"Godfather of AI" Geoffrey Hinton: The 60 Minutes Interview

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. doing no. um I think we're moving into a period. when for the 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. artificial. 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 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. chatot 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 knowhow 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. rarely. 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 predict 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. chat. 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 2 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 5 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 great. 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. medical. 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. ensures. 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. want I'm not saying it will happen if we. could stop them ever wanting to that. would be great but it's not clear we can. stop stop them ever wanting.

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 camp campaigned against the.

hydrogen bomb a man who changed the. world and found the world Beyond his. control it may be 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 know.