    Hinton says companies are legally obliged to maximise profit, which pushes platforms toward showing people more extreme content. He wants rules that make profit-seeking produce socially useful outcomes, and he notes that European AI rules exempt military uses.

  5. Safe superintelligence is uncertain but worth trying

    Hinton says nobody knows whether AI can be built so it never wants to take over, and he gives a gut estimate of 10 to 20 percent that AI wipes us out. He argues that the chance of success justifies putting enormous resources into safety research now.

Questions

Why is Geoffrey Hinton called the Godfather of AI?

He backed the idea of building AI on simulated brain cells (neural networks) for decades when few others did. Several of his students went on to lead major AI work, including Ilya Sutskever.

How likely does Hinton think it is that AI wipes out humanity?

He says he often puts it at 10 to 20 percent, but stresses this is a gut guess. He thinks the experts who say under 1 percent, and those who say it is certain, are both too extreme.

Which AI dangers does Hinton say are happening already?

He points to cyberattacks, which he says rose about twelvefold between 2023 and 2024, partly because AI makes phishing easier. He also names echo chambers on platforms like YouTube and Facebook, and early job losses.

Why does Hinton think AI is smarter than humans in a way that matters?

Because AI is digital, many copies of the same network can run on different hardware and merge what each has learned by averaging their connection strengths. Humans can only share a few bits at a time through language, and their knowledge dies with them.

What does Hinton advise people to do about AI and jobs?

He jokes that people should train to be plumbers, because physical manipulation will be hard for machines for a long time. He says individuals can do little beyond pressuring governments to force big companies to work on AI safety.

Facts

Stated by the speakers. Each quote matches the transcript, which shows what was said, not that it is true.

Geoffrey Hinton says he pushed the neural-network approach to AI for about 50 years while few people believed in it.

“I pushed that approach for like 50 years because so few people believed in it.”

0:05:59 · Geoffrey Hinton · Neural networks

Geoffrey Hinton says John von Neumann and Alan Turing both believed in brain-modelled AI, and that AI's history would have differed had either lived longer.

“Early on, von Neumann believed it and Turing believed it. And if either of those had lived, I think AI would have had a very different history.”

0:06:34 · Geoffrey Hinton · AI history

Geoffrey Hinton says cyberattacks rose about twelvefold between 2023 and 2024, which he attributes probably to large language models making phishing easier.

“between 2023 and 2024, they increased by about a factor of twelve, 1,200%. And that's probably because these large language models make it much easier to do phishing attacks.”

0:14:44 · Geoffrey Hinton · Cyberattacks · 2023-2024

Geoffrey Hinton says European AI regulations contain a clause stating they do not apply to military uses of AI.

“the European regulations have a a clause in them that say none of these regulations apply to military uses of AI.”

0:13:11 · Geoffrey Hinton · AI regulation

Geoffrey Hinton says he split his and his children's money across three Canadian banks to hedge against a cyberattack taking down one bank.

“So I spread my money, my children's money, between three banks, in the belief that if a cyber attack takes down one Canadian bank, the other Canadian banks will very quickly get very careful.”

0:17:42 · Geoffrey Hinton · Cyber risk

Geoffrey Hinton says a friend in Sussex had a drone costing under 200 pounds that could follow him through woods.

“I was visiting a friend of mine in Sussex who had a drone that cost less than 200 pounds, and the drone went up.”

0:30:33 · Geoffrey Hinton · Drones

Geoffrey Hinton says the object-recognition network was named AlexNet and the company he, Ilya Sutskever and Alex Krizhevsky founded was DNNresearch.

“the network that recognized objects was called Alex Net. The company was called D N N Research, Deep Neural Network Research.”

1:18:08 · Geoffrey Hinton · AlexNet

Geoffrey Hinton says he joined Google at age 65 after the company acquired his technology.

“I went at age sixty five to work at Google.”

1:19:03 · Geoffrey Hinton · Google career

Geoffrey Hinton says he taught a Coursera course hoping to earn money, but it earned little, which led him to sell his work to a big company.

“I taught a Coursera course in the hope that I'd make lots of money that way, but there was no money in that.”

1:17:07 · Geoffrey Hinton · Hinton's career

Geoffrey Hinton describes distillation, which he worked on at Google, as transferring the knowledge of a large neural network into a small one.

“distillation is a way of taking what a big model knows, a big neural net knows, and getting that knowledge into a small neural net.”

1:19:25 · Geoffrey Hinton · Distillation

Geoffrey Hinton says his closest moment to a revelation about AI's ability was when Google's PaLM system explained why a joke was funny.

“The closest I had to a eureka moment was when a Google system called Palm was able to say why a joke was funny”

1:19:56 · Geoffrey Hinton · AI understanding

Geoffrey Hinton says he timed his departure from Google so he could speak freely about AI safety at an MIT conference organised by MIT Technology Review.

“The precise timing of when I left Google was so that I could talk freely at a conference at M I T”

1:20:45 · Geoffrey Hinton · Leaving Google · 2023

Geoffrey Hinton says Google held back its large chatbots, possibly to protect its reputation, whereas OpenAI had less to lose by releasing theirs.

“When they had these big chat bots, they didn't release them, possibly because they were worried about their reputation.”

1:21:39 · Geoffrey Hinton · Chatbot release

Geoffrey Hinton says his former student Ilya Sutskever was probably the most important person behind early versions of ChatGPT such as GPT-2.

“He was probably the most important person behind the development of, um, ChatGPT, the the early versions like GPT two, he was very important in the development of that.”

0:39:23 · Geoffrey Hinton · OpenAI

Geoffrey Hinton says he believes OpenAI promised a significant share of its compute to safety research and later reduced that share.

“It would use a significant fraction of its resources of the compute time for doing safety research, and then it kept, then it reduced that fraction.”

0:44:24 · Geoffrey Hinton · AI safety

Geoffrey Hinton credits Elon Musk with giving Ukrainians communication, via Starlink, during the war with Russia.

“giving the Ukrainians communication during the war with Russia.”

0:42:18 · Geoffrey Hinton · Starlink

Geoffrey Hinton cites automatic teller machines as a past technology that did not cause bank teller joblessness, but argues AI is different.

“When automatic teller machines came in, a lot of bank tellers didn't lose their jobs, they just got to do more interesting things.”

0:44:51 · Geoffrey Hinton · Automation

Geoffrey Hinton says his niece's complaint-letter work fell from 25 minutes to about five with a chatbot, meaning five times fewer people are needed.

“My niece answers letters of complaint to a health service. It used to take her 25 minutes.”

0:46:22 · Geoffrey Hinton · Job displacement

Geoffrey Hinton guesses that superintelligence will arrive within ten to twenty years, though he says it could be sooner or around fifty years away.

“My guess is between ten and twenty years we'll have superintelligence.”

0:53:26 · Geoffrey Hinton · Superintelligence

Geoffrey Hinton says digital neural networks can share information by averaging their weights at trillions of bits per second, billions of times faster than human communication.

“These things are transferring trillions of bits a second, so they're billions of times better than us at sharing information.”

1:02:47 · Geoffrey Hinton · Digital intelligence

Geoffrey Hinton says he asked GPT-4, without web access, why a compost heap is like an atom bomb, to test whether it could see analogies.

“at the point when G P T four couldn't look on the web, I asked it, Why is a compost heap like an atom bomb?”

1:04:04 · Geoffrey Hinton · AI analogy

Geoffrey Hinton recalls a video of the US education secretary referring to AI in classrooms as 'A1'.

“I've seen the video of the US. education secretary talking about how they're gonna get AI in the classrooms, except she thought it was called A1.”

0:26:12 · Geoffrey Hinton · AI policy

Geoffrey Hinton says his cousin Joan Hinton was one of two female physicists at Los Alamos and moved to China after the atomic bomb was dropped.

“she was one of the two female physicists at Los Alamos. And then after they dropped the bomb, she moved to China.”

1:25:33 · Geoffrey Hinton · Joan Hinton · 1940s

Steven Bartlett says Hinton's great-great-grandfather George Boole founded Boolean algebra, a foundational principle of modern computer science.

“Your great great grandfather George Bull founded the Boolean algebra logic, which is one of the foundational principles of modern computer science.”

1:24:21 · Steven Bartlett · Hinton family

Steven Bartlett says an unnamed CEO told him by direct message that the company's headcount fell from just over 7,000 to about 5,000 because of AI agents.

“they used to have seven, just over 7,000 employees. He said, Uh, by last year, they were down to, I think, 5,000.”

1:31:44 · Steven Bartlett · Workforce cuts

Chapters

  1. 0:04:54Why Hinton is called the Godfather of AI

    Hinton explains the decades-long split between logic-based AI and brain-inspired neural networks, and why backing the latter made him influential.

    “There weren't that many people who believed that we could make neural networks work”
  2. 0:09:56Two kinds of AI risk and his odds

    He separates human misuse from the threat of AI deciding it does not need us, and gives his rough extinction estimate.

    “There's risks that come from people misusing AI, and that's most of the risks”
  3. 0:14:44Cyberattacks, viruses, elections and echo chambers

    Hinton walks through the main ways bad actors and engagement-driven platforms could use AI against society, and how he protects his own savings.

    “between 2023 and 2024, they increased by about a factor of twelve, 1,200%.”
  4. 0:25:03Regulating capitalism and autonomous weapons

    He argues companies chase profit by design, so regulation is needed, and warns that robot soldiers make invading smaller countries cheaper.

    “you need to have it very well regulated”
  5. 0:35:38Can we keep a smarter AI from taking over?

    Hinton uses the tiger cub and mother-baby analogies to show why control is hard, and says nobody knows if AI can be made not to want to take over.

    “better be sure that when it grows up, it never wants to kill you”
  6. 0:45:27Joblessness and what is left for humans

    He explains why AI differs from earlier technologies and why he expects far fewer people to be needed for many jobs.

    “I think for mundane intellectual labor, AI is just gonna replace everybody.”
  7. 1:02:47Why digital intelligence beats biological intelligence

    The technical heart of Hinton's worry: AI copies can share what they learn at enormous speed and effectively never die.

    “transferring trillions of bits a second, so they're billions of times better than us”
  8. 1:08:02Can machines have feelings and consciousness?

    Hinton argues that current chatbots have subjective experiences in a meaningful sense and that nothing stops machines from having emotions.

    “I believe that current multimodal chat bots have subjective experiences”
  9. 1:17:07Joining and leaving Google

    Hinton recounts the AlexNet auction that took him to Google, his work there, and why he left in order to speak freely about safety.

    “I have a son who has learning difficulties.”
  10. 1:29:04Closing message: effort and uncertainty

    Hinton ends on guarded hope, saying there is still a chance to build AI that does not want to take over and that it deserves enormous resources.

    “there's still a chance that we can figure out how to develop A I”

Transcript

0:00:00
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This episode is sponsored by Asana.

0:00:02
Steven Bartlett

Let me, uh, admit something to you. I'm a little bit messy. I have got ADHD and sometimes I forget things. I'll put something in Google Drive, I'll put something on my desktop, it's all over the shop. And I can't imagine how much that is costing me as an entrepreneur or as a creative. I never thought of this as a project management problem, I just thought of it as a me problem. So let me give you a window into my fiancee Melanie and how she operates.

0:00:23

She's running a business and she doesn't rely on remembering everything, she creates systems that mean she doesn't have to. And one system she's made for her business is that when people attend her retreats and they get automated itineraries and they get packs sent to them automatically after the retreat, all thanks to Asana. So if you're someone who constantly feels like you need to be better, more organized, maybe ask yourself a different question. Is it actually you that needs to change, or is it the way that you're working?

0:00:46
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0:01:12

A S A N a dot com.

0:01:15
Steven Bartlett

As a founder building a business when I was in my early 20s, I think I always had a deep sense of imposter syndrome because there was something that I wasn't good at. And that thing was finances. Finance and understanding your financial position as a small business is the great enabler of all of your dreams. I was running from it until I discovered a platform called zero. zero is an accounting and financial management platform specifically for small businesses, and it brings accounting, payments, payroll and analytics all into one place, even for people that don't love doing finances.

0:01:46

Zero wants to do the financial work for you, but its core ambition is to go beyond keeping the financial record, because zero wants to help you understand what's happening in your business. And increasingly, and this is maybe the most important thing, is help you make decisions. Finally, we have a partner who can enable us in a simple way for those people that are both left brain or right brain and enable our dreams. You can learn more about zero by going to zero dot com.

0:02:11

Thank you to zero, thank you for sponsoring this podcast, but also thank you for helping me to scale my business. As somebody that quite frankly has never loved finances that much, they call you the Godfather of AI. So what would you be saying to people about their career prospects in a world of super intelligence?

0:02:27
Geoffrey Hinton

Trained to be a plumber.

0:02:28
Steven Bartlett

Really? Okay, I think I've become a plumb.

0:02:31
Speaker 6

Geoffrey Hinton is the Nobel Prize winning pioneer whose groundbreaking work has shaped AI and the future of humanity.

0:02:39
Steven Bartlett

Why do they call you the Godfather of AI?

0:02:41
Geoffrey Hinton

because there weren't many people who believed that we could model AI on the brain. So that it learned to do complicated things like recognize objects in images or even do reasoning. And I pushed that approach for 15 years, and then Google acquired that technology and I worked there for ten years on something that's now used all the time in AI.

0:02:56
Steven Bartlett

And then you left. Why?

0:02:57
Geoffrey Hinton

Yeah, so that I could talk freely at a conference.

0:03:00
Steven Bartlett

What did you want to talk about freely?

0:03:02
Geoffrey Hinton

How dangerous AI could be. I realized that these things will one day get smarter than us and we've never had to deal with that. And if you want to know what life's like when you're not the apex intelligence, ask a chicken. So there's risks that come from people misusing AI, and then there's risks from AI getting super smart and deciding it doesn't need us.

0:03:21
Steven Bartlett

Is that a real risk?

0:03:22
Geoffrey Hinton

Yes, it is, but they're not going to stop it because it's too good for too many things.

0:03:25
Steven Bartlett

What about regulations?

0:03:26
Geoffrey Hinton

They have some, but they're not designed to deal with most of the threats. Like the European regulations have a clause that says none of these apply to military uses of AI.

0:03:34
Steven Bartlett

Really?

0:03:34
Geoffrey Hinton

Yeah, it's crazy.

0:03:35
Steven Bartlett

One of your students left OpenAI.

0:03:37
Geoffrey Hinton

Yeah, he was probably the most important person behind the development of the early versions of ChatGPT, and I think he left because he had safety concerns. We should recognize that this stuff is an existential threat, and we have to face the possibility that unless we do something soon, we're near the end.

0:03:54
Steven Bartlett

So let's do the risks and what we end up doing in such a world. Quick one before we get back to this episode, just give me 30 seconds of your time. Two things I wanted to say. The first thing is a huge thank you for listening and tuning into the show week after week. It means the world to all of us. And this really is a dream that we absolutely never had and couldn't have imagined getting to this place.

0:04:14

But secondly, it's a dream where we feel like we're only just getting started. And if you enjoy what we do here, please join the 24 of people that listen to this podcast regularly and follow us on this app. Here's a promise I'm gonna make to you. I'm gonna do everything in my power to make this show as good as I can now and into the future. We're gonna deliver the guests that you want me to speak to, and we're gonna continue to keep doing all of the things you love about this show.

0:04:40

Thank you, thank you so much. Back to the episode. Geoffrey Hinton. They call you the Godfather of AI.

0:04:51
Geoffrey Hinton

Ah, yes, they do.

0:04:53
Steven Bartlett

Why do they call you that?

0:04:54
Geoffrey Hinton

There weren't that many people who believed that we could make neural networks work artificial neural networks. So for a long time in AI, from the 1950s onwards, there were kind of two ideas about how to do AI. One idea was that sort of core of human intelligence was reasoning, and to do reasoning you needed to use some form of logic, and so AI had to be based around logic. And in your head, you must have something like symbolic expressions that you manipulated with rules, and that's how intelligence worked.

0:05:28

And things like learning or reasoning by analogy, that'll come later once we've figured out how basic reasoning works. There was a different approach, which is to say, let's model AI on the brain, because obviously the brain makes us intelligent. So simulate a network of brain cells on a computer and try and figure out how you would learn strengths of connections between brain cells. So that it learned to do complicated things like recognize objects in images or recognize speech or even do reasoning.

0:05:59

I pushed that approach for like 50 years because so few people believed in it. There weren't many good universities that had groups that did that. So if you did that, the best young students who believed in that came and worked with you. So I was very fortunate in getting a whole lot of really good students.

0:06:19
Steven Bartlett

Some of which have gone on to create and play an instrumental role in creating platforms like OpenAI.

0:06:25
Geoffrey Hinton

Yes, so Ilya Sutskever would be a nice example. A whole bunch of them.

0:06:29
Steven Bartlett

Why did you believe that modeling it off the brain was a more effective approach?

0:06:34
Geoffrey Hinton

It wasn't just me believed it. Early on, von Neumann believed it and Turing believed it. And if either of those had lived, I think AI would have had a very different history. But they both died young.

0:06:47
Steven Bartlett

You think AI would have been here sooner?

0:06:49
Geoffrey Hinton

I think neural net the neural net approach would have been accepted much sooner if either of them had lived.

0:06:56
Steven Bartlett

In this season of your life, what mission are you on?

0:07:00
Geoffrey Hinton

My main mission now is to warn people how dangerous AI could be.

0:07:06
Steven Bartlett

Did you know that when you became the Godfather of AI?

0:07:10
Geoffrey Hinton

No, not really. I was quite slow to understand some of the risks. Some of the risks were always very obvious, like people would use AI to make autonomous lethal weapons. That is things that go around deciding by themselves who to kill. Other risks, like the idea that they would one day get smarter than us and maybe would become irrelevant. I was slow to recognize that. Other people recognized it 20 years ago. I only recognised it a few years ago that that was a real risk that was come might be coming quite soon.

0:07:40
Steven Bartlett

How could you not have foreseen that? If if, with everything you know here about cracking the ability for these computers to learn similar to how humans learn, and just, you know, introducing any rate of improvement.

0:07:53
Geoffrey Hinton

It's a very good question. How could you not have seen that? But remember, neural networks 20 or 30 years ago were very primitive in what they could do. They were nowhere near as good as humans at things like vision and language and speech recognition. The idea that you have to now worry about it getting smarter than people, that seems silly then.

0:08:13
Steven Bartlett

When did that change?

0:08:14
Geoffrey Hinton

It changed for the general population when ChatGPT came out. It changed for me when I realized that the kinds of digital intelligences we're making have something that makes them far superior to the kind of biological intelligence we have. If I want to share information with you, so I go off and I learn something, and I'd like to tell you what I learned. So I produce some sentences. This is a rather simplistic model, but roughly right. Your brain is trying to figure out how can I change the strengths of connections between neurons?

0:08:45

So I might have put that word next. And so you'll do a lot of learning when a very surprising word comes, and not much learning when if it's a when it's a very obvious word. If I say fish and chips, you don't do much learning when I say chips, but if I say fish and cucumber, you do a lot more learning. You wonder, why did I say cucumber? So that's roughly what's going on in your brain.

0:09:04
Steven Bartlett

I'm predicting what's coming next.

0:09:06
Geoffrey Hinton

That's how we think it's working. Nobody really knows for sure how the brain works, and nobody knows how it gets the information about whether you should increase the strength of a connection or decrease the strength of a connection. That's the crucial thing. But what we do know now from AI is that if you could get information about whether to increase or decrease the connection strength, so as to do better at whatever task you're trying to do, then we could learn incredible things.

0:09:33

Because that's what we're doing now with artificial neural nets. It's just we don't know for real brains how they get that signal about whether to increase or decrease.

0:09:42
Steven Bartlett

As we sit here today, what are the big concerns you have around safety of AI? If we were to to list the the top couple that are really front of mind and that we should be thinking about,

0:09:52
Geoffrey Hinton

Can I have more than a couple?

0:09:53
Steven Bartlett

go ahead, I'll write them all down and we'll go through them.

0:09:56
Geoffrey Hinton

Okay, first of all, I wanna make a distinction between two completely different kinds of risk. There's risks that come from people misusing AI, and that's most of the risks and all of the short-term risks. And then there's risks that come from AI getting super smart and deciding it doesn't need us.

0:10:17
Steven Bartlett

is that a real risk?

0:10:18
Geoffrey Hinton

And I talk mainly about that second risk because lots of people say, Is that a real risk? And yes, it is. Now we don't know how much of a risk it is. We've never been in that situation before. We've never had to deal with things smarter than us. So really, the thing about that existential threat is that we have no idea how to deal with it. We have no idea what it's going to look like. And anybody who tells you they know just what's going to happen and how to deal with it, they're talking nonsense.

0:10:46

So we don't know how to estimate the probability probabilities it'll replace us. Um, some people say it's like less than 1%. My friend Jan LeCun, who was a postdoc with me, thinks, No No, we're always gonna be. We build these things, we're always gonna be in control. We'll build them to be obedient. And other people like Yudkowsky say, No, no, no, these things are gonna wipe us out for sure. If anybody builds it, it's gonna wipe us all out.

0:11:14

And he's confident of that. I think both of those positions are extreme. It's very hard to estimate the probabilities in between.

0:11:20
Steven Bartlett

If you had to bet on who was right out of your two friends?

0:11:27
Geoffrey Hinton

I simply don't know. So if I had to bet, I'd say the probability is in between, and I don't know where to estimate it in between. I often say ten to 20% chance I'll wipe us out, but that's just gut. Based on the idea that we're we're still making them and we're pretty ingenious. And the hope is that if enough smart people do enough research with enough resources, we'll figure out a way to build them so they'll never want to harm us.

0:11:54
Steven Bartlett

Sometimes I think if we we talk about that second um path. Sometimes I think about nuclear bombs and the the invention of the atomic bomb and how it compares, like, how is this different? Because the atomic bomb came along? And I imagine a lot of people at that time thought our days are numbered.

0:12:08
Geoffrey Hinton

Uh, yes, I was there, we did.

0:12:10
Steven Bartlett

Yeah, but but but what's what? Ha, we're still here.

0:12:13
Geoffrey Hinton

We're still here, yes. So the atomic bomb was really only good for one thing, and it was very obvious how it worked. Even if you hadn't had the pictures of Hiroshima and Nagasaki, it was obvious that it was a very big bomb that was very dangerous. With AI, it's good for many, many things. It's gonna be magnificent in healthcare and education, and more or less any industry that needs to use its data is gonna be able to use it better with AI.

0:12:45

So we're not gonna stop the development. You know, people say, Well, why don't we just stop it now? We're not gonna stop it because it's too good for too many things. Also, we're not gonna stop it because it's good for battle robots, and none of the countries that sell weapons are gonna want to stop it. Like the European regulations, they have some regulations about AI, it's good they have some regulations, but they're not designed to deal with most of the threats.

0:13:11

And in particular, the European regulations have a a clause in them that say none of these regulations apply to military uses of AI. So governments are willing to regulate companies and people, but they're not willing to regulate themselves.

0:13:28
Steven Bartlett

It seems pretty crazy to me that they I go back and forward. But if Europe has a regulation but the rest of the world doesn't, aren't Yeah, puts we gonna suffer?

0:13:36
Geoffrey Hinton

them at a competitive disadvantage. Yeah, and So

0:13:38
Steven Bartlett

we're seeing this already. I don't think people realize that when OpenAI release a new model or a new piece of software in America, they can't release it to to Europe yet because of regulations here. So Sam Altman tweeted saying our new AI agent thing is available to everybody, but it can't come to Europe yet because there's regulations. Yeah, what is that? That gives us a productive disadvantage, productivity disadvantage, right?

0:14:00
Geoffrey Hinton

What we need is, I mean, at this point in history, when we're about to produce things more intelligent than ourselves, what we really need is a kind of world government that works run by intelligent, thoughtful people. And that's not what we've got.

0:14:15
Steven Bartlett

So free for all.

0:14:18
Geoffrey Hinton

Well, that what we've got is sort of we've got capitalism, which is done very nicely by us. It's produced lots of goods goods and services for us. But these big companies, they're legally required to try and maximize profits, and that's not what you want from the people developing this stuff.

0:14:40
Steven Bartlett

So let's do the risks then. You talked about there's human risks and So then there's

0:14:44
Geoffrey Hinton

so I've distinguished these two kinds of risk. Let's talk about all the risks from bad human actors using AI. There's cyber attacks. So between 2023 and 2024, they increased by about a factor of twelve, 1,200%. And that's probably because these large language models make it much easier to do phishing attacks.

0:15:08
Steven Bartlett

and a phishing attack for anyone that doesn't know is

0:15:11
Geoffrey Hinton

It's they send you something saying, Oh, hi, I'm your friend John and I'm stuck in El Salvador. Could you just wire this money? That's one kind of attack. But the phishing attacks are really trying to get your login credentials.

0:15:24
Steven Bartlett

And now with AI, they can clone my voice, my image.

0:15:26
Geoffrey Hinton

And they can do all that.

0:15:28
Steven Bartlett

I'm struggling at the moment because there's a bunch of AI scams on X and also Meta, and there's one in particular on Meta, so Instagram, Facebook at the moment, which is a paid advert. Where they've taken my voice from the podcast, they've taken the my mannerisms, and they've made a new video of me encouraging people to go and take part in this crypto Ponzi scam or whatever. And we've been, you know, we spent weeks and weeks and weeks and weeks on end emailing Meta, telling please take this down.

0:15:52

They take it down, another one pops up, they take that one down, another one pops up. So it's like whack a mole. And then Very annoying, the the heartbreaking part is you get the messages from people that have fallen for this scam and they've lost 500 pounds or $500.

0:16:03
Geoffrey Hinton

And they're cross with you because you recommended it.

0:16:04
Steven Bartlett

And I'm, I'm like, I'm sad for them. It's very annoying. I Yeah,

0:16:08
Geoffrey Hinton

have a a smaller version of that, which is p. Some people now publish papers with me as one of the authors, and it looks like it's in order that they can get lots of citations to themselves.

0:16:21
Steven Bartlett

so cyber attacks a very real threat. There's been an explosion of those

0:16:24
Geoffrey Hinton

And these already, obviously, AI is very patient, so they can go through 100 million lines of code looking for known ways of attacking them. That's easy to do, but they're gonna get more creative. And they may some people believe, and I some people who know a lot believe that maybe by 2030, they'll be creating new kinds of cyber attacks, which no person ever thought of. So that's very worrisome.

0:16:53
Steven Bartlett

because they can think for themselves and discover They can think for new ways to attack.

0:16:56
Geoffrey Hinton

themselves, they can draw new conclusions from much more data than a person ever saw.

0:17:01
Steven Bartlett

Is there anything you're doing to protect yourself from cyber attacks at all?

0:17:05
Geoffrey Hinton

Yes, it's one of the few places where I changed what I do radically because I'm scared of cyber attacks. Canadian banks are extremely safe. In 2008, no Canadian banks came anywhere near going bust, so they're very safe banks because they're well regulated, fairly well regulated. Nevertheless, I think a cyber attack might be able to bring down a bank. Now, if you have all my savings in shares in banks s held by banks, so if the bank gets attacked and it holds your shares, they're still your shares.

0:17:42

And so I think you'd be okay, unless the attacker sells the shares, because the bank can sell the shares. If the attacker sells your shares, I think you're screwed. I don't know. I mean, maybe the bank would have to try and reimburse you, but the bank's bust by now, right? So so I'm worried about a Canadian bank being taken down by a cyber attack and the attacker selling selling shares that it holds. So I spread my money, my children's money, between three banks, in the belief that if a cyber attack takes down one Canadian bank, the other Canadian banks will very quickly get very careful.

0:18:21
Steven Bartlett

And do you have a phone that's not connected to the internet? Do you have any like, you know, I'm thinking about storing data and stuff like that. Do you think it's wise to consider having cold storage?

0:18:30
Geoffrey Hinton

I have a little disk drive and I back up my laptop on this hard drive, so I actually have everything on my laptop on a hard drive. At least, you know, if the whole internet went down, I had the sense I still got it on my laptop, and I still got my information. Yeah, then the next thing is using AIs to create nasty viruses. And the problem with that is that req just requires one crazy guy with a grudge, one guy who knows a little bit of molecular biology, knows a lot about AI and just wants to destroy the world.

0:19:08

You can now create new viruses relatively cheaply using AI, and you don't have to be a very skilled molecular biologist to do it. And that's very scary. So you could have a small cult, for example, and a small cult might be able to raise a few $1 million for a few $1 million. They might be able to design a whole bunch of viruses.

0:19:29
Steven Bartlett

well, I'm thinking about some of our foreign adversaries doing government funded programs. I mean, there's lots of talk around Covid and the Wuhan labatory and what they were doing in gain of function research. But I'm wondering if in, you know, China or Russia or in Iran or something, the government could fund a program for a small group of scientists to make a virus that they could, you know,

0:19:49
Geoffrey Hinton

I think they could, yes. Now they'd be worried about retaliation, they'd be worried about other governments doing the same to them. Hopefully that would help keep it under control. They might also be worried about the virus spreading to their country. Then there's, um, corrupting elections. So if you wanted to use AI to corrupt elections, a very effective thing is to be able to do targeted political advertisements where you know a lot about the person. So anybody who wanted to use AI for corrupting elections would try and get as much data as they could about everybody in the electorate.

0:20:29

With that in mind, it's a bit worrying what Musk is doing at present in the States, going in and insisting on getting access to all these things that were very carefully siloed. The claim is it's to make things more efficient, but it's exactly what you would want if you intended to corrupt the next election.

0:20:45
Steven Bartlett

how do you mean? Could you get all this data on the

0:20:48
Geoffrey Hinton

You get all this data on people, people? Yeah, you know how much they make, where they live, you know everything about them. Once you know that, it's very easy to manipulate them.

0:20:56
Steven Bartlett

because you can make an AI that

0:20:58
Geoffrey Hinton

You can send messages, um, that they'll find very convincing, telling them not to vote, for example. So I have no no reason other than common sense to think this, but I wouldn't be surprised if part of the motivation of getting all this data from American government sources is to corrupt elections. Another part might be that it's very nice training data for a big model.

0:21:24
Steven Bartlett

but he would have to be taking that data from the government and feeding it into his

0:21:27
Geoffrey Hinton

Yes, and what they've done is turned off lots of the security controls, got rid of the some of the organization to protect against that.

0:21:37
Steven Bartlett

um, so that's corrupting elections.

0:21:39
Geoffrey Hinton

Okay, then there's creating these two echo chambers by organizations like YouTube and Facebook, showing people things that will make them indignant. People love to be indignant.

0:21:55
Steven Bartlett

Indignant as in angry, or what does indignant mean?

0:21:59
Geoffrey Hinton

Feeling I'm sort of angry but feeling righteous. So, for example, if you were to show me something that said Trump did this crazy thing, here's a video of Trump doing this completely crazy thing. I would immediately click on it.

0:22:13
Steven Bartlett

yeah, okay, so putting us in echo chambers and dividing us,

0:22:18
Geoffrey Hinton

Yes, and that's, um, the policy that YouTube and Facebook and others use for deciding what to show you next is causing that. If they had a policy of showing you balanced things, they wouldn't get so many clicks and they wouldn't be able to sell so many advertisements.

0:22:38
Steven Bartlett

that's right.

0:22:38
Geoffrey Hinton

And so it's basically the profit motive is saying, show them whatever will make them click, and what will make them click is things that are more and more extreme,

0:22:47
Steven Bartlett

And that confirmed my existing bias.

0:22:49
Geoffrey Hinton

and that confirm my existing bias. So you're getting your biases confirmed all the time.

0:22:53
Steven Bartlett

Further and further and further and further, which means you're, you're driving which is now away from people.

0:22:56
Geoffrey Hinton

there's in the states, there's two communities that don't hardly talk to each other,

0:23:00
Steven Bartlett

I'm not sure people realize that this is actually happening every time they open an app. But if you go on a TikTok or a YouTube or or one of these big social networks, the algorithm, as you, you said, is designed to show you more of the things that you had interest in last time. So if you just play that out over ten years, it's gonna drive you further and further and further into whatever ideology or belief you have, and further away from nuance and common sense.

0:23:22

And, um, parity, which is a pretty remarkable thing. I I like, people don't know it's happening. They just open their phones and experience something and think this is the news or the experience everyone else is having.

0:23:36
Geoffrey Hinton

right? So basically, if you have a newspaper and everybody gets the same newspaper, you get to see all sorts of things you weren't looking for. And you get a sense that if it's in the newspaper, it's an important thing or significant thing. But if you have your own news feed, my news feed on my iPhone, three quarters of the stories are about AI. And I find it very hard to know if the whole world's talking about AI all the time, or if it's just my news feed.

0:24:04
Steven Bartlett

okay, so driving me into my echo chambers, um, which is gonna continue to divide us further and further. I'm actually noticing that the algorithms are becoming even more, what's the word tailored? And people might go, Oh, that's great, but what it means is they're becoming even more personalized, which was is means that my reality is becoming even further from your reality.

0:24:24
Geoffrey Hinton

it's crazy. We don't have a shared reality anymore. I share reality with other people who watch the BBC and other BBC News, and other people who read the Guardian, and other people who read the New York Times. I have almost no shared reality with people who watch Fox News.

0:24:43
Steven Bartlett

It's pretty, it's pretty. Um, I I

0:24:45
Geoffrey Hinton

It's worrisome. Behind all this is the idea that these companies just wanna make profit, and they'll do whatever it takes to make more profit.

0:24:54
Steven Bartlett

because they have to.

0:24:55
Geoffrey Hinton

They're legally obliged to do that.

0:24:58
Steven Bartlett

So we almost can't blame the company, can we? If they're, if Well, that's

0:25:03
Geoffrey Hinton

capitalism's done very well for us, it's produced lots of goodies, but you need to have it very well regulated. So what you really want is to have rules so that when some company is trying to make as much profit as possible, in order to make that profit, they have to do things that are good for people in general, not things that are bad for people in general. So once you get to a situation where, in order to make more profit, the company starts doing things that are very bad for society, like showing you things that are more and more extreme.

0:25:35

That's what regulations are for. So you need regulations with capitalism. Now, companies will always say regulations get in the way, make us less efficient, and that's true. The whole point of regulations is to stop them doing things to make profit that hurt society, and we need strong regulation.

0:25:53
Steven Bartlett

who's going to decide whether it hurts society or not? Because, you know,

0:25:56
Geoffrey Hinton

That's the job of politicians, unfortunately, if the politicians are owned by the companies, that's not so good.

0:26:02
Steven Bartlett

and also the politicians might not understand the technology. We've you've probably seen the Senate hearings where they wheel out, you know, Mark Zuckerberg and these big tech CEOs. And it is quite embarrassing because they're asking the wrong questions.

0:26:12
Geoffrey Hinton

Well, I've seen the video of the US. education secretary talking about how they're gonna get AI in the classrooms, except she thought it was called A1. She's actually there saying we're gonna have all the kids interacting with A1.

0:26:27
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There is a school system that's gonna start, um, making sure that first graders or even pre Ks have A1 teaching, you know, every year starting, you know, that far down into the grades, and that's just a that's a wonderful thing.

0:26:46
Steven Bartlett

And these are what these are the people that

0:26:47
Geoffrey Hinton

These are the people in charge.

0:26:50
Steven Bartlett

ultimately the tech companies are in charge because they were Well, not smart.

0:26:53
Geoffrey Hinton

the tech companies in the states now, at least a few weeks ago when I was there, they were running an advertisement about how it was very important not to regulate AI because it would hurt us in the competition with China.

0:27:06
Steven Bartlett

Yeah, and that's a that's a plausible argument, no,

0:27:09
Geoffrey Hinton

Yes, it will, but you have to decide. Do you want to compete with China by doing things that will do a lot of harm to your society? And you probably don't.

0:27:24
Steven Bartlett

I guess. They would say that it's not just China, it's Denmark and Australia and Canada and

0:27:30
Geoffrey Hinton

Yeah, they're not, so they're the UK not so worried about.

0:27:32
Steven Bartlett

and Germany. But if they kneecap themselves with regulation, if they slow themselves down, then the founders, the entrepreneurs, the investors are gonna go

0:27:38
Geoffrey Hinton

I think calling it kneecapping is so taking a particular point of view, is take taking the point of view that regulations are sort of very harmful. What you need to do is just constrain the big companies so that in order to make profit, they have to do things that are socially useful. Like Google search is a great example. That didn't need regulation because it just made information available to people. It was great. But then if you take YouTube, which starts showing you adverts and showing you more and more extreme things, that needs regulation.

0:28:10
Steven Bartlett

But we don't have the people to regulate it, as we've identified.

0:28:13
Geoffrey Hinton

I think people know pretty well, um, that particular problem of showing you more and more extreme things. That's a well known problem that the politicians understand. They just, um, need to get on and regulate it,

0:28:25
Steven Bartlett

So that was the the next point, which was that the algorithms are gonna drive us further into our echo chambers. What's next? Lethal autonomous weapons, Lethal autonomous weapons,

0:28:39
Geoffrey Hinton

that means things that can kill you and make their own decision about whether to kill you.

0:28:42
Steven Bartlett

which is the great dream, I guess, of the military industrial complex, being able to create such weapons.

0:28:50
Geoffrey Hinton

so the worst thing about them is big, powerful countries always have the ability to invade smaller, poorer countries. They're just more powerful. But if you do that using actual soldiers, you get bodies coming back in bags, and the relatives of the soldiers that were killed don't like it. So you get something like Vietnam. In the end, there's a lot of protest at home. If, instead of bodies coming back in bags, it was dead robots, there'd be much less protest, and the military industrial complex would like it much more.

0:29:27

Because robots are expensive, and suppose you had something that could get killed and was expensive to replace, that would be just great. Big countries can invade small countries much more easily because they don't have their soldiers being killed.

0:29:42
Steven Bartlett

And the risk here is that these robots will malfunction, or they'll just be more

0:29:49
Geoffrey Hinton

No, no, that's even if the robots do exactly what the people who built the robots want them to do. The risk is that it's going to make big countries invade small countries more often.

0:29:58
Steven Bartlett

more often because they can.

0:29:59
Geoffrey Hinton

Yeah, and it's not a nice thing to do.

0:30:00
Steven Bartlett

So it brings down the friction of war.

0:30:02
Geoffrey Hinton

It brings down the cost of doing an invasion.

0:30:04
Steven Bartlett

hm. But and these machines will be smarter at warfare as well, so they'll be Well, even better.

0:30:10
Geoffrey Hinton

when the machines aren't smarter, so the lethal autonomous weapons, they can make them now, and they I think all the big defense departments are busy making them. Even if they're not smarter than people, they're still very nasty, scary things.

0:30:23
Steven Bartlett

Because I'm thinking that, you know, they could show just a picture, go get this guy and go take out anyone he's been texting. And this little wasp.

0:30:33
Geoffrey Hinton

so two days ago I was visiting a friend of mine in Sussex who had a drone that cost less than 200 pounds, and the drone went up. It took a good look at me, and then it could follow me through the woods, and it follow. It was very spooky having this drone. It was about two meters behind me. It was looking at me, and if I moved over there, it moved over there. It could just track me for 200 pounds, but it was already quite spooky.

0:31:01
Steven Bartlett

Yeah, and I imagine there's, as you say, a race going on as we speak to who can build the most complex autonomous autonomous weapons. There is a a risk I often hear that some of these things will combine and the cyber attack will release weapons.

0:31:16
Geoffrey Hinton

sure, um, you can. You can get combinatorially many risks by combining these other risks. So, I mean, for example, you could get a super intelligent AI that decides to get rid of people, and the obvious way to do that is just to make one of these nasty viruses. If you made a virus that was very contagious, very lethal and very slow, everybody would have it before they realized what was happening. I mean, I think if a super intelligence wanted to get rid of us, it would probably go for something biological like that that wouldn't affect it.

0:31:51
Steven Bartlett

Do you not think it could just very quickly turn us against each other? For example, it could send a warning on the nuclear systems in America that there's a nuclear bomb coming from Russia, or vice versa, and one retaliates.

0:32:02
Geoffrey Hinton

Yeah, I mean, my basic view is there's so many ways in which a superintelligence could get rid of us. It's not worth speculating about.

0:32:11
Steven Bartlett

What what is to stop Well, what you it?

0:32:12
Geoffrey Hinton

have to do is prevent it ever wanting to. That's what we should be doing.

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0:32:19
Steven Bartlett

Let me, uh, admit something to you. I'm a little bit messy. I have got ADHD and sometimes I forget things. I'll put something in Google Drive, I'll put something on my desktop, it's all over the shop. And I can't imagine how much that is costing me as an entrepreneur or as a creative. I never thought of this as a project management problem, I just thought of it as a me problem. So let me give you a window into my fiancee Melanie and how she operates.

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Steven Bartlett

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0:34:28

Thank you to zero, thank you for sponsoring this podcast, but also thank you for helping me to scale my business. As somebody that quite frankly has never loved finances that much,

0:34:36
Geoffrey Hinton

British one. There's no way we're gonna prevent it from. It's smarter than us, right? There's no way we're gonna prevent it getting rid of us if it wants to. We're not used to thinking about things smarter than us. If you want to know what life's like when you're not the apex intelligence, ask a chicken.

0:34:58
Steven Bartlett

Yeah, I was thinking about my dog Pablo, my French bulldog, this morning as I left home. He has no idea where I'm going, he has no idea what I do. I can't even talk to him.

0:35:07
Geoffrey Hinton

yeah, and the intell the intelligence gap will be like that.

0:35:10
Steven Bartlett

So you're telling me that if I'm Pablo, my French bulldog, I need to figure out a way to make my owner not wipe me out.

0:35:19
Geoffrey Hinton

Yeah, so we have one example of that, which is mothers and babies. Evolution put a lot of work into that. Mothers are smarter than babies, but babies are in control, and they're in control cause the mother just can't bear lots of hormones and things, but the ba the mother just can't bear the sound of the baby crying.

0:35:37
Steven Bartlett

Not all mothers.

0:35:38
Geoffrey Hinton

Not all mothers, and then the baby's not in control, and then bad things happen. We somehow need to figure out how to make them not want to take over. The analogy I often use is forget about intelligence, just think about physical strength. Suppose you have a nice little tiger cub, it's sort of bit bigger than a cat, it's really cute, it's very cuddly, very interesting to watch. Except that you better be sure that when it grows up, it never wants to kill you, because if it ever wanted to kill you, you'd be dead in a few seconds.

0:36:10
Steven Bartlett

And you're saying the AI we have now is the tiger cub and it's growing up. So we need to train it as it's when it's a baby.

0:36:18
Geoffrey Hinton

well, now a tiger has lots of innate stuff built in, so you know, when it grows up, it's not a safe thing to have around.

0:36:24
Steven Bartlett

But lions, people that have lions as pets, sometimes the lion is affectionate to its creator, but not to others.

0:36:30
Geoffrey Hinton

yes, and we don't know whether these AIs we. We simply don't know whether we can make them not want to take over and not want to hurt us.

0:36:40
Steven Bartlett

Do you think we can? Do you think it's possible to train

0:36:42
Geoffrey Hinton

I don't know.

0:36:42
Steven Bartlett

super intelligence?

0:36:43
Geoffrey Hinton

I don't think it's clear that we can, so I think it might be hopeless, but I also think we might be able to. And it'd be sort of crazy if people went extinct cause we couldn't be bothered to try.

0:36:56
Steven Bartlett

If that's even a possibility, how do you feel about your life's work? Because you were

0:37:01
Geoffrey Hinton

Yeah, um, it sort of takes the edge off, it doesn't it? I mean, the idea is it's gonna be wonderful in healthcare and wonderful in education and wonderful. I mean, it's gonna make call centers much more efficient, though one worries a bit about what the people who are doing that job now do. It makes me sad. I don't feel particularly guilty about developing AI like 40 years ago, because at that time we had no idea that this stuff was going to happen this fast.

0:37:29

We thought we had plenty of time to worry about things like that. They when you, when you can't get the AI to do much and you want to get it to do a little bit more. You don't worry about this stupid little thing is gonna take over from people. You just want it to be able to do a little bit more of the things people can do. It's not like I knowingly did something thinking this might wipe us all out, but I'm gonna do it anyway.

0:37:53

But it is a bit sad that it's not just gonna be something for good. So I feel I have a duty now to talk about the risks.

0:38:02
Steven Bartlett

and if you could play it forward and you could go forward thirty fifty years and you found out that it led to the extinction of humanity. And if that does end up being being the outcome,

0:38:16
Geoffrey Hinton

Well, if you played it forward and it led to the extinction of humanity, I would use that to tell people, to tell their governments that we really have to work on how we're going to keep this stuff under control. I think we need people to tell governments that governments have to force the companies to use their resources to work on safety. And they're not doing much of that because you don't make profits that way.

0:38:40
Steven Bartlett

one of your your students we talked about earlier, um, Ilya, Ilya left OpenAI and there was lots of conversation around the fact that he left because he had safety concerns and he's gone on to set set up a AI safety company. Why do you think he left?

0:39:01
Geoffrey Hinton

I think he left because he had safety concerns.

0:39:03
Steven Bartlett

Really?

0:39:03
Geoffrey Hinton

He, um, I still have lunch with him from time to time. His his parents live in Toronto, and when he comes to Toronto, we have lunch together. He doesn't talk to me about what went on at OpenAI, so I have no inside information about that. But I know Ilya very well, and he is genuinely concerned with safety, so I think that's why he left.

0:39:21
Steven Bartlett

because he was one of the top people, I mean, he was,

0:39:23
Geoffrey Hinton

He was probably the most important person behind the development of, um, ChatGPT, the the early versions like GPT two, he was very important in the development of that.

0:39:33
Steven Bartlett

you know him personally, so you know his character.

0:39:36
Geoffrey Hinton

Yes, he has a good moral compass. He's not like someone like Musk, who has no moral compass.

0:39:42
Steven Bartlett

Does Sam Altman have a good moral compass?

0:39:45
Geoffrey Hinton

We'll see. You I don't know Sam, so I don't want to comment on that.

0:39:52
Steven Bartlett

But from what you've seen, are you concerned about the actions Well, that they've taken? Because if you because know Ilya and Ilya's a good you guy and he's left,

0:40:01
Geoffrey Hinton

that will give you some insight. Yes, it'll give you some reason to believe that there's a problem there. And if you look at Sam's statements some years ago, he sort of happily said in one interview, and this stuff will probably kill us all. That's not exactly what he said, but that's what it amounted to. Now he's saying, you don't need to worry too much about it. And I suspect that's not driven by seeking after the truth, that's driven by seeking after money.

0:40:32
Steven Bartlett

is it money or is it power?

0:40:34
Geoffrey Hinton

Yeah, I shouldn't have said money, it's some some combination of those, yes,

0:40:38
Steven Bartlett

Okay, I guess money's a proxy for power, but I am. I've got a friend who's a billionaire and he is in those circles. And when I went to his house and had, uh, lunch with him one day, he knows lots of people in AI, building the biggest AI companies in the world. And he gave me a cautionary warning across the across his kitchen table in London, where he gave me an insight into the private conversations these people have.

0:41:00

Not the media interviews they do where they talk about safety and all these things, but actually what some of these individuals think is gonna happen.

0:41:07
Geoffrey Hinton

and what do they think's gonna happen?

0:41:09
Steven Bartlett

It's not what they say publicly, you know, one one person who I sh shouldn't name, who is the who's leading one of the biggest AI companies in the world. He told me that he knows this person very well, and he privately thinks that we're heading towards this kind of dystopian world where we have just huge amounts of free time, we don't work anymore. And this person doesn't really give a fuck about the harm that it's gonna have on the world.

0:41:31

And this person who I'm referring to is building one of the biggest AI companies in the world. And I then watched this person's interviews online.

0:41:36
Geoffrey Hinton

trying to figure out which of three people it is.

0:41:38
Steven Bartlett

Yeah, well, it's one of those three people. And I watched this person's interviews online. And I reflect on a conversation that my billionaire friend had with me, who knows him, and I go, fucking hell, this guy's lying publicly, like he's not telling the the truth to the world. And that's haunted me a little bit. It's part of the reason I have so many conversations around AI on this podcast, because I'm like, I don't know if they're, I think they're a lit.

0:41:58

Some of them are a little bit sadistic about power, and I think they they like the idea that they will change the world, that they will be the one that fundamentally shifts the world.

0:42:10
Geoffrey Hinton

I think Musk is clearly like that, right?

0:42:14
Steven Bartlett

He's such a complex character that I don't, I don't really know how to place Musk. Um,

0:42:18
Geoffrey Hinton

He's done some really good things, like, um, pushing electric cars. That was a really good thing to do. Some of the things he said about self driving were a bit exaggerated, but he that was a really useful thing he did, giving the Ukrainians communication during the war with Russia.

0:42:35
Steven Bartlett

Starlink, yeah.

0:42:36
Geoffrey Hinton

Um, that was a really good thing he did. There's a bunch of things like that, um, but he's also done some very bad things.

0:42:44
Steven Bartlett

So coming back to this point of the possibility of destruction and the motives of these big companies. Are you at all hopeful that anything can be done to slow down the pace and acceleration of AI?

0:43:02
Geoffrey Hinton

Okay, there's two issues. One is can you slow it down? And the other is can you make it so I mean it will be safe in the end? It won't wipe us all out. I don't believe we're gonna slow it down. And the reason I don't believe we're gonna slow it down is because there's competition between countries and competition between companies within a country. And all of that is making it go faster and faster. And if the US slowed it down, China wouldn't slow it down.

0:43:28
Steven Bartlett

does Ilya think it's possible to make AI safe. safe?

0:43:35
Geoffrey Hinton

I think he does. He won't tell me what his secret source is. I. I'm not sure how many people know what his secret source is. I think a lot of the investors don't know what his secret source is, but they've given him billions of dollars anyway, because they have so much faith in Ilya, which isn't foolish. I mean, he was very important in AlexNet, which got object recognition working well. He was the main the main force behind the things like GPT two, which then led to ChatGPT.

0:44:05

So I think having a lot of faith in Ilya is a very reasonable decision.

0:44:09
Steven Bartlett

There's something quite haunting about the guy that made and was the main force behind GPT two, which led rise to this whole revolution, left the company because of safety reasons. He knows something that I don't know about what might happen next.

0:44:24
Geoffrey Hinton

Well, the company had now, I don't know the precise details, um, but I'm fairly sure the company had indicated that it would. It would use a significant fraction of its resources of the compute time for doing safety research, and then it kept, then it reduced that fraction. I think that's one of the things that happened.

0:44:43
Steven Bartlett

Yeah, that was reported publicly. Yeah, we got into the autonomous weapons part of the risk framework.

0:44:51
Geoffrey Hinton

right, so the next one is joblessness. In the past, new technologies have come in, which didn't lead to joblessness, new jobs were created. So the classic example people use is automatic teller machines. When automatic teller machines came in, a lot of bank tellers didn't lose their jobs, they just got to do more interesting things. But here, I think this is more like when they got machines in the industrial revolution. And you can't have a job digging ditches now, because a machine can dig ditches much better than you can.

0:45:27

And I think for mundane intellectual labor, AI is just gonna replace everybody. Now it will may well be in the form of you have fewer people using AI assistants, so it's a combination of a person and an AI assistant are now doing the work that ten people could do previously.

0:45:46
Steven Bartlett

people say that it will create new jobs, though, so we'll be fine.

0:45:51
Geoffrey Hinton

Yes, and that's been the case for other technologies, but this is a very different kind of technology. If it can do all mundane human intellectual labor, then what new jobs is it gonna create? You'd you'd have to be very skilled to have a job that it couldn't just do. So I don't, I don't think they're right. I think you can try and generalize from other technologies that have come in, like computers or automatic teller machines, but I think this is different.

0:46:18
Steven Bartlett

People use this phrase, they say AI won't take your job, a human using AI will take your job.

0:46:22
Geoffrey Hinton

Yes, I think that's true, but for many jobs, that'll mean you need far fewer people. My niece answers letters of complaint to a health service. It used to take her 25 minutes. She'd read the complaint and she'd think how to reply, and she'd write a letter, and now she just scans it into, um, a chatbot, and it writes the letter. She just checks the letter. Occasionally she tells it to revise it in some ways. The whole process takes her five minutes.

0:46:54

That means she can answer five times as many letters, and that means they need five times fewer of her, so she can do the job that five of her used to do. Now, that will mean they need less people. In other jobs, like in healthcare, they're much more elastic. So if you could make doctors five times as efficient, we could all have five times as much healthcare for the same price, and that would be great. There's there's almost no limit to how much healthcare people can absorb.

0:47:25

They always want more healthcare if if there's no cost to it. There are jobs where you can make a person with an AI assistant much more efficient, and you won't need to less people because you'll just have much more of that being done. But most jobs, I think, are not like that.

0:47:42
Steven Bartlett

Am I right in thinking? The sort of industrial revolution w played a role in replacing muscles, and this revolution in AI replaces intelligence, the brain.

0:47:52
Geoffrey Hinton

yeah. So mundane intellectual labor is like having strong muscles, and it's not worth much anymore.

0:48:00
Steven Bartlett

So muscles have been replaced, now intelligence is being replaced. So what remains?

0:48:06
Geoffrey Hinton

maybe for a while, some kinds of creativity, but the whole idea of superintelligence is nothing remains. Um, these things will get to be better than us at everything.

0:48:15
Steven Bartlett

So what, what do we end up doing in such a world?

0:48:17
Geoffrey Hinton

Well, if they work for us, we end up getting lots of goods and services for not much effort.

0:48:25
Steven Bartlett

Okay, but that sounds tempting and nice, but I don't know. There's a cautionary tale in creating more and more ease for humans in in it going badly.

0:48:35
Geoffrey Hinton

Yes, and we need to figure out if we can make it go well. So the the nice scenario is imagine a company with a CEO who is very dumb, probably the son of the former CEO, and he has an executive assistant who's very smart. And he says, I think we should do this, and the executive assistant makes it all work. The CEO feels great. He doesn't understand that he's not really in control, and in s in some sense, he is in control.

0:49:07

He suggests what the company should do, she just makes it all work, everything's great. That's the good scenario.

0:49:14
Steven Bartlett

And the bad scenario?

0:49:15
Geoffrey Hinton

The bad scenario, she thinks, why do we need him?

0:49:19
Steven Bartlett

Yeah, I mean, I in a world where we have super intelligence, which you don't believe is that far away.

0:49:26
Geoffrey Hinton

Yeah, I think it might not be that far away. It's very hard to predict, but I think we might get it in like 20 years or even less.

0:49:33
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0:51:45
Geoffrey Hinton

Okay, so it's already. AI is already better than us at a lot of things, in particular areas like chess, for example. AI is so much better than us that people will never beat those things again. Maybe the occasional win, but basically they'll never be comparable again. Obviously the same in Go. In terms of the amount of knowledge they have, um, something like GPT four knows thousands of times more than you do. There's a few areas in which your knowledge is better than it, and in almost all areas it just knows more than you do.

0:52:18
Steven Bartlett

what areas am I better than it?

0:52:22
Geoffrey Hinton

Probably in interviewing CEOs, you're probably better at that. You've got a lot of experience at it, you're a good interviewer, you know a lot about it. If you tried, if you got GPT four to interview a CEO, probably do a worse job.

0:52:38
Steven Bartlett

Okay, I'm trying to think if that, if I agree with that statement. Uh, GPT four, I think for sure. Um, but I, but I guess you could train one.

0:52:47
Geoffrey Hinton

but it may not be long before

0:52:49
Steven Bartlett

Yeah, I guess you could train one on this the how I ask questions and what I do, and

0:52:52
Geoffrey Hinton

sure. And if you took a general purpose sort of foundation model and then you trained it up on not just you, but every every interview you could find doing interviews like this, but especially you, it would probably get to be quite good at doing your job, but probably not as good as you for a while.

0:53:12
Steven Bartlett

okay. So there's a few areas left, and then super intelligence becomes when it's better than us at all things.

0:53:18
Geoffrey Hinton

When it's much smarter than you, and at almost all things, it's better than you. Yeah,

0:53:22
Steven Bartlett

And you, you, you say that this might be a decade away or so.

0:53:26
Geoffrey Hinton

yeah, it might be, it might be even closer, some people think it's even closer, it might well be much further, it might be fifty years away. That's still a possibility. It might be that somehow training on human data limits you to not being much smarter than humans. My guess is between ten and twenty years we'll have superintelligence.

0:53:45
Steven Bartlett

On this point of joblessness, it it's something that I've been thinking a lot about. In particular, because I started messing around with AI agents, and we released an episode on the podcast actually this morning, where we had a debate about AI agents with some a CEO of a big AI agent company and a few other people. And it was the first moment where I had, no, it was another moment where I had a eureka moment about what the future might look like.

0:54:06

When I was able, in the interview, to tell this agent to order all of us drinks, and then five minutes later, in the interview, you see the guy show up with the drinks. And I didn't touch anything, I just told it to order us drinks to the studio.

0:54:17
Geoffrey Hinton

And you and you didn't know about who you normally got your drinks from. It figured that out from the web.

0:54:21
Steven Bartlett

Yeah, figured it out cause it went on Uber Eats. It has my my my data, I guess, and it I. We put it on the screen in real time, so everyone at home can see the agent going through the internet, picking the drinks, adding a tip for the driver, putting my address in, putting my credit card details in. And then the next thing you see is the drinks show up. So that that was one moment, and then the other moment was when I used a tool called Replit and I built software by just telling the agent what I wanted.

0:54:46
Geoffrey Hinton

yes, it's amazing, right?

0:54:48
Steven Bartlett

It's amazing and terrifying at the same time. Yes, and Because

0:54:52
Geoffrey Hinton

if it can build software like that, right? Remember that the A I, when it's training, is using code, and if it can modify its own code, then it gets quite scary, right?

0:55:05
Steven Bartlett

because it can modify itself.

0:55:05
Geoffrey Hinton

It can change itself in a way we can't change ourselves. We can't change our innate endowment, right? There's nothing about itself that it couldn't change.

0:55:16
Steven Bartlett

On this point of joblessness, you have kids

0:55:18
Geoffrey Hinton

I do. and they have kids, No,

0:55:21
Steven Bartlett

they don't have kids, so no grandkids yet. What would you be saying to people about their career prospects in a world of superintelligence? What should we we be thinking about?

0:55:29
Geoffrey Hinton

um, in the meantime, I'd say it's gonna be a long time before it's as good at physical manipulation as us. And so a good bet would be to be a plumber.

0:55:42
Steven Bartlett

until the humanoid robots show up in such a world where there is mass joblessness, which is not something that you just predict. But this is something that Sam Altman at OpenAI, I've heard him predict, and many of the CEOs, I mean, Elon Musk. I watched an interview, which I'll play on screen of him being asked this question. And it's very rare that you see Elon Musk silent for twelve seconds or whatever it was. And then he basically says something about he actually is living in suspended disbelief, i.

0:56:06

e. he's basically just not thinking about it.

0:56:08
Speaker 5

And you think about advising your children on a career with so much that is changing, what do you tell them is gonna be of value?

0:56:28
Geoffrey Hinton

Well, that is a tough question to answer. I would just say, you know, to to sort of follow their heart in terms of what they they find, um, interesting to do or fulfilling to do. I mean, if I think about it too hard, it frankly, it can be, uh, just dis dispiriting and, uh, demotivating. Um, because, I mean, I, I go through, I mean, I, I. I've put a lot of blood, sweat and tears into building the companies and then it.

0:56:57

And then I'm like, wait, well, should I be doing this? Because if I'm sacrificing time with friends and family that I would prefer to to to do. But but then ultimately, the A I can do all these things. Does that make sense? I, I don't know. Um, to some extent, I have to have deliberate suspension of disbelief in order to to remain motivated. Um, so I, I guess I would say, just, you know, work on things that you find interesting, fulfilling, and um, and and that contribute, uh, some good to the rest of society.

0:57:32

yeah, a lot of these threats. It's very hard to intellectually, you can see the threat, but it's very hard to come to terms with it emotionally. I, I haven't come to terms with it emotionally yet.

0:57:45
Steven Bartlett

what do you mean by that?

0:57:48
Geoffrey Hinton

I haven't come to terms with what the development of superintelligence could do to my children's future. I'm okay, I'm seventy seven, I'm gonna be out of here soon. But for my children and my my younger friends, my nephews and nieces and their children, um, I just don't like to think about what could happen.

0:58:18
Steven Bartlett

Why?

0:58:20
Geoffrey Hinton

Because it could be awful.

0:58:24
Steven Bartlett

In in what way?

0:58:27
Geoffrey Hinton

Well, if I ever decided to take over, I mean, it would need people for a while to run the power stations until it designed better analog machines to run the power stations. There's so many ways it could get rid of people, all of which would, of course, be very nasty.

0:58:45
Steven Bartlett

Is that part of the reason you do what you do now?

0:58:48
Geoffrey Hinton

Yeah, I I mean, I think we should be making a huge effort right now to try and figure out if we can develop it safely.

0:58:55
Steven Bartlett

Are you concerned about the midterm impact, potentially on your nephews and your your kids in terms of their jobs as well?

0:59:01
Geoffrey Hinton

Yeah, I'm concerned about all that.

0:59:03
Steven Bartlett

Are there any particular industries that you think are most at risk? People talk about the creative industries a lot, and it sort of knowledge work. They talk about lawyers and accountants and stuff like that.

0:59:12
Geoffrey Hinton

Yeah, so that's why I mentioned plumbers. I think plumbers are less at risk.

0:59:15
Steven Bartlett

Okay, I'm gonna become a plumber.

0:59:16
Geoffrey Hinton

Someone like a legal assistant, a paralegal, um, they're not gonna be needed for very long.

0:59:24
Steven Bartlett

And is there a wealth inequality issue here that will will, uh, arise I think, from this?

0:59:27
Geoffrey Hinton

yeah, I think in a society which shared out things fairly, if you get a big increase in productivity, everybody should be better off. But if you can replace lots of people by AIs, then the people who get replaced will be worse off. And the company that supplies the AIs will be much better off, and the company that uses the AIs. So it's gonna increase the gap between rich and poor, and we know that if you look at that gap between rich and poor, that basically tells you how nice a society is.

1:00:05

If you have a big gap, you get very nasty societies in which people live in walled communities and put other people in mass jails. It's not good to increase the gap between rich and poor.

1:00:17
Steven Bartlett

The International Monetary Fund has expressed profound concerns that generative A I could cause massive labor disruptions and rising inequality and has called for policies that prevent this from happening. I read that in the Business Insider. So, have they What do you do?

1:00:31
Geoffrey Hinton

given any idea what the policies should look like? Yeah, that's the problem. I mean, if A I can make everything much more efficient and get rid of people for most jobs, or have a person assisted by A I doing many, many people's work, it's not obvious what to do about it. universal basic income So,

1:00:50
Steven Bartlett

give, give everybody money.

1:00:51
Geoffrey Hinton

yeah, I th. I I think that's a good start and it stops people starving, but for a lot of people, their dignity is tied up with their job. I mean, who you think you are is tied up with you doing this job, right? And if we said we'll give you the same money just to sit around, that would impact your dignity.

1:01:13
Steven Bartlett

you said something earlier about it surpassing or being superior to human intelligence. A lot of people, I think, like to believe that A I is is on a computer, and it's something you can just turn off if you don't like it.

1:01:25
Geoffrey Hinton

Well, let me tell you why I think it's superior. Um, it's digital, and because it's digital, you can have. You can simulate a neural network on one piece of hardware, and you can simulate exactly the same neural network on a different piece of hardware. So you can have clones of the same intelligence. Now you could get this one to go off and look at one bit of the internet, and this other one to look at a different bit of the internet.

1:01:52

And while they're looking at these different bits of the internet, they can be syncing with each other, so they keep their weights the same, the connection strengths, the same weights of connection strengths. So this one might look at something on the internet and say, Oh, I'd like to increase this strength of this connection a bit, and it can convey that information to this one so it can increase the strength of that connection a bit. Based on this one's experience,

1:02:14
Steven Bartlett

and when you say the strength of the connection, you're talking about learning. that's learning, yes, learning Yeah,

1:02:19
Geoffrey Hinton

consists of saying, instead of this one giving 2.4 votes for whether that one should turn on, we'll have this one give 2.5 votes for whether this one should turn on. And that would be a little bit of learning. So these two different copies of the same neural net are getting different experiences, they're looking at different data, but they're sharing what they've learned by averaging their weights together, and they can do that averaging at like, you can average 1 trillion weights.

1:02:47

When you and I transfer information, we're limited to the amount of information in a sentence, and the amount of information in a sentence is maybe a hundred bits. It's very little information. We're lucky if we're transferring like ten bits a second. These things are transferring trillions of bits a second, so they're billions of times better than us at sharing information. And that's because they're digital and you can have two bits of hardware using the connection strengths in exactly the same way.

1:03:13

We're analog and you can't do that. Your brain's different from my brain, and if I could see the connection strengths between all your neurons, it wouldn't do me any good because my neurons work slightly differently and they're connected up slightly differently. So when you die, all your knowledge dies with you. When these things die, suppose you take these two digital intelligences that are clones of each other and you destroy the hardware they run on. As long as you've stored the connection strength somewhere, you can just build new hardware that executes the same instructions, so it'll know how to use those connection strengths, and you've recreated that intelligence.

1:03:50

So they're immortal. We've actually solved the problem of immortality, but it's only for digital things.

1:03:57
Steven Bartlett

so it knows it will effen essentially know everything that humans know, but more, because it will learn new things.

1:04:04
Geoffrey Hinton

It will learn new things, it will also see all sorts of analogies that people probably never saw. So, for example, at the point when G P T four couldn't look on the web, I asked it, Why is a compost heap like an atom bomb? Off you go.

1:04:21
Steven Bartlett

I have no idea.

1:04:23
Geoffrey Hinton

Exactly, excellent. Most, that's exactly what most people would say. It said. Well, the time scales are very different and the energy scales are very different. But then it went on to talk about how a compost

1:04:34
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1:05:26
Geoffrey Hinton

deep. As it gets hotter, generates heat faster, and an atom bomb, as it produces more neutrons, generates neutrons faster. And so they're both chain reactions, but at very different time and energy scales. And I believe G P T four had seen that during its training, it had understood the analogy between a compost heap and an atom bomb. And the reason I believe that is if you've only got 1 trillion connections, remember, you have 100 trillion, and you need to have thousands of times more knowledge than a person.

1:05:57

You need to compress information into those connections, and to compress information, you need to see analogies between different things. In other words, it needs to see all the things that are chain reactions and understand the basic idea of a chain reaction. And code that, and then code the ways in which they're different. And that's just a more efficient way of coding things than coding each of them separately. So it's seen many, many analogies, probably many analogies that people have never seen.

1:06:24

That's why I also think that people who say these things are never be creative, they're going to be much more creative than us because they're going to see all sorts of analogies we never saw. And a lot of creativity is about seeing strange analogies.

1:06:36
Steven Bartlett

People are somewhat romantic about the specialness of what it is to be human, and you hear lots of people saying, it's very, very different, it's, it's computer. We are, you know, we're conscious, we are creatives, we we have these sort of innate, unique abilities that the computers will never have. What do you say to those people?

1:06:53
Geoffrey Hinton

I'd argue a bit with the innate. Um, so the first thing I say is we have a long history of believing people were special, and we should have learned by now. We thought we were at the center of the universe, we thought we were made in the image of God. White people thought they were very special. We just tend to want to think we're special. My belief is that more or less everyone has a completely wrong model of what the mind is.

1:07:23

Let's suppose I drink a lot or I drop some acid and not recommend it, and I say to you, I have the subjective experience of little pink elephants floating in front of me. Most people interpret that as there's some kind of inner theater called the mind, and only I can see what's in my mind. And in this inner theater, there's a little pink elephant floating around. So, in other words, what's happened is my perceptual system's gone wrong, and I'm trying to indicate to you how it's gone wrong and what it's trying to tell me.

1:08:02

And the way I do that is by telling you what would have to be out there in the real world for it to be telling the truth. And so these little pink elephants, they're not in some inner theater. These little pink elephants are hypothetical things in the real world. And that's my way of telling you how my perceptual system's telling me fibs. So now let's do that with a chatbot. Because I believe that current multimodal chat bots have subjective experiences, and very few people believe that, but I'll try and make you believe it.

1:08:37

So suppose I have a multimodal chat bot, it's got a robot arm so it can point, and it's got a camera so it can see things. And I put an object in front of it and I say, point at the object, it goes like this, no problem. Then I put a prism in front of its lens, and so then I put an object in front of it and I say, point at the object, and it goes there good.

1:08:58

And I say, no, that's not where the object is. The object's actually straight in front of you, but I put a prism in front of your lens. And the chatbot says, Oh, I see the prism bent the light rays, so, um, the object's actually there. But I had the subjective experience that it was there. Now, if the chatbot says that, it's using the words subjective experience exactly the way people use them, it's an alternative view of what's going on.

1:09:24

They're hypothetical states of the world, which, if they were true, would mean my perceptual system wasn't lying. And that's the best way I can tell you what my perceptual system's doing when it's lying to me. Now we need to go further to deal with sentience and consciousness and feelings and emotions, but I think in the end, they're all going to be dealt with in a similar way. There's no reason machines can't have them all, but people say machines can't have feelings, and people are curiously confident about that.

1:09:51

I've no idea why. Suppose I make a battle robot and it's a little battle robot, and it sees a big battle robot that's much more powerful than it. It will be really useful if it got scared. Now, when I get scared, um, various physiological things happen that we don't need to go into, and those won't happen with the robot. But all the cognitive things, like I better get the hell out of here, and I better sort of change my way of thinking, so I focus and focus and focus and don't get distracted.

1:10:25

All of that will happen with robots, too. People will build in things so that they when the circumstances are such, they should get the hell out of there. They get scared and run away. They'll have emotions, then they won't have the physiological aspects, but they will have all the cognitive aspects. And I think it would be odd to say they're just simulating emotions. No, they're really having those emotions. The little robot got scared and ran away,

1:10:48
Steven Bartlett

it's not running away because of adrenaline, it's running away because of a sequence of sort of neurological in its neural net processes happen, which which meant.

1:10:57
Geoffrey Hinton

have the equivalent effect to adrenaline.

1:11:00
Steven Bartlett

So do you do you think?

1:11:01
Geoffrey Hinton

And it's not just adrenaline, right? There's a lot of cognitive stuff going on when you get scared.

1:11:04
Steven Bartlett

Yeah, so do you think that there is conscious A I? And when I say conscious, I mean that represents the same properties of consciousness that a human has.

1:11:16
Geoffrey Hinton

There's two issues here, there's a sort of empirical one and a philosophical one. I don't think there's anything in principle that stops machines from being conscious. I'll give you a little demonstration of that before we carry on. Suppose I take your brain and I take one brain cell in your brain and I replace it by. It's a bit black mirror like. I replace it by a little piece of nanotechnology that's just the same size that behaves in exactly the same way.

1:11:43

When it gets pings from other neurons, it sends out pings just as the brain cell would have, so the other neurons don't know anything's changed. Okay, I've just replaced one of your brain cells with this little piece of nanotechnology. Would you still be conscious? Now you can see where this argument's going.

1:12:00
Steven Bartlett

yeah, so if you replaced all of them,

1:12:02
Geoffrey Hinton

As I replace them all, at what point do you stop being conscious?

1:12:06
Steven Bartlett

well, people think of consciousness as this like ethereal thing that exists maybe beyond the brain cells.

1:12:12
Geoffrey Hinton

Yeah, well, people have a lot of crazy ideas. Um, people don't know what consciousness is, and they often don't know what they mean by it. And then they fall back on saying, Well, I know, because I've got it, and I can see that I've got it. And they fall back on this theater model of the mind, which I think is nonsense.

1:12:31
Steven Bartlett

What do you think of consciousness as if you had to try and define it? Is it? Cause? I think of it as just like the awareness of myself. I don't know.

1:12:37
Geoffrey Hinton

I think it's a term we'll stop using. Suppose you want to under understand how a car works well, you know, some cars have a lot of oomph and other cars have a lot less oomph, like an Aston Martin's got lots of oomph and a little Toyota Corolla doesn't have much oomph. But oomph isn't a very good concept for understanding cars. Um, if you want to understand cars, you need to understand about electric engines or petrol engines and how they work.

1:13:04

And it gives rise to oomph, but oomph isn't a very useful explanatory concept. It's a kind of essence of a car, it's the essence of an Aston Martin, but it doesn't explain much. I think consciousness is like that, and I think we'll stop using that term. But I don't think there's anything, any reason why a machine shouldn't have it. If your view of consciousness is that it intrinsically involves self-awareness, then the machine's got to have self-awareness.

1:13:29

It's got to have cognition about its own cognition and stuff. But I'm a materialist through and through, and I don't think there's any reason why a machine shouldn't have consciousness.

1:13:42
Steven Bartlett

Do you think they do then have the same consciousness that we think of ourselves as being uniquely, uh, given as a gift when we're born?

1:13:51
Geoffrey Hinton

I'm ambivalent about that at present, so I don't think there's this hard line. I think as soon as you have a machine that has some self-awareness, it's got some consciousness. Um, I think it's an emergent property of a complex system. It's not a sort of essence that's throughout the universe. It's you make this really complicated system that's complicated enough to have a model of itself, and it does perception. And I think then you're beginning to get a conscious machine.

1:14:24

So I don't think there's any sharp distinction between what we've got now and conscious machines. I don't think it's going to one day we're going to wake up and say, Hey, if you put this special chemical in, it becomes conscious. It's not going to be like that.

1:14:36
Steven Bartlett

I think we will wonder if these computers are like thinking like we are on their own when we're not there, and if they're experiencing emotions, if they're contending with I. We, I think we probably, you know, we think about things like love and things that are feel unique to biological species. Um, are they? Sa? They're thinking, are they? Uh, do they have concerns?

1:14:55
Geoffrey Hinton

I think they really are thinking, and I think as soon as you make a I agents, they will have concerns. If you want to make an effective A I agent, suppose you let's take a call center. In a call center, you have people at present. They have all sorts of emotions and feelings, which are kind of useful. So suppose I call up the call center and I'm actually lonely and I don't actually want to know the answer to why my computer isn't working.

1:15:23

I just want somebody to talk to. After a while, the person in the call center will either get bored or get annoyed with me and will terminate it. Well, you replace them by an A I agent, the A I agent needs to have the same kind of responses. If someone's just called up because they just want to talk to the A I agent and we're happy to talk for who the whole day to the A I agent, that's not good for business.

1:15:48

And you want an A I agent that either gets bored or gets irritated and says, I'm sorry, but I don't have time for this. And once it does that, I think it's got emotions. Now, like I say, emotions have two aspects to them. There's the cognitive aspect and the behavioral aspect, and then there's a physiological aspect, and those go together with us. And if the A I agent gets embarrassed, it won't go red,

1:16:14
Steven Bartlett

Yeah, so there's no physiological

1:16:16
Geoffrey Hinton

and the skin won't start sweating, but it might have all the same behavior. And in that case, I'd say, yeah, it's having emotion, it's got an emotion.

1:16:23
Steven Bartlett

so it's gonna have the same sort of cognitive thought, and then it's gonna act upon that cognitive in the same way, thought.

1:16:28
Geoffrey Hinton

but without the physiological responses.

1:16:31
Steven Bartlett

And does that matter that it's, it doesn't go red in the face, and it's just a different, I mean, that's a response to the It makes it somewhat question.

1:16:36
Geoffrey Hinton

different from us. For some things, the physiological aspects are very important, like love. They're a long way from having love the same way we do, but I don't see why they shouldn't have emotions. So I think what's happened is people have a model of how the mind works and what feelings are and what emotions are, and their model's just wrong.

1:16:59
Steven Bartlett

what, um, what brought you to Google? You, you worked at Google for about a decade, right? What brought you there?

1:17:07
Geoffrey Hinton

I have a son who has learning difficulties. And in order to be sure he would never be out on the street, I needed to get several $1 million. And I wasn't going to get that as an academic. I tried, so I taught a Coursera course in the hope that I'd make lots of money that way, but there was no money in that. So I figured out, well, the only way to get millions of dollars is to sell myself to a big company.

1:17:38

And so when I was sixty five, fortunately for me, I had two brilliant students who produced something called Alex Net, which was neural net that was very good at recognizing objects in images. And so Ilya and Alex and I set up a little company and auctioned it, and we actually set up an auction where we had a number of big companies bidding for us.

1:18:05
Steven Bartlett

And that company was called Alex Net,

1:18:08
Geoffrey Hinton

No, the the the network that recognized objects was called Alex Net. The company was called D N N Research, Deep Neural Network Research.

1:18:16
Steven Bartlett

and it was doing things like this. I'll put this, uh, graph up on the screen. that's that, But that's Alex Net, this picture shows eight images and Alex Net's ability, which is your company's ability to spot what was in those images.

1:18:28
Geoffrey Hinton

yeah. So it could tell the difference between various kinds of mushroom, and about 12% of ImageNet is dogs. And to be good at ImageNet, you have to tell the difference between very similar kinds of dog, and it we got to be very good at that.

1:18:44
Steven Bartlett

And your your company, Alex Net, won several awards, I believe, for its ability to outperform its competitors. And so Google ultimately ended up acquiring your technology,

1:18:55
Geoffrey Hinton

Google acquired that technology and some other technology.

1:18:59
Steven Bartlett

and you went to work at Google at age, what, sixty six,

1:19:03
Geoffrey Hinton

I went at age sixty five to work at Google.

1:19:05
Steven Bartlett

sixty five, and you left at age seventy six,

1:19:08
Geoffrey Hinton

Seventy five. seventy five, okay, I worked there for more or less exactly ten years.

1:19:11
Steven Bartlett

and what were you doing there

1:19:13
Geoffrey Hinton

Okay, they were very nice to me, they said. They said pretty much you can do what you like. I worked on something called distillation that did really work well, and that's now used all the time

1:19:25
Steven Bartlett

in A I?

1:19:25
Geoffrey Hinton

in A I. And distillation is a way of taking what a big model knows, a big neural net knows, and getting that knowledge into a small neural net. Then, at the end, I got very interested in analog computation and whether it would be possible to get these big language models running in analog hardware, so they used much less energy. And it was while I was doing that work that I began to really realize how much better digital is for sharing information.

1:19:53
Steven Bartlett

Was there a eureka moment?

1:19:56
Geoffrey Hinton

There was a eureka month or two, um, and it was a sort of coupling of chat GPT coming out, although Google had very similar things a year earlier, and I'd seen those and that had a big impact effect on me. The closest I had to a eureka moment was when a Google system called Palm was able to say why a joke was funny, and I'd always thought of that as a kind of landmark. If it can say why a joke's funny, it really does understand, and it could say why a joke was funny.

1:20:29

And that, coupled with realizing why digital is so much better than analog for sharing information, suddenly made me very interested in A I safety. And that these things were going to get a lot smarter than us.

1:20:43
Steven Bartlett

Why did you leave Google?

1:20:45
Geoffrey Hinton

The main reason I left Google was cause I was seventy five and I wanted to retire. I've done a very bad job of that. The precise timing of when I left Google was so that I could talk freely at a conference at M I T, but I left cause I was I'm old and I was finding it harder to program. I was making many more mistakes when I programmed, which is very annoying.

1:21:07
Steven Bartlett

You wanted to talk freely at a conference at M I T?

1:21:09
Geoffrey Hinton

Yes, at M I T organized by M I T tech review.

1:21:12
Steven Bartlett

What did you want to talk about freely?

1:21:14
Geoffrey Hinton

A I safety.

1:21:15
Steven Bartlett

And you couldn't do that while you were at Google.

1:21:17
Geoffrey Hinton

Well, I could have done it while I was at Google, and Google encouraged me to stay and work on A I safety and said I could do whatever I liked on A I safety. You kind of censor yourself if you work for a big company, you don't feel right saying things that'll damage the big company, even if you could get away with it. It just feels wrong to me. I didn't leave because I was cross with anything Google was doing.

1:21:39

I think Google actually behaved very responsibly. When they had these big chat bots, they didn't release them, possibly because they were worried about their reputation. They had a very good reputation and they didn't want to damage it. So it's Open A I didn't have a reputation, and so they could afford to take the gamble.

1:21:56
Steven Bartlett

I mean, there's also a big conversation happening around how it will cannibalize their core business in search. There is now, yes, Yeah, and it's the old innovator's dilemma, to some degree, I guess that they're they're contending

1:22:07
Geoffrey Hinton

yes, it is.

1:22:07
Steven Bartlett

with. Make sure you keep what I'm about to say to yourself. I'm inviting 10,000 of you to come even deeper into the diary of a CEO. Welcome to my inner circle. This is a brand new private community that I'm launching to the world. We have so many incredible things that happen that you are never shown. We have the briefs that are on my pad when I'm recording the conversation. We have clips we've never released. We have behind the scenes conversations with the guest, and also the episodes that we've never, ever released, and so much more.

1:22:37

In the circle, you'll have direct access to me. You can tell us what you want this show to be, who you want us to interview, and the types of conversations you would love us to have. But remember, for now, we're only inviting the first 10,000 people that join before it closes. So if you wanna join our private closed community, head to the link in the description below or go to d o a c circle dot com.

1:22:58

I will speak to you there. I'm continually shocked by the types of individuals that listen to this conversation. Um, because they come up to me sometimes. So I hear from politicians, I hear from some royal people, I hear from entrepreneurs all over the world, whether they are the entrepreneurs building some of the biggest companies in the world, or they're, you know, early stage startups. For those people that are listening to this conversation now that are in positions of power and influence, world leaders, let's say, what's your message to them?

1:23:26
Geoffrey Hinton

I'd say what you need is highly regulated capitalism. That's what seems to work best.

1:23:31
Steven Bartlett

And what would you say to the average person? Not doesn't work in the industry, somewhat concerned about the future, doesn't know if they're helpless or not. What should they be doing in their own lives?

1:23:43
Geoffrey Hinton

My feeling is there's not much they can do. This isn't, isn't going to be decided by just as climate change isn't going to be decided by people separating out the plastic bags from the UM compostables. That's not gonna have much effect. It's gonna be decided by whether the lobbyists for the big energy companies can be kept under control. I don't think there's much people can do to accept for try and pressure their governments to force the big companies to work on A I safety that they can do.

1:24:21
Steven Bartlett

You've led a fascinating, fascinating, winding life. I think one of the things most people don't know about you is that your family has a big history of being involved in tremendous things. You have a family tree, which is one of the most impressive that I've ever seen or read about. Your great great grandfather George Bull founded the Boolean algebra logic, which is one of the foundational principles of modern computer science. You have, uh, your great great grandmother, Mary Everest Bull, who was a mathematician and educator who made huge leaps forward in mathematics.

1:24:56

From what I was able to ascertain, um, I mean, I can, the list goes on and on and on. I mean, your great great uncle George Everest is what Mount Everest is named after. Is that is that correct?

1:25:09
Geoffrey Hinton

I think he's my great, great, great uncle. His his niece married George Bull, so Mary Mary Bull was Mary Everest Bull, and she was the niece of Everest.

1:25:23
Steven Bartlett

And your first cousin once removed, Joan Hinton, was involved in the new, uh, nuclear physicist who worked on the Manhattan Project, which is the World War II development of the first nuclear bomb.

1:25:33
Geoffrey Hinton

Yeah, she was one of the two female physicists at Los Alamos. And then after they dropped the bomb, she moved to China.

1:25:42
Steven Bartlett

Why?

1:25:43
Geoffrey Hinton

She was very cross with him dropping the bomb, and her family had a lot of links with China. Her mother was friends with Chiang. Mm. Quite weird,

1:25:57
Steven Bartlett

When you look back at your life, Geoffrey, with h the hindsight you have now and the retros retrospective clarity, what might you have done differently if you were advising me?

1:26:10
Geoffrey Hinton

I guess I have two pieces of advice. One is if you have an intuition that people are doing things wrong and there's a better way to do things, don't give up on that intuition. Just cause people say it's silly. Don't give up on the intuition until you figured out why it's wrong, figured out for yourself why that intuition isn't correct. And usually it's wrong if it disagrees with everybody else, and you'll eventually figure out why it's wrong.

1:26:40

But just occasionally, you'll have an intuition that's actually right and everybody else is wrong. And I lucked out that way. Early on, I thought neural nets are definitely the way to go to make A I, and almost everybody said that was crazy, and I stuck with it because I couldn't. It such seemed to me it was obviously right. Now, the idea that you should stick with your intuitions isn't going to work if you have bad intuitions.

1:27:08

But if you have bad intuitions, you're never going to do anything anyway, so you might as well stick with them.

1:27:14
Steven Bartlett

And in your own career journey, is there anything you look back on and say, with the hindsight I have now, I should have taken a different approach at that juncture?

1:27:23
Geoffrey Hinton

I wish I'd spent more time with my wife, um, and with my children when they were little. I was kind of obsessed with work. Your wife passed away Yeah,

1:27:41
Steven Bartlett

from ovarian cancer.

1:27:43
Geoffrey Hinton

no, oh, that was another wife. Um, I had two wives die of cancer.

1:27:48
Steven Bartlett

oh, really sorry.

1:27:49
Geoffrey Hinton

The first one died of ovarian cancer and the second one died of pancreatic cancer

1:27:53
Steven Bartlett

And you wish you'd spent more time with her.

1:27:55
Geoffrey Hinton

with the second wife. Yeah, who was a wonderful person.

1:27:59
Steven Bartlett

Why do you say that in your seventies? What is it that you've, you've figured out that I might not know yet?

1:28:05
Geoffrey Hinton

Oh, just cause she's gone and I can't spend more time with her now.

1:28:10
Steven Bartlett

But you didn't know that at the time.

1:28:14
Geoffrey Hinton

At the time, you think, I mean, it was likely I would die before her, just cause she was a woman and I was a man. Um, I didn't, I just didn't spend enough time when I could.

1:28:28
Steven Bartlett

I I think I I inquire there because I think there's many of us that are so consumed with what we're doing professionally that we kind of assume, um, or more immortality with our partners because they've always been there. So we, I mean, I'm

1:28:39
Geoffrey Hinton

and she was very supportive of me spending a lot of time working. But

1:28:43
Steven Bartlett

and why do you say your children as well? What's the what's the

1:28:46
Geoffrey Hinton

or I didn't spend enough time with them when they were little.

1:28:50
Steven Bartlett

and you regret that now? If you, um, if you had a closing message for for my, for my listeners about AI and AI safety, what would that be, Geoffrey?

1:29:04
Geoffrey Hinton

there's still a chance that we can figure out how to develop A I that won't want to take over from us. And because there's a chance, we should put enormous resources into trying to figure that out, cause if we don't, it's going to take over.

1:29:19
Steven Bartlett

And are you hopeful?

1:29:21
Geoffrey Hinton

I just don't know. I'm agnostic.

1:29:24
Steven Bartlett

You must get get better, get in bed at night, and when you're thinking to yourself about probabilities of outcomes, there must be a bias in one direction. Cause there certainly is for me. I me imagine everyone listening now has a internal prediction that they might not say out loud, but of how they think it's going to play out.

1:29:43
Geoffrey Hinton

I really don't know, I genuinely don't know. I think it's incredibly uncertain. When I'm feeling slightly depressed, I think people are toast, A I is going to take over. When I'm feeling cheerful, I think we'll figure out a way.

1:29:58
Steven Bartlett

Maybe one of the facets of being a human, um, is because we've always been here, like we were saying about our loved ones and our relationships. We assume casually that we will always be here and we'll always figure everything out. But there's a beginning and an end to everything, as we saw from the dinosaurs. Don't we?

1:30:14
Geoffrey Hinton

yeah, and we have to face the possibility that unless we do something soon, we're near the end.

1:30:27
Steven Bartlett

We have a closing tradition on this podcast where the last guest leaves a question in their diary. And the question that they've left for you is with everything that you see ahead of us, what is the biggest threat you see to human happiness?

1:30:49
Geoffrey Hinton

I think the joblessness is a fairly urgent short-term threat to human happiness. I think if you make lots and lots of people unemployed, even if they get universal basic income, um, they're not gonna be happy Because they need purpose because they need purpose. Yes,

1:31:07
Steven Bartlett

and structure.

1:31:07
Geoffrey Hinton

they need to feel they're contributing something, they're useful.

1:31:11
Steven Bartlett

And do you think the outcome that there's gonna be huge job displacement is more probable than not?

1:31:16
Geoffrey Hinton

Yes, I do. And what's the time That one, I think, is definitely more probable than not. If I worked in a call center, I'd be terrified.

1:31:25
Steven Bartlett

and what's the time frame for that? In terms of mass job I think it's beginning displacement?

1:31:29
Geoffrey Hinton

to happen already. I read an article in the Atlantic recently that said it's already getting hard for university graduates to get jobs, and part of that may be that people are already using A I for the jobs they would have got.

1:31:44
Steven Bartlett

I spoke to the C E O of a major company that everyone will know of lots of people use. And he said to me in D M s that they used to have seven, just over 7,000 employees. He said, Uh, by last year, they were down to, I think, 5,000. He said, Right now, they have 3,600, and he said, by the end of summer, because of A I agents, they'll be down to 3,000.

1:32:03

So you've

1:32:04
Geoffrey Hinton

So it's happening already.

1:32:05
Steven Bartlett

yes, he's halved his workforce because A I agents can now handle eighty of the customer service inquiries and other things, so it's it's happening already. So urgent action is needed. I don't know what that urgent action is.

1:32:20
Geoffrey Hinton

that's a tricky one because that depends very much on the political system, and political systems are all going in the wrong direction at present.

1:32:28
Steven Bartlett

I mean, what do we need to do? Save up money? Like, do we save money? Do we move to another part of the world?

1:32:33
Geoffrey Hinton

I don't know.

1:32:35
Steven Bartlett

What would you tell your kids to do? They said, Dad, like, there's gonna be loads of just job displacement.

1:32:40
Geoffrey Hinton

Because I worked for Google for ten years, they have enough money, Okay, okay, fuck so they're not typical.

1:32:47
Steven Bartlett

what if they didn't have money?

1:32:48
Geoffrey Hinton

Trained to be a plumber.

1:32:50
Steven Bartlett

Really? Geoffrey, thank you so much. You're the first Nobel Prize winner that I've ever had a conversation with, I think, in my life. So that's a tremendous honor. And you, you, you received that award for a lifetime of exceptional work in pushing the world forward in so many profound ways. That will lead to great and that have led to great advancements and things that matter so much to us. And now you've turned this season in your life to shining a light on some of your own work, but also on the the the broader risks of A I and how, um, and how it might impact us adversely.

1:33:26

And there's very few people that have worked inside the the machine of a Google or a big tech company that have contributed to the field of A I. That are now at the very forefront of warning us against the very thing that they worked upon.

1:33:39
Geoffrey Hinton

th. There are actually a surprising number of us now.

1:33:43
Steven Bartlett

They're not as, uh, as public, and they're actually quite hard to get to have these kinds of conversations because many of them are still in that industry. So, you know, someone who tries to contact these people often and ask invites them to have conversations. They often are a little bit hesitant to speak openly, so they speak privately, but they're less willing to openly, because maybe maybe they still have something, some sort of incentives at play.

1:34:05
Geoffrey Hinton

I have an advantage over them, which is I'm I'm older, so I'm unemployed, so I can say what I like.

1:34:09
Steven Bartlett

Well, there you go. So thank you for doing what you do. It's a real honor and please do continue to do it.

1:34:14
Geoffrey Hinton

Thank you.

1:34:14
Steven Bartlett

Thank you so much.

1:34:19
Geoffrey Hinton

People think I'm joking when I say that, but I'm not.

1:34:22
Steven Bartlett

The plumbing fish.

1:34:22
Geoffrey Hinton

Yeah, and plumbers are pretty well paid.

1:34:26
Steven Bartlett

This episode is sponsored by Asana. Let me, uh, admit something to you. I'm a little bit messy. I have got A D H D and sometimes I forget things. I'll put something in Google Drive, I'll put something on my desktop, it's all over the shop. And I can't imagine how much that is costing me as an entrepreneur or as a creative. I never thought of this as a project management problem, I just thought of it as a me problem.

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1:36:02

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