CBS. 60 MINUTES. “Godfather of AI” Geoffrey Hinton: The 60 Minutes Interview. 09 OCT 2023.

There’s no guaranteed path to safety as artificial intelligence advances, Geoffrey Hinton, AI pioneer, warns. He shares his thoughts on AI’s benefits and dangers with Scott Pelley.

“Maybe we look back and see this as a kind of turning point when humanity had to make the decision about whether to develop these things further. And what to do to protect themselves if they did. I don’t know. I think my main message is there’s enormous uncertainty about what’s going to happen next. These things do understand. And because they understand we need to think hard about what’s going to happen next. And we just don’t know.” – Geoffrey Hinton


whether you think artificial

intelligence will save the world or end

it you have Jeffrey Hinton to thank

Hinton has been called The Godfather of

AI a British computer scientist whose

controversial ideas help make advanced

artificial intelligence possible and so

change the world Hinton believes that AI

will do enormous good but tonight he has

a warning he says that AI systems may be

more intelligent than we know and

there’s a chance the machines could take

over which made us ask the

question the story will continue in a

moment does Humanity know what it’s



um I think we’re moving into a period

when for the first first time ever we

may have things more intelligent than us

you believe they can understand yes you

believe they are intelligent yes you

believe these systems have experiences

of their own and can make decisions

based on those experiences in the same

sense as people do yes are they

conscious I think they probably don’t

have much self-awareness at present so

in that sense I don’t think they’re

conscious will they have self-awareness

consciousness I oh yes I think they will

in time and so human beings will be the

second most intelligent beings on the

planet yeah Jeffrey Hinton told us the

artificial intelligence he set in motion

was an accident born of a failure in the

1970s at the University of Edinburgh he

dreamed of simulating a neural network

on a computer simply as a tool for what

he was really studying

the human brain but back then almost no

one thought software could mimic the

brain his PhD advisor told him to drop

it before it ruined his career Hinton

says he failed to figure out the human

mind but the long Pursuit led to an


version it took much much longer than I

expected it took like 50 years before it

worked well but in the end it did work

well at what point did you realize that

you were right about neural networks and

most everyone else was wrong I always

thought I was

right in 2019 Hinton and collaborators

Yan laon on the left and yosua Beno won

the touring award the Nobel Prize of

computing to understand how their work

on artificial neural networks helped

machines learn to learn let us take you

to a a

game look at that oh my goodness this is

Google’s AI lab in London which we first

showed you this past April Jeffrey

Hinton wasn’t involved in this soccer

project but these robots are a great

example of machine learning the thing to

understand is that the robots were not

programmed to play soccer they were told

to score they had to learn how on their

own oh

go in general here’s how AI does it

Henton and his collaborators created

software in layers with each layer

handling part of the problem that’s the

so-called neural network but this is the

key when for example the robot scores a

message is sent back down through all of

the layers that says that pathway was

right likewise when an answer is wrong

that message goes down through the

network so correct connections get

stronger wrong connections get weaker

and by trial and error the machine

teaches itself you think these AI

systems are better at learning than the

human mind I think they may be yes and

at present they’re quite a lot smaller

so even the biggest chatbots only have

about a trillion Connections in them the

human brain has about 100 trillion and

yet in the trillion Connections in a

chatbot it knows far more than you do in

your 100 trillion connections which

suggests it’s got a much better way of

getting knowledge into those connections

a much better way of getting knowledge

that isn’t fully understood we have a

very good idea of sort of roughly what

it’s doing but as soon as it gets really

complicated we don’t actually know

what’s going on anymore than we know

what’s going on in your brain what do

you mean we don’t know exactly how it

works it was designed by people no it

wasn’t what we did was we designed the

learning algorithm that’s a bit like

designing the principle of evolution but

when this learning algorithm then

interacts with data it produces

complicated neural networks that are

good at doing things but we don’t really

understand exactly how they do those

things what are the

implications of these systems

autonomously writing their own computer

code and executing their own computer

code that’s a serious worry right so one

of the ways in which these systems might

Escape control is by writing their own

computer code to modify

themselves and that’s something we need

to seriously worry about what do you say

to someone who might argue if the

systems become benevolent just turn them

off they will be able to manipulate

people right and these will be very good

at convincing people because they’ll

have learned from all the novels that

were ever written all the books by

makavelli all the political connives

they’ll know all that stuff they’ll know

how to do it knoow of the human kind

runs in Jeffrey hinton’s family his

ancestors include mathematician George

buou who invented the basis of computing

and George Everest who surveyed India

and got that mountain named after him

but as a boy Hinton himself could never

climb the peak of expectations raised by

a domineering father every morning when

I went to school he’d actually say to me

as I walked down the driveway get in

their pitching and maybe when you’re

twice as old as me you’ll be half as

good dad was an authority on Beatles he

knew a lot more about beatles than he

knew about people did you feel that as a

child a bit yes

when he died we went to his study at the

University and the walls were lined with

boxes of papers on different kinds of

beetle and just near the door there was

a slightly smaller box that simply said

not insects and that’s where he had all

the things about the

family today at 75 Hinton recently

retired after what he calls 10 happy

years at Google now he’s professor

ameritus at the University of Toronto

and he happened to mention he has more

academic citations than his father some

of his research led to chatbots like

Google’s Bard which we met last spring

confounding absolutely confounding we

asked Bard to write a story from six

words for sale baby shoes never

worn holy cow the shoes were a gift from

my wife but we never had a baby Bard

created a deeply human tale of a man

whose wife could not conceive and a

stranger who accepted the shoes to heal

the pain after her miscarriage I am


speechless I don’t know what to make of

this chatbots are said to be language

models that just predict the next most

likely word based on probability you’ll

hear people saying things like they’re

just doing autocomplete they’re just

trying to pred the next word and they’re

just using

statistics well it’s true they’re just

trying to predict the next word but if

you think about it to predict the next

word you have to understand the

sentences so the idea they just

predicting the next word so they’re not

intelligent is crazy you have to be

really intelligent to predict the next

word really accurately to prove it

Hinton showed us a test he devised for


gp4 the chatbot from a company called

open AI it was sort of reassuring to see

a turing Award winner mistype and blame

the computer oh damn this thing we’re

going to go back and start again that’s

okay hinton’s test was a riddle about

house painting an answer would demand

reasoning and

planning this is what he typed into chat

gp4 the rooms in my house are painted

white or blue or yellow and yellow paint

Fades to White within a year in two

years time I’d like all the rooms to be

white what should I do the answer began

in one second gp4 advised the rooms

painted in blue need to be repainted the

rooms painted in yellow don’t need to be

repainted because they would Fade to

White before the deadline and oh I

didn’t even think of that it warned if

you paint the yellow rooms white there’s

a risk the color might be off when the

yellow Fades besides it advised you’d be

wasting resources painting rooms that

were going to Fade to White anyway you

believe that chat GPD

4 understands I believe it definitely

understands yes and in five years time I

think in 5 years time it may well be

able to reason better than us reasoning

that he says is leading to ai’s risks

and great

benefits so an obvious area where

there’s huge benefits is Healthcare AI

is already comparable with Radiologists

at understanding what’s going on in


images it’s going to be very good at

designing drugs it already is designing

drugs so that’s an area where it’s

almost entirely going to do good I like

that area the risks are

what well the risks are having a whole

class of people who are

unemployed and not valued much because

what they what they used to do is now

done by machines other immediate risks

he worries about include fake news

unintended bias in employment and

policing and autonomous Battlefield

robots what is a path forward that


safety I don’t know I I can’t see a path

that guarantees

safety that we’re entering a period of

great uncertainty where we’re dealing

with things we’ve never dealt with

before and normally the first time you

deal with something totally novel you

get it wrong and we can’t afford to get

it wrong with these things can’t afford

to get it wrong why well because they

might take over take over from Humanity

yes that’s a possibility why would they

saying it will happen if we could stop

them ever wanting to that would be great

but it’s not clear we can stop them ever


to Jeffrey Hinton told us he has no

regrets because of ai’s potential for

good but he says now is the moment to

run experiments to understand AI for

governments to impose regulations and

for a world treaty to ban the use of

military robots he reminded us of Robert

Oppenheimer who after inventing the

atomic bomb campaigned against the

hydrogen bomb a man who changed the

world and found the world Beyond his

control it maybe we look back and see

this as a kind of Turning Point when

Humanity had to make the decision about

whether to develop these things further

and what to do to protect themselves if

they did um I don’t know I think my main

message is there’s enormous uncertainty

about what’s going to happen

next these things do

understand and because they understand

we need to think hard about what’s going

to happen next and we just don’t