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41,057 views 18 Dec 2024

The 2024 laureates in the fields of physics, chemistry, medicine and economic sciences talk to Zeinab Badawi and students in the audience at the Royal Palace in Stockholm about their discoveries and achievements, and how these might find a practical application.

TRANSCRIPT.  warm welcome to the Royal Palace and the badot library here you will find over 100,000 books a collection that used to belong to previous kings and queens of the House of badot offering a glimpse into their history and interests however today we’re here to listen to our esteemed Nobel laurates to their insights their expertise and their invaluable contributions to science and economics once again a very warm welcome to the Royal Palace in this program we’ll be looking at the potential and pitfalls of artificial intelligence why some countries are richer than others and what a worm tells us about the origins of life [Applause] [Music] [Applause] [Music] your Royal Highness thank you for that very warm welcome to your palace here in Stockholm and uh Nobel laurates this is the first time that some of you have been brought together in discussion on um television and we’re also joined by some of your family and friends as well as students from here in Stockholm um before we start let’s just give them a really big round of applause renewed congratulations to all of you I guess you’re all getting very used to the sound of Applause now aren’t you so tell me um how has winning the Nobel Prize changed your life uh who shall I start with Gary well the level of attention is something that’s a THX what it ever was for other Awards it’s you know the Nobel is a it’s a brand and it’s 120 something years of History to completely uh mesmerizing Daron one of the uh economists what about you how’s it changed your life I mean I’m here well being in Stockholm for one week in December that’s a life-changing event but I am amazingly grateful and happy honored and I’ll take it as it comes your diary is going to be super full from now on you’re going to be running around from lecture to lecture and guest appearances so Professor Jeffrey Hinton what about you um yeah it makes an amazing change I get huge amounts of email asking me to do things um I luckily have an assistant who deals with most of it um I get stopped for selfies in the street which is um it’s very annoying but if it went away I’d be disappointed but also you’ve been teaching for many years at the University of Toronto and you said after you won the Nobel Prize They At Last gave you an office yes they didn’t think I was worth an office before that James um I’ve noticed that people take what I say much more seriously I’ve always proceeded on the assumption that no one was ever actually listening to anything I said so now I have to really choose my words carefully yeah and does that extend to your family members as well or do they listen to what you say now um I’d have to think about that one David Baker uh well actually a highlight has really been this week and having all my my family and and colleagues here it’s been a great celebration and um yeah I’ve had to give up email which has been positive um and I’ve learned to completely avoid selfies so um but uh on the whole it’s been very exciting and you don’t travel light do you if I could put it that way just remind me how many people have you come with to Stockholm uh 185 I think that must be a record I’m going to have to check but I’m pretty sure that must be a record well it’s quite a party you’re going to have and uh sir Demis hassabis um well of course it’s been an honor of a lifetime and um to tell you the truth it hasn’t really sunk in yet so uh maybe I’ll do that over the Christmas holidays um but it’s also you know an amazing platform to talk about your subject more widely and have to think about that responsibility in the coming years mhm okay let’s turn now to the awards that were made this year and let’s start with the physics prize and here’s a brief summary of the research behind that prize this year’s physics prize rewards research that laid the foundations for the development of AI enabling machine learning with artificial neural networks John hopfield created a structure that can store and reconstruct information Jeffrey Hinton built on his ideas and made it possible to create completely new content with the help of AI so-called generative AI this opens up numerous potential areas of use for instance by providing techniques for calculating and predicting the properties of molecules and materials their research has also prompted extensive discussion of the ethics around how the technology is developed and used so Jeffrey Hinton you actually wanted to find out how the human brain works so how does it work we still don’t know we’ve made lots of efforts to figure out how the brain figures out how to change the strength of connections between two neurons we’ve learned a lot from these big systems that we’ve built which is if you could find any way to know whether you should increase or decrease the strength and then you just did did that for all of the connections all 100 trillion connections and you just kept doing that with lots of examples slightly increasing or decreasing the strength then you would get fantastic systems like gb4 these big chatbots learn thousands of times more than any one person so they can compress all of human knowledge into only a trillion connections and we have a 100 trillion connections and none of us know much but that’s but that’s interesting he says speak for yourself but anyway he does know a lot actually but compared with gbt so it make you you make it sound though as if this is the best computer and it’s never been bettered we don’t quite know how it works and yet you also say that artificial intelligence artificial neuron networks could outsmart humans oh I think we’ve been bettered already if you look at gbd4 it knows much more than any one person it’s like a not very good expert at everything um so it’s got much more knowledge in far fewer connections and we’ve been bettered in that sense do you agree with that Miss well look I think so I mean just going back to your initial question um originally in with with the with the field of AI there’s a lot of inspiration taken from architectures of the brain including neur networks and an algorithm called reinforcement learning um then we’ve gone into a kind of engineering phase now where we’re scaling these systems up to massive size all of these large Foundation models or language models uh and there’s many leading models now and I think we’ll we’ll end up in the next phase where we’ll start using these AI models to analyze our own brains and to help with Neuroscience as one of the sciences that AI helps with so actually I think it’s going of come sort of Full Circle neurosciences sort of inspired modern Ai and then AI will come back and um help us I think understand what’s special about the brain will machine intelligence outsmart humans I mean what what kind of time frame are you talking about are you saying it’s already happened so in terms of the amount of knowledge you can have in one system it’s clearly already happened right GB knows much more than any human yeah and it it does make stuff up but it still knows a lot yeah um in terms of the timing I think all the leading experts I know people like Demis um they believe it’s going to happen they believe these machines are going to get smarter than people at general intelligence and they just differ in how long they think that’s going to take well we’re going to start being bossed around by machines and robots is that what your suggestion well that’s the question um can you have things more intelligent than you and you still staying control once they’re more intelligent than us will they be the bosses or will we still be the bosses and what do you think I think we need to do a lot of research right now on how we Remain the bosses you didn’t actually answer that question dearis do you think that machine intelligence could outsmart outwits to the extent that actually they start ruling the roost no well look I think for now so I disagree with with with with Jeff on the fact that today’s systems are still not that good they’re impressive they can talk to us and other things they acquire a lot of knowledge um but they’re pretty weak at a lot of things they’re not very good at planning yet or reasoning um or uh imagining and you know creativity those kinds of things but they they are going to get better rapidly so it depends now on how we design those systems and how we um decide to sort of as a society deploy those systems and build those systems all right so we’ll look at what we do about it but gentlemen this is a very big fundamental question Gary and then you yeah I think you’re overrating humans in this so we make up a lot of untruths as well and uh there’s so many examples of false ideas that get propagated and and it’s getting worse of course with social networks so the standards for AI to do well it is it’s pretty low you humanity is way overrated right okay dve humans I I’ll I’ll take a contrarian view here um you know humans since the really the beginning of civilization have have created things that are um better at them than in almost every domain you know cars can go infinitely faster planes can fly humans can’t um you know for a long time we’ve had computers that can do calculations that humans can’t do um Demis has developed you know programs that solve go and chess so we’re very comfortable I think with machines being able to do things that we can’t do chat GP you know gp4 um has much more knowledge than any human being I think we just take this kind of thing in stride I don’t think we worry about losing control so I guess that’s the key issue that we know that computers can do a lot that we can’t but it’s question of control I mean planes fly but it’s the human pilot who’s in the cockpit assisted by technology obviously and we still drive cars yeah um what about you two The Economist where do you stand on this question I’ll take the opposite position to Gary I think humans are incredibly underrated right now human adaptability fluidity creativity but also Community I think humans are just amazing social animals we learn as collectives and as collectives we are able to do a huge number of things in very quick succession so I would worry about those people controlling AI before AI itself turning on us humankind’s greatest enemy is humankind the sort of do evils that we see in Popular Science fic who think they’re doing good I wouldn’t put those past doing huge damage yeah I would agree I mean as the tools get more powerful I think the worry is not the machines themselves but people using the tools misinformation autonomous military weapons all kinds of things humans have a great track record of inventing things you know that jeopardize the human race such as nuclear weapons I mean just think about how close we’ve been to obliterating the planet with the Cuba Cuban Missile Crisis and you know so so we’ve done it already we can do it again in a different form or you know with a diff so so so I guess I would I would like to ask Demis you know I I I take the point of view everyone’s saying yes we need to regulate we need to but who has the incentive to do that I don’t you know like it’s one thing to say that but but I I suspect the politicians and the governments they’re just playing catchup that you know the thing is moving faster than they can get their hands on and who in the private sector they just want to make money and get this stuff out there and so where where are the incentives to actually do something about that yeah well look I mean there’s obviously the reason that many of us are working on AI is because we want to bring to bear all of the incredible benefits that can happen with AI from in medicine but also productivity and so on but I agree with you there is a going to be a kind of coordination problem where um I think there has to be some form of international cooperation on these issues I think we’ve got a few years to get our act together on that and I think leading researchers and leading um labs in industry and Academia need to come together to kind of demand that sort of cooperation as we get closer to artificial general intelligence um and have more information about what that might look like but I’m I’m I’m a big believer in human Ingenuity and um as David says you know we’re unbelievably adaptive as a species and you know look at our modern technology we already use today that we sort of seamlessly the younger generation just seamlessly adapts to and takes as a given and I think that’s also happened with these chat Bots which you know 25 years ago we would have been amazed those of us in this in the area of AI if you were to transport the Technologies back we have today back then um and yet we’ve all um Society seems to have sort of seamlessly adapted to that as well Jeffrey Hinton do you see that happening you’ve raised the alarm Bells about humans becoming subservient in a way to to machines um do you think that there’s enough of a debate at an international level do we need more Ethics in science to debate these kind of issues do you see that happening so to distinguish two kinds of risks from AI one is relatively shortterm and that’s to do with Bad actors and that’s much more urgent um that were that’s going to be obvious with lethal autonomous weapons which all the big defense departments are developing and they have no intention of not doing it the European regulations on AI say none of these regulations apply to military uses of AI so they clearly intend to go ahead with all that and there’s many other short-term risks like cyber crime um generating bad pathogens fake videos surveillance all of those short-term risks are very serious and we need to take them seriously and it’s going to be very hard to get collaboration on those then the long-term risk that these things will get more intelligent than us and they’ll be agents they’ll act in the world and they’ll decide that they can achieve their goals better which we gave them the goals and they can achieve them better if they just brush us aside and get on with it um that particular risk the existential threat is a place where people will cooperate and that’s because because we’re all in the same boat nobody wants these AIS to take over from people and so the Chinese Communist party doesn’t want AI to be in control it wants the Chinese Communist party to be in control you know for somebody who’s described as the Godfather of AI you sound quite a bit down on it in so many ways well it’s potentially very dangerous it’s potentially very good and potentially very dangerous and I you know I think we should be making a huge effort now into making sure we can get the good aspects of of it without the bad possibilities and it’s not going to happen automatically like he says well we’ve got some students in the audience here and I know that some of them want to pose a question to you Lau prashan yadava from the kth AI Society your question please I’d like to know in what ways AI can be put to use uh in bringing truly democratic values and bringing economic equalities to the world so in what way can AI promote democ Ry and equality in the world who’s going to answer that one I can start off I mean I I think um as we’ve discussed actually for most of the conversation you I think powerful Technologies in of themselves are um kind of like neutral they could go good or bad depending on what we as society decide to do with them and I think AI is just the latest example of that in that case maybe it’s going to be the most powerful thing and most important that we get right but it’s also on the optimistic end I think it’s one of the challenges it’s the only challenge I can think of that could be useful to address the other challenges if we get it right so um so that’s the key um I don’t know you know democracy and other things that’s better out scope maybe it’s for the economist to talk about well I’ll I’ll just say I think AI is an informational tool and it would be most useful and most uh enriching for us in every respect if it’s useful reliable and enabling information for everybody not just for somebody sitting at top to manipulate others but enabling for Citizens for example enabling for workers of different skills to do their tasks all of those are aspects of democratization but we still have a long way to go for that sort of tool to be available in a widespread way and not be manipulable let’s go for another question now from our audience Al karini papasu from the Stockholm School of Economics your question please uh hello thank you uh my question regards how do you think philosophy and science coexist um we have a very deep need for more philosophy and great endon perhaps There’s an opportunity for some new great philosophers to appear um to help us through the next phase of technological development um in my view that that is going to require depending on your definition of philosophy um some uh uh deep thinking and and wider Thinking Beyond the technology itself yeah absolutely I think actually one of the things with the advances in AI we will need to understand much better what makes us conscious what makes us human there might be some stumbling blocks that will make us delve deeper into some of these questions but even if advances in AI are very fast we will need to question our own existence and what makes that more meaningful certainly we need ethics but the kind of philosophy we don’t need I think is philosophers talking about Consciousness and sentience and subjective experience I think understanding those is a scientific problem and we’ll be better off without philosophers anybody else on this no all right thank you very much but let’s turn now to um some of the work that has contributed to the award for the chemistry prize this year for Demis cabis David Baker along with John jumper and let’s just get a brief idea of the research that led to the chemistry Nobel Prize award the ability to figure out quickly what proteins look like and to create proteins of your own has fundamentally changed the development of chemistry biology and medical science by creating the AI program Alpha fold 2 this year’s chemistry laurates Demis hassabis and John jumper have made it possible to calculate the shape of proteins and thereby understand how the building block of life Life Works the second half of this year’s award goes to David Baker for what’s been described as the almost impossible feat of building entirely new kinds of proteins useful not least for producing what could block the SARS Cove 2 virus making new proteins can simply open up whole new worlds so let’s start with you David Baker you’ve been applauded for creating these new proteins and actually you didn’t even want to become a scientist in the first place so it’s quite amazing that You’ now got this Nobel Prize but just tell us what kind of um applications implications do you think your work has uh led to or could lead to yeah I think following up on our previous discussion um I think I can really talk about the the really real power of AI to do good so um some of the proteins in nature uh solve all the problems that came up during Evolution and we face all kinds of new problems in the world today you know we live longer so neur neurodegenerative diseases are important we heating up and pling the planet and these are really existential problems and uh now um you know maybe with Evolution another 100 million years proteins would evolve that would help address these but with protein design we can now design proteins to uh try and deal with these today and so we’re designing proteins completely new proteins to do things ranging from breaking down plastic that’s been released into the environment to um uh combating neurod degenerative disease and and cancer and de sis of course you’re well known for being a co-founder of Deep Mind the machine Learning Company and uh I mean you’re a chess uh Champion you’re a child prodigy really um you know making video games when you’re only in your team so here you are you’ve got a Nobel Prize under your belt as well um but you’ve already actually started using the research that for which you were awarded the prize along with John jumper that’s right so we we are with our own collaborations um uh we’ve been uh working with uh institutes like the drugs for neglected diseases part of the who uh and uh indeed because if you reduce the cost of of understanding what these proteins do you can go straight to drug design um that can help uh with a lot of the diseases that affect the poorer countries of the world where big farmer won’t go because there isn’t a return to be made so but in fact it affects uh you know a larger part of the of the world’s population so um I think these these Technologies actually going back to our earlier conversation will help a lot of the poorer parts of the world by making the cost of Discovery so much um so much lower you know that it’s within the scope then of Nos and nonprofits anybody else want to chip in on this I mean I mean obviously I think this is just an amazing opportunity for science anything we can use to improve the scientific process can have can have not necessarily will have have can have great benefits but that doesn’t change some of the tenor of the earlier conversation great tools also still create great risks Fritz harber you know a Nobel Prize winner for work on which we depend every day with uh synthetic fertilizers you know also made chemical weapons for the German Army in World War one and directly causing the deaths of hundreds of thousands of people so the responsibility of scientist with powerful tools is no less we’re seeing skepticism in all sorts of positions of power now aren’t we um all over the world is is that something that worries you that policy makers don’t perhaps understand the full complexity of science be climate science or or you know other difficult issues well I would say it’s also part of our responsibility that we have to work harder in getting people to trust science I think there is much greater skepticism about science and I don’t know I don’t think anybody knows exactly why but it is part of the general polarization but it’s also probably the way that we are not properly communicating the uncertainties in science the disagreements in science what we are sure and what we are not sure so I think we do have a lot more responsibilities in building the Public’s trust in the knowledge that’s usable in order for that knowledge to be seamlessly applicable to good things Demis and then maybe Gary yeah yeah I think um I I agree with that and uh I think in the in just in the realm of AI I feel like um one of the benefits of uh the sort of chatbot era is AI is much more than just chatbots you know it’s scientific tools and other things and and but that it has brought it to the Public’s Consciousness and also made governments more aware of it and sort of brought it out of the realm of Science Fiction and I think that’s good because I think in the last couple of years I’ve seen a lot more convening of government Civil Society um academic institutes to discuss the broader uh issues beyond the Technologies which I totally agree with by the way including things like what new institutes do we need how do do we distribute the the benefits of this uh uh widely um that’s a societal problem it’s not a technal technological problem and um we need to have a broad debate about that and we’ve started seeing that we’ve had a couple of um Global safety Summits about a one in the UK one in South Korea next one’s in France um and I think we need actually a higher intensity and more rapid discussion around those issues Gary do you want to come in here yeah I the engine of Western economies in terms of the revolution in the last 50 years has been technology and and uh science and Silicon Valley and that sort of thing in terms of and and um if you wanted to if you’re an enemy of the West you want to destabilize that and so I think this whole Social Network I don’t trust technology I don’t trust any of the Enterprises I don’t think that’s evolved naturally I think that’s been manipulated by bad agents and uh we have to be aware of that which bad agents I I think it’s Russia and Iran I I don’t think it’s stupid to say that and uh politics yeah they’re not not looking in our best interests I think there’s other bad agents too I probably the energy industry would like you not to believe in climate change just like the tobacco industry knew very well that cigarettes cause cancer but they hid that fact for a long time you know if we cannot trust the energy companies we cannot trust pharmaceutical companies tobacco companies can we trust the tech companies which are extremely concentrated and if AI is so important what about uh the power of tech companies I don’t know why ask me I don’t work for a tech so you have an objective opinion no no but that’s that’s one aspect of the risks of AI that we didn’t talk about okay well but just to take a more positive point of view again I mean despite the skepticism of about science and certainly um you don’t have to look far in the US it should be pointed out that it was the response to covid with the MRNA vaccines was truly miraculous it was a technology that really had not been proven at at all and in very little time because it was it was this thing about having a common enemy and and a threat um you know we were able to mobilize very quickly try something really completely new and bring it to the point where it uh did a huge amount of good so um uh so there there reasons to be optimistic that were other threats to appear that uh a lot of the silliness would sort of filter out and um the correct actions would be taken and the Skeptics died okay well on that positive not let’s just pause there for a moment and let’s turn to the economics Nobel Prize and let’s see why the award was made this [Music] year this year’s prize in economics touches on historical injustices and cruelties as well as current events too the question of how economic development is connected to individual rights equality and decent political leaders when large parts of the world were colonized by European powers their approaches varied derone asoglu Simon Johnson and James Robinson have shown that Prosperity Rose in places where the colonial authorities built functioning social institutions rather than simply exploiting the locals and their resources but no growth or improvements in lifestyle were created in societies where democracy and legal certainties were lacking the laur’s research also helps us understand why this is the case and could contribute to reducing income gaps between [Music] nations so Daron when you’re both talking about the importance of democratic institutions what kind of Institutions are you talking about the uh label that we Simon Jim and I use as inclusive Institution ions meaning institutions that distribute political power and economic power and opportunity broadly in society and that requires certain political institutions that provide voice to people so that they can participate their views are expressed and also constraints on the exercise of that power so you just talking about really the checks and balances we see in you know set down in constitutions like a an independent legislature a free Judiciary freedom of speech with you know a me the media being able to operate as it absolutely absolutely but that’s not enough partly because what you write in a constitution is not going to get enforced unless there is a general empowerment of the people so Constitutions are sometimes changed just like shirts and uh it doesn’t mean anything unless it becomes enforced but you have also seen um countries Prosper economically which have been governed by fairly authoritarian governments haven’t you I mean often we talk about Lee kuu in Singapore or Mah Muhammad in Malaysia for instance yeah I think that’s not the general pattern I mean so there are examples like that of course but for every example like that there’s far more examples of autocratic societies that have not flourished economically you know if if you can create inclusive Economic Institutions even under a politically kind of autocratic Society you can flourish economically at least transitorily you know that’s what happened in China you know starting in the late 1970s it was the movement towards a much more inclusive economy giving people the right to make decisions making them residual claimants on their own efforts and you know so so that that’s what generated economic growth but our our view is that you know you can’t sustain an economy like that under a autocratic political system it can be there for a transitory period but it’s not sustainable a lot of research is based on countries which have been colonized and um there’s been a lot of debate of course particularly in the United Kingdom because of the historical you know Great British Empire and um whether it was good or bad for the countries that were colonized practically all of Africa but you say that colonization often brought about a reversal in economic fortunes of the colonized people so just unpack for us why you say that because it sounds like you’re saying colonization was bad for the people I I think colonization was a disaster AB absolutely but of course it did create prosperous Societies in parts of the world in North America and australasia but for the indigenous people it was a catastrophe you know diseases wiped out 90% of the population of the Americas people were exploited they had their lands and livelihoods destroyed their communities destroyed I mean absolutely yes so so so I don’t you know so I don’t think there’s much to about that in my view I think this notion of reversal you know the Americas is very clear in the Americas you know at the time 5 you go back 500 years where were the prosperous parts of the Americas Central America the Central Valley of Mexico andian the Inca Empire you know the mexicas the valley of Waka you know there you had you had writing you had political complexity you had economic organization sophistication whatever the southern cone of Latin America North America far behind you know and then this gets completely reversed during the colonial period and the places that were relatively poor then become relatively prosperous so that’s there you see the reversal in a very clear way right I want to bring you in Demis because your mother is Singaporean or Singaporean born uh you brought up in in Britain of course but um what do you think when you hear about this kind of thing about democracy and prosperity and well it’s very I mean it’s very interesting obviously I’ve heard from my mother the sort of economic miracle that leanu brought to Singapore and he’s re when you’re rightly revered for that I don’t know obviously this is not my area but it’s it’s how do you how do you try and you know how are these institutions going to be built in the places where they aren’t um is there external is it going to be external encouragement or it has to happen internally or you know how is that going to or you just have to be lucky with finding the right leader like like a Le oneu yeah I mean I think you know the success stories are all they all come from within people build the institutions in their own context I mean there are you know I think Lewan Yu is a sort of fascinating person he’s not the only person in the world like that you know you had seretti karma in in in in Botswana you know you have other kind of outstanding leaders but I think on average you know the evidence suggests autocratic regimes don’t do as well as Democratic ones and sure you know people matter individuals matter having good leader matter where’ you find leanu you know that’s what was going to ask you so then if it has to come from within you know what so you’re pointing out with your great work like what the issues are but how other than wait for for the right you know Mandela or leanu to come along which is very rare as you say what else can be done to you know encourage those institutions to be built yeah but there’s lots of Institutions are built without famous leaders I think the track record of external imposition of Institutions is not very good there are a few cases where you can point to but uh but generally institutions are built organically but there are influences out there so one of the cases Jim already hinted that Sama Botswana you know an amazingly successful democracy in subsaharan Africa an amazingly successful country in terms of economic growth uh very rapid growth on the whole and it was all existing actually pre-colonial institutions that were the basis of more democratic but leadership there mattered too so you need you need a combination so I think facilitating institution building domestically providing tools for them and getting rid of our hindrances often you know Western and Russian powers or sometimes Chinese Powers interfering in other Count’s uh domestic affairs is not conducive to better institution building but at the end of the day institutions are going to be built bottom up okay so look a major theme of this year’s Nobel prizes has been artificial intelligence so James let me ask you then if you think technology AI could help Africa develop but Africa has not been benefiting from all this technology I’m saying it it could but to do that many things have to change many things have to change institutions have to change politics has to change you know people’s trusts all sorts of things have to change and what about the impact of technology AI for instance on Democracy really I am talking about the impact on jobs to what extent there’ll be displacement of human activity and jobs by machines yeah I mean I think that’s a huge risk I believe that humans would have a very difficult time building their social systems and communities if they become majorly sidelined and they feel they don’t have dignity or use or a way to contribute to the social good from your perspective I mean there have been a lot of advances in technology over the last 100 years have have any of them really cause massive displacement of jobs I mean already you know there’s um a lot of these Technologies are out there but have they reduced the number of jobs yeah yeah there it has happened it has happened I mean the early phase of the Industrial Revolution where it was all lot about automation there were huge displacements huge wage losses onethird two you know people’s wages within 20 years in real terms fell to for some people to onethird of it what it was that’s just a tremendous yes but down then in the end it became better so I yes so in my view there will be a lot of disruption like these other like the Industrial Revolution 90 years it took 90 years I don’t think what we want to put up with but there could be new classes of jobs I mean most but those new classes of jobs they’re not automatic so there are like two ways of thinking uh on this beyond the artificial general intelligence one is that you introduce these disruptive Technologies and the system automatically adjusts nobody needs to do anything no policy maker no scientist nor technologist the system will adjust I think that just does is is contradicted by history the way that it works is that we all have to work in order to make things better including technologist so that we actually use the scientific knowledge to create new tasks more capabilities for humans rather than just sidelining them I mean we’ve seen used to talk about the lessons of history but we saw with the printing press Revolution people who were writing books were put out of business but then lots of new jobs were created through publishing but look at the last 40 years the US is an extreme case yeah but roughly speaking I’m exaggerating a little bit but about half of the US population those who don’t have college degrees have had almost no growth in their real incomes until about 2015 from 1980 so no new jobs of import were created for them there were a lot of new jobs in the 1990s and 2000s but they were all for people with postgraduate degrees and and and specialized knowledge okay Jeff Hinton do you think that this increase in product activity essentially that will come with um Automation and so on and so forth is is a good thing for society well it ought to be right I mean it’s crazy we’re we’re talking about um having a huge increase in productivity so there’s going to be more goods and services for everybody so everybody ought to be better off but actually it’s going to be the other way around and it’s because we live in a capitalist society and so what’s going to happen is this huge increase in productivity is going to make much more money for the big companies and the rich and it’s going to increase the gap between the rich and the people who lose their jobs and as soon as you increase that Gap you get fertile ground for fascism and so it’s very scary that um we may be at a point where we’re just making things worse and worse and it’s crazy because we’re doing something that should help everybody and obviously it will help in healthcare it help in education but if the profits just go to the rich that’s going to make Society worse so okay let’s look at the last award and that’s the Nobel Prize for medicine or physiology and this is why it was awarded this year our organs and tissues are made up of many varied types of cells they all have identical genetic material but different characteristics this year’s medicine laurates Gary riffkin and Victor Ambrose have shown how a new form of Gene regulation microrna is crucial in ensuring that the different cells of organisms such as muscles or nerve cells get the functions they need it’s already known that abnormal levels of micro RNA increase the risk of cancer but the laurat research could lead to developing new Diagnostics and treatments for example it could map how microrna varies in different diseases helping unlock prognosis for the development of diseases so Gary your research was based on um looking at mutant strains of the round worm um actually it should have its own Nobel Prize shouldn’t it It’s featured so much in research that’s led to Nobel prizes but um just tell us what does your work with round worms tell us about genetic mutations in humans doing genetics is is a form of doing what evolution has been doing for 4 billion years the our planet is a genetic experiment that’s has been generating diverse life from primitive life over four billion years by inducing variation to give you the tree of life that goes you know to bats and to plants and to bacteria and we do that on one organism and the reason it works so well is that Evolution has evolved a way to generate diversity by mutating that’s that’s what all around us you know when you see a a green tree it’s because photosynthesis was developed two billion years ago the reason we can breathe oxygen is because photosynthesis evolved and it wasn’t there beforehand and so what we’re doing is that process and that’s why it works so well so the reason uh the worm has gotten four Nobel prizes is that and it’s the worm that got it so you know we we’re just The Operators uh is she behave with this yeah yeah it’s very tiny it’s very tiny it’s a millimeter long it you know it has 959 cells that’s different from us right our not every one of our cells does not have a name you know it but every cell in a worm has a name and that attracted a kind of cohort of people who like names names are important and we we’re thinking about well we can learn a lot about how biology works by sort of following cells what’s their history what do they become how much do they talk to each other but we figure it out by breaking it but it’s I mean it’s extraordinary that a human has about 20,000 genes and a worm has 20,000 gen that’s why we really are too self-important we’re just not you know humans are just not that great you know we’re we’re fine I’m happy to be a human I don’t want to be a worm but you know you know a bacteria has 4,000 genes that’s not very different from 20,000 I’m sorry right and you know people say oh geez if you look for life on other planets it’s bacteria how boring you got it all wrong folks bacteria are totally awesome yeah yeah but so what you’re saying essentially is that mutations obviously can be bad because they can lead to sorts of genetic um illnesses and so on but they’re not always bad and some are quite actually relatively insignificant like you’re color blind aren’t you for instance I mean that’s a genetic mutation it is and it’s a debilitating mutation for me be uh in the days of black and white um publishing I I was King things were fine and then everything became color you know it it I have to say so like uh our little worm I’ll go to a seminar and people are presenting graphs with red green and and I come out going gez that was just complete horse what I didn’t and people said oh it was fantastic you didn’t see I wrote to Google Maps and said you guys you do traffic is red and green means things are F I can’t see it and you’re losing 4% of the of the users and it’s the best 4% but I mean you actually want did not respond you wanted to be an electrical engineer originally did well yes I did Electronics as a kid cuz I loved electronics and I built kits uh I built a shortwave radio with a $39 kit made with vacuum tubes this is before you know transistors but the resistors have a color code right and so and it tells you how many ohms it is and that’s how much resistance it has and so I didn’t know it I didn’t know I was color blind at the time so I put it together and the test for how well you are whether it’s going to work is you turn it on and if it doesn’t smoke that that’s good and my electronic assembly didn’t pass the smoke test so um let’s go for another question now from our audience Jasmin kovitz what do you want to ask Professor rkin was micro RNA an unexpected Fant or was it a part of your hypothesis while conducting your research there no hypothesis on that no no no no no it was a complete surprise and I love surprises and really you know that’s the beauty of doing genetics is that what comes out is what teaches you right it’s and you know you do a mutagenesis you get an animal that looks like what you were looking for part of the search is saying what am I going to look for that’s the the art of it how did your research with Victor Ambrose’s um go down when you first published it in the early 1990s it was in a little little corner of biology this worm and there was a sense when you would deliver a paper to go to give a talk about it that well it’s a worm who cares you know and it’s a weird little animal until it we discovered that it was in human genome and then many other genomes and it’s been embraced and it what was especially sort of empowering to it was was it it intersected with RNA interference which is an antiviral response and people really care now of course about antiviral responses of course I mean how did you all find doing your research I mean just listening to what Gary is saying did you encounter setbacks can you define particular moments when your research really felt that you you were on a winning streak did people discourage you from what you were doing all of the above really I mean you know Academia is really hard at some level you know you work sometimes three years on a project and then somebody anonymously destroys it so that’s very very difficult to get used to so I do a lot of coaching with my graduate students to get them ready for that but on the other hand I found Academia to be quite open-minded as well you know when Jim Simon Johnson and I for example started doing our work you know I think there was not much of the sort in economics and people could have said no this is not economics and some people did and people could have said this is crazy and some people did but there were a lot of people who were open-minded especially young researchers you know they’re hungry for new angles so I found Academia to be quite open-minded as well but a tough Place D Salis David I think I think you’ve both said that research in proteins is kind of seen as at the time being on The Lunatic Fringe of uh science um I mean how how did you cope with that kind of perception that you were doing something that was a bit out there well I think when um when we started trying to design proteins everyone thought it was a crazy way to try and solve hard problems the only proteins we knew at the time were the ones that came down through you know through Evolution the ones in us and in all living things so the idea that you could make completely new ones and that they could they could do new things was was really seen as um you know Lunatic Fringe as you said but um I think the way you deal with that is you you work on the problem and you make progress and uh you know now it’s gotten to the point where um every other day there’s another company saying they’re joining the protein design Revolution and they’re going to be solving so you can go from The Lunatic Fringe to the mainstream faster than you might expect utterly Vindicated weren’t you I mean yeah it’s very right similar with you know I think if you’re fascinated enough and passionate enough about the area you’re going to you know I was going to do it no matter what you know and and actually um I can’t think of anything more interesting to work on than than in the nature of intelligence and and and computation of you know computational principles underpinning that and when we started like Deep Mind in 2010 um nobody was working on AI pretty much there was some Yes except for very few people very few fored people in in in in um in Academia and uh and then now fast forward 15 years which is not very much time and obviously the whole world’s talking about it and certainly in Industry no one was doing that in 2010 but we I we already foresaw um building on you know the great work of people like Professor Hinton that um uh this would be one of the most consequential transformative Technologies in the world if it could be done and if it’s that you see something like that then it’s worth doing in its you know in of itself I mean you Professor Hinton along with your co-recipient of the physics Nobel Prize professor John hopfield who is 91 a real Pioneer in this field of Technology also I mean do does this what you’ve just heard here resonate with you that work that at one stage was seen as being on The Lunatic Fringe and then here you are years later Vindicated uh yes so um people students would apply to my department to work with me and other professors in my department would say oh if you work with Hinton that’s the end of your career this stuff is rubbish how did that make you feel I mean did you still you luckily at the time I didn’t know about it time I think for another question from our audience and Mano dinakaran from The kolinska Institute wants to ask this what’s your question thank you Laurette um science is all about being motivated when things don’t go the way we expect them to so what kept you all motivated when things didn’t go the way you expected in times of hardship and helped you adapt who’d like to pick it up there that’s that’s the best bit that when it doesn’t when what you expected to happen doesn’t happen and then you you really learn that’s when you really learn something I mean so that’s the best bit it’s really crushing for the first couple of days and then you then you then then you like oh then oh now I learned something that’s like I didn’t understand that there is ascertainment bias here cuz you have the people who’ve gotten winning hands in the in the poker game of life you know right well gentlemen thanks to all of you and renewed congratulations on your Nobel prizes that saw from this year’s Nobel mindes from the Royal Palace in Stockholm it’s been a privilege having this discussion with you thank you to their Royal highnesses the Crown Princess Victoria and Prince Daniel for being with us of course everybody else in the audience and you also at home for watching from me Zay abuwi and the rest of the Nobel Minds team goodbye

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