Speaker 1: Well, it's exciting al having actually Rishi Sunac do this
Speaker 1: global AI summit to try and shape the agenda on
Speaker 1: how you regulator and how you use it safely.
Speaker 2: I think people that are really grappling for the extent
Speaker 2: to which this is positive and the extent to which
Speaker 2: the truly alarming headlines around the damage it could also
Speaker 2: do the extent to which they are something real going concerns.
Speaker 1: And it's interesting to see the UK. Actually, I think
Speaker 1: it's the first summit of its kind, right, global summit
Speaker 1: looking at the risks of AI, and it's interesting to
Speaker 1: see the UK trying to gather everyone together to talk
Speaker 1: about it.
Speaker 2: It is interesting, and I think it feels convincingly Rishi Sunac,
Speaker 2: doesn't it. It feels like something everything about his backstory
Speaker 2: suggests he has a kind of credible take on AI,
Speaker 2: having worked in the States where many of these tech
Speaker 2: companies are based, and also at the same time wanting
Speaker 2: to just rein in and check some of its influence
Speaker 2: for you know, everyday voters and people. So I think
Speaker 2: there is It does feel like it's convincingly Sunakian. Not
Speaker 2: a word, maybe a word. I don't think it is, well,
Speaker 2: just any think it feels like he you know, but
Speaker 2: we we you know a lot of people are asking
Speaker 2: what actually are the aims for the summit, what actually
Speaker 2: do they want to come out of it. We've heard
Speaker 2: talk of this institute being set up. That's probably the
Speaker 2: easy bit. What is the institute do is the heart
Speaker 2: of it.
Speaker 1: And that's really what we're looking at this week. Welcome
Speaker 1: to In the City, Bloomberg's podcast, connecting you to the
Speaker 1: conversations and the story is shaping the world of finance.
Speaker 1: I'm front Sine Lackwell with Rastratton in the London studio.
Speaker 1: Now with us this week. Nick Langson, his global editorial
Speaker 1: lead for Tech and Gaming and co host of the
Speaker 1: Bloomberg original program AI I R L. In Real Life,
Speaker 1: Nate is the pace the fastest we've ever seen it
Speaker 1: at the pace for change.
Speaker 3: It feels like it, absolutely, and I think that is
Speaker 3: symptomatic the fact that the amount of money that now
Speaker 3: exists in order to invest in some of these technologies
Speaker 3: has never been greater. We have seen an enormous speeding
Speaker 3: up of tech development. Absolutely because a lot of the
Speaker 3: companies that are able to invest enormously in these kinds
Speaker 3: of technologies in artificial intelligence are the ones that have
Speaker 3: made the most money from the most recent technological innovations,
Speaker 3: ie cloud computing, search, and social media.
Speaker 1: Some of us are freaked out about AI. Others think
Speaker 1: that this is the best thing that could happen to us.
Speaker 1: But because of your time, why do you've seen these
Speaker 1: changes and really have chronicled them from the very beginning.
Speaker 3: I remember when DeepMind was founded and everyone got very
Speaker 3: excited about this weirdly secretive company that no one knew
Speaker 3: anything about. That suddenly was all the rage in computer
Speaker 3: science and deep learning, which is what underpins the vast
Speaker 3: majority of what we currently see as artificial intelligence, although
Speaker 3: that is only a fraction of the overall body of
Speaker 3: work that is AI, which has been in development since
Speaker 3: the nineteen fifties, and we've seen it go from a
Speaker 3: conversation about making better use of big data. You know,
Speaker 3: that was a huge topic about ten years ago. But
Speaker 3: obviously it goes without saying almost that the release of
Speaker 3: chat GPT, which bear in mind, at the time we
Speaker 3: speak right now isn't even a year old. I think
Speaker 3: that's sometimes quite shocking to people just to realize how
Speaker 3: relatively recent that all happened. It wasn't until that release
Speaker 3: was made public that people and businesses and investors and
Speaker 3: governments and regulators started to realize, Okay, now we get it.
Speaker 3: Now we can see the potential impact returns on investment
Speaker 3: but also harms. And it really, I think motivated everybody
Speaker 3: to think, Okay, now we need to really take this serious.
Speaker 2: And Nate haven't covered this for eighteen years when the
Speaker 2: last few weeks feels like the headlines and the warnings
Speaker 2: sort of end of the world is nigh have reached
Speaker 2: a bit of a kind of fever pitch. Do you
Speaker 2: think it's hysterical or do you think these are proportionate warnings.
Speaker 3: I think they are well meaning but wildly doom focus,
Speaker 3: and I think history teaches us some lessons here about
Speaker 3: how to prepare for these kinds of changes. My favorite
Speaker 3: comparison to make is that of the dot com boom.
Speaker 3: You know, in the very late nineties, there was an
Speaker 3: enormous fear that the millennium bug, as it was coined,
Speaker 3: was going to cause a complete collapse of society, planes
Speaker 3: falling out of the sky. There was at least one
Speaker 3: airline that put one of its senior managers on a
Speaker 3: plane just to prove that they weren't worried their planes
Speaker 3: were going to fall out of the sky at midnight.
Speaker 3: Banks printed additional cash because they feared people would do
Speaker 3: a run on the banks and stockpile cash. There was
Speaker 3: a legitimate fear that this was the end of all times.
Speaker 3: And then of course the millennium came to pass and
Speaker 3: everyone realized that maybe they'd slightly overplayed the worries. But
Speaker 3: it did encourage people for those years leading up to
Speaker 3: that to at least check and prepare. And that's why
Speaker 3: I think that the questions about is this going to
Speaker 3: usher in an era of homegrown chemical warfare? Will this
Speaker 3: cause the color of society? Because an AI becomes self
Speaker 3: interested in preserving itself and growing itself. And it is
Speaker 3: useful to ask those questions, but I think it's more
Speaker 3: useful to keep it into context around what is physically
Speaker 3: possible and what are some of the actual real world
Speaker 3: requirements for that to even happen.
Speaker 2: I e.
Speaker 3: An enormous amount of power and computing resource that either
Speaker 3: doesn't exist or exists but is fundamentally inoperable because it
Speaker 3: would just cost too much money.
Speaker 2: And you can see Richie Sunak and his government trying
Speaker 2: to straddle that sort of looking both ways. Huge risks coming,
Speaker 2: but huge opportunities too. Yeah.
Speaker 3: Absolutely, I mean it's a totally realistic concern and it's
Speaker 3: smart to think about these. It's very smart to have
Speaker 3: a public debate. And one of the biggest challenges that
Speaker 3: we have with social media now is the result of
Speaker 3: largely unchecked, unregulated growth of technology companies that eventually resulted
Speaker 3: in the consolidation of power and influence in the hands
Speaker 3: of a very small number of extraor ordinarily powerful entities,
Speaker 3: all of which are commercially motivated and publicly owned. And therefore,
Speaker 3: you know, we can't get the genie back in the
Speaker 3: bottle for that. We want to avoid that this time.
Speaker 2: I mean, that's my question when I'm looking ahead to
Speaker 2: the summit that they're hosting, which is in many ways,
Speaker 2: you know, is smart, and I think it probably is
Speaker 2: a decent moment for the UK to show some leadership
Speaker 2: in an area where there is great investment in the UK.
Speaker 2: But the question I keep returning to is, as you say,
Speaker 2: when you look at the evidence of getting big social
Speaker 2: media companies to do the right thing and to police
Speaker 2: themselves and so on, have we got the kind of
Speaker 2: track record from them that suggests that they will also
Speaker 2: police themselves in managing these huge language sets.
Speaker 3: Absolutely not no, there is absolutely no, they're absolutely not.
Speaker 3: But there are good intentions. But some of the good
Speaker 3: intentions also come with the caveat that they are self
Speaker 3: interested in protecting their business. They want to release the
Speaker 3: technology because they want to commercialize it and monetize it
Speaker 3: and be seen, as you know, as a leader in
Speaker 3: that field. But at the same time, you don't want
Speaker 3: to be caught out. And it's why you see a
Speaker 3: lot of companies calling for regulation, because it gives them
Speaker 3: boundaries and guardrails and it allows them to say, well, look,
Speaker 3: we've played by the rules you set, so it's not
Speaker 3: our fault that this happened. And that is a challenge
Speaker 3: in its own right.
Speaker 1: But it'd be interesting to see what you think actually
Speaker 1: the overarching goal for this AI summit is, and when
Speaker 1: we understand the goal, whether other countries like chrying to
Speaker 1: share those goals.
Speaker 2: Well, so yes to different different questions, but you're absolutely
Speaker 2: right the key questions what's the goal for the UK? Well,
Speaker 2: there is investment in the UK by these firms. If
Speaker 2: we're asking the question that we are often asking on
Speaker 2: this pod and in the readout and all over Bloomberg.
Speaker 2: Whereas the growth agenda come from, Partly it will be
Speaker 2: around investment in tech firms into the UK. So the
Speaker 2: first thing, there's that. Secondly it's something which she soon
Speaker 2: that cares about. And everything about his backstory points to
Speaker 2: a summit on AI. You know, if his ties right,
Speaker 2: you know, he's a you know, Standford Business School. He
Speaker 2: has spend a lot of his career in America, so
Speaker 2: he is instinctively comfortable with those companies. But equally he
Speaker 2: is the MP for constituency in Yorkshire, which you know,
Speaker 2: at the end of the day, normal people will be
Speaker 2: affected by this revolution that is coming. I think it
Speaker 2: is interesting the question around what effect it will have
Speaker 2: on jobs Eventually. We've had warnings this week on job
Speaker 2: losses by twenty thirty and are people ready? And you
Speaker 2: have a lot of very sensible people saying in that
Speaker 2: context where many many low paid jobs are being automated,
Speaker 2: we have to think about a debate around universal basic income,
Speaker 2: which a few years ago was unthinkable. I think we
Speaker 2: all know and everyone listening though, is that there are
Speaker 2: and Nate's mentioned it already there's these constant fars that
Speaker 2: new tech's going to get rid of jobs and they
Speaker 2: don't necessarily materialize. I feel a bit more gloomy about
Speaker 2: this one because you have seen increasingly over the last
Speaker 2: few years that lots of low paid jobs are being
Speaker 2: automated and they aren't being replaced by particularly high esteemed
Speaker 2: valuable jobs that give people, you know, a sense of
Speaker 2: purpose in the morning when they go to work. I
Speaker 2: think there is a question mark there, But it is
Speaker 2: the case too that history does show us that actually
Speaker 2: it's the kind of the luod Oitte fallacy that essentially,
Speaker 2: in the end, different jobs are made and there's more
Speaker 2: of them. Well, I hope.
Speaker 1: So is there illegitimacy for the UK to be hosting this?
Speaker 1: So by regulating it, do you also attract growth and
Speaker 1: investment because you're seen as the AI destination?
Speaker 3: I think we need to work very hard to be
Speaker 3: seen as an AI destination. I think that in the sense,
Speaker 3: the UK has an opportunity here to play something of
Speaker 3: a Switzerland role in AI because let's be honest, the
Speaker 3: money is in China and the US we do not
Speaker 3: have a huge AI tech scene in that you know,
Speaker 3: we are investing a tiny amount of money in AI.
Speaker 3: We are making a very small amount of money available
Speaker 3: to AI development. Even the billion pounds that figure that
Speaker 3: gets thrown around that you know, SUNA can smaller than
Speaker 3: I mean, I think it was Amazon invested something like
Speaker 3: four billion dollars in one AI company. That goes four
Speaker 3: times the figure from one company in one startup, like
Speaker 3: it pales into its significance. But I do think on
Speaker 3: my Switzerland comparison is that there is an argument I think,
Speaker 3: and it's not one the government I'm sure we'd agree with,
Speaker 3: but I think it's realistic that if you have a
Speaker 3: country like the UK that will be impacted or benefited
Speaker 3: by negative or positive outcomes of AI but doesn't actually
Speaker 3: have much of a commercial stake in its development, it
Speaker 3: actually puts it in a rather arguably neutral role in
Speaker 3: setting at least some of the agendas that other countries
Speaker 3: play by, because we can be a little bit more
Speaker 3: impartial as long.
Speaker 1: As whatever the UK's goals are shared with the people
Speaker 1: that matter, i e. China.
Speaker 3: Yes, that's very true, and there is some argument whether
Speaker 3: we do or not, And certainly the US and China
Speaker 3: have a very different approach to how they foster and
Speaker 3: encourage the growth and development of a lot of technologies.
Speaker 3: China is very much top down, the party will dictate
Speaker 3: a lot of the time where the money should go
Speaker 3: and where the support for development should come from, whereas
Speaker 3: the US is much more like, we'll get on with it,
Speaker 3: private enterprise and we'll regulate if we have to.
Speaker 2: And the pitch from the government will be, Okay, let's
Speaker 2: use these brexit freedoms. You've seen already tech bosses saying
Speaker 2: use your Brexit freedoms, right, So it's not just the
Speaker 2: necessarily a sort of comm's line from this government, it
Speaker 2: is it's also being echoed by people in the industry.
Speaker 2: So that's so that's that's that's the pitch. But completely
Speaker 2: you know, Nate is obviously very lucid on you know,
Speaker 2: in reality, does the UK have the heft to convene
Speaker 2: this debate and necessarily pull out of it's that kind
Speaker 2: of not quite as regulatory as the EU, not quite
Speaker 2: as wild west as America, and definitely not China or
Speaker 2: whether actually in all of that, you know, then you
Speaker 2: know they get left behind.
Speaker 1: But are they still aligned with the EU? So again
Speaker 1: it's I.
Speaker 2: Think there is that here that here that they can
Speaker 2: actually push out further and that and they're being encouraged
Speaker 2: to by various players in this scene.
Speaker 1: So they're forming an institute to try and understand. First,
Speaker 1: you have to understand it, I guess, right, So that's
Speaker 1: where we die. Where's that incident going to be? But
Speaker 1: you have to understand what you're regulating before you regulate.
Speaker 1: So the problem with regulators is that they're always a
Speaker 1: step behind. Because AI evolves, the chips evolve, it gets smarter,
Speaker 1: and the regulators need to catch up.
Speaker 3: That's always been the problem with technology as well. And
Speaker 3: that's what's so interesting is that none of this is
Speaker 3: unique to AI. This is something that's happened every year,
Speaker 3: every decade, seemingly that I can remember reading about or
Speaker 3: talking about. The hope is that we collectively learn from
Speaker 3: past experience that when we spot something that maybe we
Speaker 3: should probably put a lot of extra time into looking
Speaker 3: at early, we do that. I like to think that
Speaker 3: that's kind of what the world is doing with this,
Speaker 3: and that maybe that's a good thing.
Speaker 1: So Nate, isn't the problem with deep fakes that actually
Speaker 1: you can't really tell them apart. So there's a picture
Speaker 1: of a leopard going around. There's three of them, and
Speaker 1: it challenges you to find the deep fake one.
Speaker 3: The difficult it's very, very difficult. There are many experts
Speaker 3: trained in this that cannot tell a deep fake from
Speaker 3: the real thing, and so there's this debate around we
Speaker 3: should have everybody in the industry that is producing something
Speaker 3: that would qualify as a deep fake or something that
Speaker 3: is generated to water market. And that's not watermarking in
Speaker 3: the sense of if you look at a photo online
Speaker 3: and it's got like the brand slightly proof, yeah, proof
Speaker 3: across the top, or it's some audio water marking that
Speaker 3: makes the video useless to share or sell. It's not
Speaker 3: that sort of thing. It's baked into the image itself.
Speaker 3: In a very similar way to right now, if you
Speaker 3: take your iPhone or your Android phone, you take a photograph,
Speaker 3: the amount of data that is stored in that image
Speaker 3: that you never see unless you look for it, it
Speaker 3: is staggering. Everything is in there where it was taken,
Speaker 3: the GPS coordinates, the timestamp, the model of camera, the
Speaker 3: model of lens in the camera, the aperture of the
Speaker 3: lens attached to the camera. You know whether the flash fired,
Speaker 3: whether it didn't the model make everything. This would just
Speaker 3: be another piece exactly. It's all stored in. There is removable,
Speaker 3: you can delete it, but the vast majority are never
Speaker 3: going to be removed because no one knows they're there,
Speaker 3: and why would you.
Speaker 2: For the most that feels in a very difficult debate.
Speaker 2: That feels promising, But the problem is does everybody agree
Speaker 2: to the watermark.
Speaker 3: Everyone would have to agree to it, and everyone would
Speaker 3: have to sign up to support it in a way,
Speaker 3: and it's a slightly strange comparison perhaps, but in the
Speaker 3: way that if you buy an audio like an AV
Speaker 3: receiver for a home cinema or a pair of headphones
Speaker 3: or something that you know they all support Dolby Digital,
Speaker 3: you know that is a format, that is a standard,
Speaker 3: that is a thing that is internationally recognized and adopted,
Speaker 3: and so you would need a standard's body to say
Speaker 3: this is the standard for watermarking whether an image or
Speaker 3: even part of an image is a deep fake, and
Speaker 3: that every other piece of software or hardware around the
Speaker 3: world can read and interpret that, and that at least
Speaker 3: gets you some of the way towards identifying whether is
Speaker 3: real or fake. But it does change because you can
Speaker 3: manipulate images.
Speaker 2: And how quickly can that happen, because clearly we've got
Speaker 2: two major elections next year years so not for next year.
Speaker 3: Very quickly it can be developed, but adoption and an
Speaker 3: acceptance internationally and roll out is is a many years
Speaker 3: long process, I would say.
Speaker 2: So we'll see deep fakes in the next elections, right.
Speaker 3: I spoke to an expert the other day and said,
Speaker 3: will will deep fakes decide the twenty twenty four election,
Speaker 3: and he said, no, it'll be one or lost on
Speaker 3: abortion rights, but it will be deep fakes that are
Speaker 3: the core driver underneath that or words to that effect.
Speaker 2: It is by the time you've established that something's a
Speaker 2: deep fake, some of the damage will have been done
Speaker 2: twelve as later, and a lot of people won't even
Speaker 2: listen to the clarification, as we've seen recently.
Speaker 3: Yeah, and the argument comes down to, well, is being
Speaker 3: used to spread disinformation and sometimes things are created with
Speaker 3: the goal of subverting reality as a disinformation item. But
Speaker 3: if that looks real and somebody unwittingly shares it, they
Speaker 3: are sharing it effectively is misinformation because they don't realize
Speaker 3: that it's not real. And with the speed of social media,
Speaker 3: it can travel way quicker than you could ever possibly counteract.
Speaker 2: It, and so I mean, we're probably guilty in this
Speaker 2: conversation of focusing too much on the downside, and that's
Speaker 2: for justifiable reasons, but the upsides are massive. My favorite is,
Speaker 2: you know, for a teacher who has to mark thirty
Speaker 2: books or twenty five books every night, that can be aied.
Speaker 2: Ditto for difficult healthcare. AI will spot stuff that it
Speaker 2: was impossible for GPS to necessarily crawl over all that data.
Speaker 2: So there's legitimate hopes that sensible, proportionate use of AI
Speaker 2: can help with productivity and release all of us to
Speaker 2: do what The question is, how do you adjudicate well?
Speaker 3: I think one thing that's really important to keep in
Speaker 3: mind in all of these conversations is that there is
Speaker 3: this sort of common belief that you can take a
Speaker 3: problem and you can throw AI at it and that
Speaker 3: problem gets solved. And that's just not true. And it's
Speaker 3: really important that people understand that you can't just throw
Speaker 3: something into AI and suddenly get something better. It's a
Speaker 3: significantly more complex series of steps to do that. One
Speaker 3: of the things I find most fascinating about what could
Speaker 3: happen now is if you look at the large language models,
Speaker 3: which is what if you take chat GPT, that is,
Speaker 3: you know, the poster child for a lot of this,
Speaker 3: even though the technology underneath it isn't that new. It
Speaker 3: uses large language models, it scrapes the entire Internet, it
Speaker 3: reads every word on the Internet. Increasingly, now those sorts
Speaker 3: of products are able to look at every video and
Speaker 3: every picture and that's what's called a multimodal AI and
Speaker 3: it can process that, train itself on that and then
Speaker 3: give you usable outcomes. But there comes a point I think,
Speaker 3: and I actually think we're reaching that point now where
Speaker 3: everything that exists has been read and scanned. So in
Speaker 3: order to improve to the same degree, you need new
Speaker 3: types of data, and you need quality data.
Speaker 1: Reliable data, I mean reliable problem exactly, deep fakes right,
Speaker 1: it has to be vetted data.
Speaker 3: It does. And so the next step is, well, where
Speaker 3: does the next huge volume of data come from. It
Speaker 3: will come from sensors, it will come from us, it
Speaker 3: will come from medical trials and studies. But my point
Speaker 3: is is that if you develop some kind of a
Speaker 3: system that can try with molecules, looking at the interactions
Speaker 3: of molecules in a way that you cannot realistically do.
Speaker 3: In a lab, you can run all these simulations to
Speaker 3: figure out how a molecule might interact, take the data
Speaker 3: that that simulation has created, and then apply AI to well,
Speaker 3: what could we do with this that changes the game entirely.
Speaker 3: That is not where we're at really right now, but
Speaker 3: that is probably one of the next steps that we're
Speaker 3: going to get to, and that's where things get very exciting.
Speaker 3: An optimistic, I'm optimistic, but I mean I'm an optimist
Speaker 3: generally speaking, and I think that we have a when
Speaker 3: we talk about doomerism and AI doomerism, I think we
Speaker 3: take a really anthropocentric view of these systems in that
Speaker 3: we build things to kind of mimic our own inherent
Speaker 3: abilities with the human brain. Neural networks are very loosely
Speaker 3: modeled on how human neurons work and interact with each other,
Speaker 3: and so when they do something, as in, when an
Speaker 3: AI system does something that looks slightly human like, it
Speaker 3: looks a bit like creativity, It's kind of like seeing
Speaker 3: a face in a piece of toast, you sort of think, well,
Speaker 3: is that the you know, is that the reincarnation of
Speaker 3: the Messiah. It's not it's just very burn bread. But
Speaker 3: as human beings, we are evolutionary trained to see that,
Speaker 3: and I think we spot those in AI as well,
Speaker 3: and then we say, well, if it's going to do
Speaker 3: a little bit of human like creativity on this, humans
Speaker 3: do sadly have a tendency to start wars and kill
Speaker 3: each other, and maybe we should stop it doing that.
Speaker 3: But it's not necessarily coercentric.
Speaker 1: That's a big word name. I think I have to
Speaker 1: google it it.
Speaker 2: I mean, yeah, we obsession about human beings, and.
Speaker 3: It's the obsession that humans are the end game, you know.
Speaker 3: It's this thing that we are the most evolved and
Speaker 3: the holy Grail, the final step in the evolutionary journey,
Speaker 3: and that anything we create is ultimately aiming to get
Speaker 3: to that point too. And I just think that's not
Speaker 3: necessarily true.
Speaker 1: Does in the UK at the summit need a big
Speaker 1: win and saying we're regulating this way so that people
Speaker 1: are safe.
Speaker 3: That would be great, but I mean, the technology doesn't
Speaker 3: respect borders, it doesn't respect geopolitical tensions. It just it
Speaker 3: is what it is, and the technology is global, so
Speaker 3: I think it'd be very hard for anyone to come
Speaker 3: out of that and say yes, we've set the agenda
Speaker 3: for global regulation because it doesn't work, and we saw
Speaker 3: that it doesn't work with social media. Look at Facebook.
Speaker 3: It cannot come up with a content moderation policy that
Speaker 3: it can create in California, plot and apply worldwide when
Speaker 3: cultural sensitivities and laws are so vastly different outside of
Speaker 3: its own country, so that the idea is best principles
Speaker 3: and being able to come up with something that says,
Speaker 3: you know, if you run through this checklist of ten
Speaker 3: things that will at least get you closer to being
Speaker 3: able to answer a question that your own constituents and
Speaker 3: your own jurisdiction may be asking you, which is how
Speaker 3: should we move forward? That would be quite useful. I think.
Speaker 1: Thanks for listening to this week's in the City. We'll
Speaker 1: be back next week, but in the meantime, if you
Speaker 1: like our show, please head on over to wherever you
Speaker 1: listen to podcasts, rate, review, and subscribe. It doesn't really
Speaker 1: help people find the show. This episode was hosted by
Speaker 1: me Francine Laqua with Allegro Stratton. It was produced by Summersati,
Speaker 1: additional editing by Blake Maples and really special thanks to
Speaker 1: Nate Langxing