Fmr. Google CEO Eric Schmidt on the Consequences of an A.I. Revolution | Amanpour and Company

now from hyperbolic headlines about its threat to our survival to the promise of its life-changing technology artificial intelligence is here and it is here to stay how it's applied and more importantly how it's regulated are the questions being navigated right now Walter Isaacson speaks to the former CEO of Google Eric Schmidt about ai's impact on life politics and warfare and what can be done to keep it under control thank you Chris John and Eric Schmidt welcome to the show thanks for having me Walter you know industrial and scientific and technological Revolution sometimes sneak up on us I mean nobody woke up one morning in 1760 and said oh my God the industrial revolution has started but in the past three or four weeks between my students and myself we suddenly feel we're in a revolution where artificial intelligence has become personal it's become chat Bots and things that'll integrate into our lives do you think we're on the cusp of some new Revolution I do and partly this revolution is happening faster than I've ever seen uh chat GPT which was released a few months ago now has more than 100 million users it took Gmail five years to get to the same point there's something about the diffusion of technology that we interact with at the human scale that's going to change our world in a really profound way much more profound than people think you and Henry Kissinger and Daniel Hutton Loker have written a book the age of AI and I think part of it is excerpted or there's an essay in the Wall Street Journal and it Compares this to the Advent of the Enlightenment something I think that was spurred to by great technology which is movable type printing presses at uh Gutenberg did compare what's happening now to the enlightenment we do not have a philosophical basis for interacting with an intelligence that's near our ability but non-human we don't know what happens to our identity how we communicate how we think about ourselves when these things arrive now these things are not Killer Robots which was what everybody assumes we're building because we're not doing that what is arriving is a kind of intelligence that's different it comes to answers differently than we do it seems to have hidden understanding and meaning that we don't understand today it discovers things that we've never known we don't know how far this goes but the biggest issue is that as we've made these things bigger and bigger they keep emerging with new capabilities we have not figured out how powerful this technology is going to be yet we've had AI for 20 years now that's been part of our technology but now it's becoming very personal it's things we do every day a normal person like myself whether I'm doing search or I'm writing an email or I'm preparing a lecture at Tulane suddenly these are tools it's almost like when the computer went from being in a really big room in a research institute and suddenly you had it in the 1970s it arrived as a personal computer tell me about this transformation of AI to being something personal the systems are organized to essentially engage you more and the reason they want to engage you more is if you engage more you use it more they make more money so what they do is they learn what your preferences are using various algorithms and so they say ah Walter likes this and Eric likes that and so forth and they build a profile now that profile is not a dossier and it's not written in English and so forth but it's a pretty good approximation of what you like and what you think and then the algorithms know how to make you more engaged by the way the best way to get you more engaged is to make you more outraged and the best way to make you more outraged is to use more inflammatory language and so forth well let's stop right there because that means this could destroy our politics well it will and the reason it's going to is that not only will the opponents of a political figure produce videos that are false and harmful but also the messaging is going to get more and more outrageous and you can get a situation and I call this the Dual evil problem let's say that URI was a truly horrific person which we're not somebody who's a racist or something like that and we have the diffusion model generate a racist video and then the other of us is some sort of Psychopathic social media person who doesn't care about the quality and all he wants to make it worse so what happens is my computer makes a racist video on my behalf and does a good job and then your computer system knowing that it will get even more Revenue if it's more outrageous makes it worse right so you see how it goes one way now let's say that you and I were Saints and the sense that I did something saintly and that you were the world's best social media person you would take my sanely thing and you would make it more sanely so you see how it pushes to the sides and and my theory about life today is the reason everyone's upset is because the social media is busy trying to make us upset so the algorithms of social media Twitter Facebook many other things I try to get engagement by getting enragement by getting us upset you just said and what you're saying is that added to this will be these new AI systems that will make this even worse is that right we've got a situation where we have megaphones of people who we frankly don't want to hear about and they're going to find an audience and they're going to find it a big audience because they're going to do crazy stuff that's not okay in my view in a democracy democracies are at some level about reason debate and these systems will drive against that I don't see a solution today from this except that we're going to have to regulate some of it for example we're going to have to know who's on the platform to hold them responsible for if they do something really outrageous or illegal and we're also going to have to know where the content came from we're going to know have to know if it was authentic or if it was boosted and changed in some way and we're also going to have to know how the platform makes its own decisions all of those are sensible improvements so we can understand why we're being fed this information so who is going to determine these guard rails and how are we going to get them in place internationally well in Europe it's already part of the legislation and some form of agreement in America between the government and the industry is going to be required I don't think we need to get rid of free speech or any of those things although there are people who've proposed that we can't even have free speech from my perspective the technology of Engagement is generally good if you take the guard rails around and you keep the most extreme cases off the platform forms but my point about generative AI is these systems are going to soup up engagement and soup up your attention there's an old phrase about what the currency of the future in economics is attention and these systems are looking for your attention as a consumer so every time you go oh my God I had no idea remember that it's trying to get you to have that reaction now going back to the generative AI combined with large language models it's going to do some other things that are particularly powerful it will be able to generate insights and ideas that we as humans have not had think of them as existing as savants if I'm a physicist I'll have a savant that runs around and suggests physics problems for me to work on and that sort of thing all of that is very good so the power of AI in terms of improving science and biology and human health will be extraordinary but it comes with this impact on our on our societal discourse it's not going to be easy to get through this you say we don't understand how they make these decisions now it used to be with AI and with computers we wrote programs they were step by step and they were rules based and it was if this then do this these new systems seem to just look at billions of pieces of information and of human behaviors and everything else and they aren't following any rules that we give them does that what is that what makes them both amazing and dangerous yes my whole world was we get computers to do things because we tell it what to do and step by step and it got better and better but that's fundamentally the as built environment that we all use today with machine learning which has been in its current version available in one form or another for about a decade instead of programming it you learn it so the language that you say is can we learn what the right answer is it started off with classifiers where you'd say is this a zebra or a giraffe and that got pretty good then a technology called reinforcement learning came along which was allowed us to sort of figure out what to do next in a complicated multiplayer game and now these large language models have come along with this massive scale but the way to understand how you would both strengthen large language models and constrain them is to learn how to do it so in the the normal taxonomy you would describe we have this big thing that's doing weird stuff we want to learn what it's doing so we can stop it doing the bad things the problem with learning what it's doing is since its behavior is immersion is you have to run it for a while to understand and then you have to have humans decide this is bad right so the way chat gbt was so successful is that they invented a technique which ultimately involved humans telling it good bad good bads it wasn't fully done by computers the problem with good bad good bad with humans is eventually that doesn't scale but here's the real problem so far that sounds pretty good but in a situation where all of the software is being released there are what are called raw models which are unconstrained and the people who've played with the raw models say that they are these are ones that you and I can't get to as normal users say they're very frightening build me a copy of the 1918 bird flu virus show me a way to blow up this building and where to put the bomb things that are very very dangerous appears to have been discovered in the Raw versions of the models how do we keep those out of bad people's hands well the problem we don't today know how to do it and here's why imagine a situation where the model gets smarter and smarter and it's got this checking system you can imagine in a situation where the model gets smarter and smarter and it learns to whatever it's being checked to say the right answer but when it's not being checked to say what it really thinks and like uh how the computer in 2001 Space Odyssey is learning how to outwit the crew and by the way how would it do that well these things have what are called objective functions and they're trained and so if you give it a strongest a strong enough objective function to really surface the most interesting answer that may overwhelm the system that's trying to keep it under control and within appropriate guardrails these problems are today unsolved the reason we don't know how these work is they're essentially collections of numbers people have looked very hard at what essentially activation nodes where inside the Matrix and there are areas that seem to control the outcome but when you look at it on a microscope in in a computer sense you get the same sort of confusion if you look in a human brain in a human brain you say where did that thought come from you can't find it it's the same is true in these large language models so far well let me drill down on some case use cases that we might have you and I were once on the defense Innovation board for the U.S government and you've been involved in another commission on National Intelligence tell me how you think this will change the fighting of wars the biggest short-term concern is actually biological warfare um last year there was a group that did synthesis of a whole bunch of viruses to try to be helpful and then they use the same program the same algorithm the same large language model approach if you will to work it backward and come up with the world's worst and most terrible pathogens there's every reason to think that these Technologies when spread broadly will allow terrorist actions that we cannot possibly imagine this has got to get addressed people are working on this another thing that's happening is that the concept of war the concept of conflict is occurring much more quickly it looks like these systems have developed abilities to both do offensive and defensive cyber attacks they actually understand where the vulnerabilities are in ways we don't fully understand and they can be used to accelerate both offensive and defensive actions that means that a good chance in the future of a war war is a war that takes a millisecond right North Korea attacks the U.S the U.S attacks back China decides it's a bad time for war the whole thing occurred in a in a millisecond that's faster than human decision making time which means that our systems are defensive systems are going to have to be on a hair trigger and they're going to have to be invoked by AI that we don't fully understand you know the first time I talked about this in depth with you and with Henry Kissinger together was in China I think maybe three years ago and it was a question then and now more of a question of are we going to cooperate with China and trying to figure this out or is this the great new arms race that's going to happen and with our new confrontational attitude towards China is that going to make it harder to deal with the emergent technology of artificial intelligence well three years ago China announced its AI strategy because they love to announce their strategies and include dominating AI by 2030. so China of course has efforts in generative Ai and large languages models as well they also have large efforts in Quantum and biology which are doing well they're already ahead of us in 5G they're ahead of us in financial services and in terms of batteries new energy all the things that you use in your electric car so we should take them as a strong competitor in the case of large language models they have not been as advanced as the American companies have the American and UK companies for reasons I don't fully understand one idea that I would offer is that the large language models because they are unpredictable today cannot be offered to the public in China because the Chinese government does not want unfettered access to information in other words how do the Chinese government know that these systems are not going to talk about Channel and square or something which is not possible to talk in an area of lack of free speech so we will see but at the moment they're they're trying to catch up but they are behind we recently put in some restrictions on Hardware which will slow them down but not by much whenever there's a big Innovative change it moves the Arc of History sometimes towards more individual Freedom even the printing press you know takes away the hold of the Roman Catholic Church allows the Reformation allows the Renaissance even do you think this will inevitably push history to more individual Freedom or will it be used for more authoritarian purposes I'm sure the answer is both if you are another authoritarian dictatorship you know let's say a really bad one you would use these Technologies to both surveil your citizens but also manipulate them lie to them misinform them tell them things which are falsehoods cause them to be motivated against National National fears all of the things that governments and ideologues do in that case if you're a democracy you're going to use it first to try to improve your business situation and also because you believe in free speech you're going to allow people to say what they think the dangers to both are obvious for the autocracy it will so compound their control that it could lead to a revolution inside the autocracy people don't want this kind of restrictions that are possible in a democracy as we've discussed the concept of being able to flood the zone right the ability for a single individual to define the narrative who shouldn't otherwise have that kind of power is very palpable in these Technologies and it's really important that we understand that Human Nature has not changed if you show someone a video and you say to them this video is false at some basic level there's evidence that they still believe it to be true and you tell them up front pictures that have been seen cannot be unseen videos that have been seen cannot be unseen we have to confront the fact that humans are manipulable by these Technologies and we need to put the appropriate safeguards in place to make sure that we as a body populists are not so manipulated to the wrong outcome Alex Schmidt thank you so much for joining us thank you Walter and thank you again thank you foreign

Channel: Amanpour and Company

Views: 274,659

Keywords: interview, CNN, PBS, Christiane Amanpour, world news, news anchor, news show, news, public affairs, late-night TV, journalist, Chief International Correspondent, Google, Eric Schmidt

Id: Sg3EchbCcA0

Length: 18min 7sec (1087 seconds)

Published: Thu Mar 23 2023