Speaker 1: Welcome to tech Stuff, a production of I Heart Radios,
Speaker 1: How Stuff Works. Hey there, and welcome to tech Stuff.
Speaker 1: I'm your host, Jonathan Strickland. I'm an executive producer with
Speaker 1: How Stuff Works and I Heart Radio and I Love
Speaker 1: all Things Tech. And Oz and Kara from Sleepwalkers have
Speaker 1: come back to join me yet again. Spoiler alert. We
Speaker 1: actually haven't left anywhere. We just sat here the whole
Speaker 1: time and we're recording two episodes back to back. But
Speaker 1: if you haven't heard our previous discussion, which is kind
Speaker 1: of a high level discussion about AI and the potential
Speaker 1: dangers and sort of the the various messaging we've received
Speaker 1: about AI and the warning signs and the promises, you
Speaker 1: should listen to that episode first. If you haven't subscribed
Speaker 1: to Sleepwalkers, you should absolutely do that too, because the
Speaker 1: show is amazing. And today we're gonna talk a little
Speaker 1: bit more about how different parts of the world are
Speaker 1: treating AI, whether it's from a government perfective or a
Speaker 1: business perspective, The technological you know, development of AI, where
Speaker 1: is that actually happening the fastest, And the answer to
Speaker 1: that might surprise you if you haven't been paying close
Speaker 1: attention to news around the world and we're going to
Speaker 1: dive into all of that. So, without any further Ado,
Speaker 1: welcome back to the show, Os and Kara, Thank you
Speaker 1: so much. Jonathan, Hi Jonathan again. Hi again. Yea. And
Speaker 1: while we were between shows, we were just you know,
Speaker 1: talking about Lady Gaga and Shakespeare as you are want
Speaker 1: to do. Uh, this is kind of what we technologists
Speaker 1: technology podcasters tend to to really, you know, kind of
Speaker 1: revel in when we're not on on Mike or at
Speaker 1: least not recording. But I wanted to talk first about
Speaker 1: where do we see really aggressive you know, moving forward
Speaker 1: on on technology and AI, Like, where are we seeing
Speaker 1: the most development in AI? Because a lot of people
Speaker 1: think of Silicon Valley as sort of the place like
Speaker 1: it's it's the breeding ground for all technologies. But as
Speaker 1: it turns out, that's that's really a very narrow view,
Speaker 1: and it it's ignoring a giant superpower that is pouring
Speaker 1: a lot of resources into AI development. Right China. Yeah, sorry,
Speaker 1: that China is is um is leading the charge on AI.
Speaker 1: And one of the guests we had on the show
Speaker 1: on Sleepwalkers is a guy called Kaifu Lee who was
Speaker 1: part of the team at Apple that developed the technology
Speaker 1: behind SyRI in the nineties, went on to run Google
Speaker 1: China and is now one of the biggest technology investors
Speaker 1: in China through a fund called Signivation Ventures, which is
Speaker 1: about all sorts of different technology ventures in China, including
Speaker 1: several unicorns a billion dollar companies, one of which is
Speaker 1: called meg v which does facial recognition technology. Kai Fu
Speaker 1: Lee recently wrote a book called AI Superpowers, China, Silicon
Speaker 1: Valley and the New World Order. New World Order is
Speaker 1: quite a resonant phrase, shall we say, But the thesis
Speaker 1: of the book is simply that China are doing AI
Speaker 1: a lot better, a lot more aggressively, and with a
Speaker 1: lot more promise than we are in the US. And
Speaker 1: that's for two reasons. Number one, China, unlike the US,
Speaker 1: is a centralized country, a centralized government who have said absolutely,
Speaker 1: with no hesitation, AI is our biggest priority. In seventeen,
Speaker 1: the Communist Party released what they called the New Generation
Speaker 1: Artificial Intelligence Development Plan, and the first paragraph read AI
Speaker 1: has become a new focus of international competition. AI is
Speaker 1: a strategic technology that will lead the future. The was
Speaker 1: major developed countries are taking the development of AI as
Speaker 1: a major strategy to enhance national competitiveness and protect national security.
Speaker 1: So China have been on this for two years, I
Speaker 1: mean for longer than two years, but they're taking immensity
Speaker 1: seriously and we're not. We did have our own presidential
Speaker 1: executive order in April of this year, but it didn't
Speaker 1: come with any funding a kaifu. Second point, which I'm
Speaker 1: sure we'll get onto, is that the China also have
Speaker 1: a much richer data set, which is the power behind
Speaker 1: the throne of AI. Yeah, something that I think a
Speaker 1: lot of Americans in particular aren't aware of is that
Speaker 1: when you look over at China and China's efforts to
Speaker 1: to own AI essentially, I mean there there's they're saying,
Speaker 1: we are going to be established as the the primary
Speaker 1: source of AI development by twenty thirty and they're they're
Speaker 1: well on their way to doing that already. Um. You
Speaker 1: look at the the B A T that's the three
Speaker 1: big companies that collectively are valued at more than a
Speaker 1: trillion dollars, bay Do, Ali, Baba and ten Cent, and
Speaker 1: those are already enormous corporations that have deep ties to
Speaker 1: the state government of China than that are working very
Speaker 1: hard in AI. But beyond that, even though you know,
Speaker 1: you might think, well, those are maybe three big companies,
Speaker 1: but how is that that that big of a of
Speaker 1: a of a you know, a force on its own.
Speaker 1: They also invest heavily in lots of startup companies, including unicorns. Uh.
Speaker 1: They in fact, they out of the six hundred billion
Speaker 1: dollars of unicorns out of China from a couple of
Speaker 1: years ago, they made up fifty percent of the investment
Speaker 1: into those companies. Then beyond that, they're investing in companies
Speaker 1: outside of China and in other parts of the world,
Speaker 1: including the United States. Uh. Ten Cent, for example, has
Speaker 1: been investing heavily in video games over in the West Coast,
Speaker 1: I'm along with lots of other different companies out there.
Speaker 1: So not only are you talking about a country that
Speaker 1: has an enormous population and therefore an enormous source of
Speaker 1: information on its own, it has spread out around the globe,
Speaker 1: so it's gathering information from everywhere. So it's it's really
Speaker 1: this incredibly pervasive system to gather the fuel that is
Speaker 1: going to power artificial intelligence. Uh. And meanwhile, you also
Speaker 1: have very smart people running very sophisticated laboratories working on
Speaker 1: the next generation of of algorithms and applications of AI.
Speaker 1: So you've got like the perfect storm over there. Yeah. Absolutely.
Speaker 1: And I also think, I mean, just in terms of
Speaker 1: what you're talking about, you know, Tencent being involved in
Speaker 1: Fortnite if I'm correct, Yes, yeah, I was just doing
Speaker 1: was doing the floss right over here. Actually, that's right.
Speaker 1: And also the ownership of a little known dating app
Speaker 1: called grinder Um, which the US is actually trying to
Speaker 1: get back just because of the national security threat that
Speaker 1: is involved in the Chinese owning uh so much user
Speaker 1: data from United States citizens, including U S military personnel. Um.
Speaker 1: I think I think what's alarming about this is that
Speaker 1: we is that we're sort of entering into this new
Speaker 1: territory of you know, war and competition and war being
Speaker 1: less about you know, guns and bombs and more. And
Speaker 1: this is not these are not my words I've read this,
Speaker 1: but more about you know, bits and bites, so to speak.
Speaker 1: I think you read that from Secret Ar State Mike Pompeo.
Speaker 1: That's right, I'm quoting Mike Pompeio. Happily, I think, um,
Speaker 1: which actually he said in regards to Huawei, which is
Speaker 1: obviously in the news quite a bit recently. Um, you know.
Speaker 1: I think that the there's there's the technology race, which is,
Speaker 1: you know, sort of who's going to have who's going
Speaker 1: to advance quickly and in the best way. But it's
Speaker 1: also about sort of who owns data and who has
Speaker 1: access to what data. I think the China, the Chinese
Speaker 1: government does not really have a problem uh spying on
Speaker 1: its citizens. I don't even think we'd call it spying necessarily.
Speaker 1: I think it's sweeping, um is what is what they
Speaker 1: tend to do, and um with that data can make
Speaker 1: some pretty uh you know, chilling accusations about people who
Speaker 1: they think are dissenting against the government. Um. You know,
Speaker 1: in the United States, we are very free with the
Speaker 1: data we give away because I don't think enough people
Speaker 1: think about how much data they're giving away in any
Speaker 1: given day. But the US government hopefully will remain so
Speaker 1: is not as what's the word pervasive, pervasive and aggressive
Speaker 1: about collecting said data and using it to um, you know,
Speaker 1: in prison there citizens. So I don't know, I think
Speaker 1: China can kind of get away with more and maybe
Speaker 1: that's why the Chinese government is allowing Chinese businesses to
Speaker 1: get away with more than the US government. Ill saying
Speaker 1: it's worth pointing out in the US, you know, we
Speaker 1: have this phenomenous surveillance capitalism, So there's a bunch of
Speaker 1: big firms who take all the data we give them,
Speaker 1: use it to model us, make predictions about us, and
Speaker 1: sell us more stuff. In China, it's surveillance statecraft, and
Speaker 1: the data is not siloed between Amazon, Google, face Book
Speaker 1: and others. UM. It's tends to be in the hands
Speaker 1: of the big technology companies in China, you know who,
Speaker 1: given that they're not fully state owned, but much more
Speaker 1: hand in pocket with the government than our technology companies
Speaker 1: are share their collected data much more widely, which allows
Speaker 1: them to make better predictions about what might happen and
Speaker 1: be determinative about the outcome of their citizens. I do
Speaker 1: think it's worth pointing out a lot of this conversation
Speaker 1: about the difference between AI in China and the United
Speaker 1: States that we have on this side of the Pacific
Speaker 1: um is filtered through our liberal individual worldview, which states
Speaker 1: that you know, free will, the ability to control one's
Speaker 1: own outcomes, um, the you know, the the recognition of
Speaker 1: oneself as an individual are the utmost goods, and that
Speaker 1: worldview simply isn't shared throughout most of China. Now you
Speaker 1: can say that's that will change, you know, society opens up.
Speaker 1: You can say there's an inevitable progress, if you want
Speaker 1: to call it, program us towards our worldview. But the
Speaker 1: fact is that isn't the world view in China. And
Speaker 1: many Chinese citizens are used to living in one on
Speaker 1: one party states since um, since mal z Dong or
Speaker 1: where it was in the nineteen forties, and so there's
Speaker 1: a there's a there's a there's a sense of being
Speaker 1: accustomed to the belief that harmony and the furthering of
Speaker 1: the state's goals rise um rising is a rising tide
Speaker 1: which raises all boats. And so you know, I think
Speaker 1: we have this desire to see and of course it
Speaker 1: has happened in China. There's been Channeman's Square, you know.
Speaker 1: There there there have been organic protest movements. But we
Speaker 1: do have the desire to impose our absolute belief in
Speaker 1: the importance of the individual and free will on the
Speaker 1: rest of the world. And you know, I'm not sure
Speaker 1: that if you ask the average Chinese citizen, you know,
Speaker 1: do you resent being surveiled when the most highest number
Speaker 1: of people have been lifted out of poverty in the
Speaker 1: fastest time of any country tree in history. I think
Speaker 1: the answer might be, you know, perhaps we prefer more freedoms,
Speaker 1: but this isn't the worst thing in the world. Also,
Speaker 1: China is an ethnically largely ethnically homogeneous society. So for that,
Speaker 1: for the average Han Chinese, that the trade off for this,
Speaker 1: this lifting out of poverty and the national pride which
Speaker 1: is which is absolutely on the rise in China, giving
Speaker 1: a much stronger sense of national identity, I would argue
Speaker 1: than we have here, the tradeoff may be worth it.
Speaker 1: What's very chilling, Beyond chilling is the treatment of the
Speaker 1: non Han Chinese in China, the tibet the Tibetans, and
Speaker 1: specifically the Weakers, who are really the people who experienced
Speaker 1: the hard end of this surveillance state in China. Hey, guys,
Speaker 1: it's Jonathan from the future. I'm just popping into interrupt
Speaker 1: here because as it turned out, we got so into
Speaker 1: this conversation I totally forgot to put in a break.
Speaker 1: So let's take a quick break even while Jonathan in
Speaker 1: the past and ours and Kara continue their conversation. We'll
Speaker 1: get back to that in just a second, Hey, guys,
Speaker 1: Jonathan from the future. Again, we're going to get right
Speaker 1: back into the episode. Oz was just talking about China
Speaker 1: and it's use of technology and the creation of a
Speaker 1: surveillance state, and we're gonna pick up with my response. Yeah,
Speaker 1: and as we mentioned in the last episode, you know,
Speaker 1: we were talking about about bias and how that can
Speaker 1: be unintentionally inserted into a system and how that can
Speaker 1: cause harm. But you could also intentionally create a biased
Speaker 1: system specifically in order to keep tabs on particular populations
Speaker 1: that that are, you know, minorities, and yeah, the and
Speaker 1: obviously that could lead to truly horrific inhumane practices, leading
Speaker 1: all the way up to even genocide. Yes, I mean,
Speaker 1: right now what we're seeing is sort of um imprisonment
Speaker 1: in re education camps. But I think it's important to
Speaker 1: note and this is again, you know, piggybacking off of
Speaker 1: what Oz was saying. You know, the Chinese Communist Party
Speaker 1: has often used surveillance as a means for control. The
Speaker 1: differences is that artificial intelligence enables a kind of surveillance
Speaker 1: that we haven't seen before, which is, you know, in China,
Speaker 1: there is basically a very large operation that they call Egypt,
Speaker 1: which is the Integrated Joint up Integrated Joint Operations. And
Speaker 1: what that does is it's a database that is sweeping
Speaker 1: information from you know, basically every source imaginable WiFi, you know,
Speaker 1: visitor management system so you know, for example, in America,
Speaker 1: what we call you know, when you walk into a
Speaker 1: building and register your name to visit an office. You know, um,
Speaker 1: wecha um we chat conversations, you know, uh, when you
Speaker 1: leave the country, when you come back in the country,
Speaker 1: all of these things are being swept into um a
Speaker 1: larger I don't I don't know what the word is
Speaker 1: for it. It's not server, I don't know how to
Speaker 1: say it. It's a system. It's a system. It's a
Speaker 1: system that it's then making decisions and predictions about who
Speaker 1: is basically doing right and doing wrong. And we just
Speaker 1: simply don't have We don't have anything like that in
Speaker 1: the United States right now. I mean, certainly we can
Speaker 1: there there are companies that can use our information in
Speaker 1: the United States to make predictions about us, to sell
Speaker 1: us things, to basically set our insurance premiums. But as
Speaker 1: far as just an integrated system that is making decisions
Speaker 1: about its people and then also using it to imprison
Speaker 1: its people. There's it's just unprecedented. And you know, the
Speaker 1: Human Rights Watch is basically calling it a humanitarian crisis,
Speaker 1: which I which I think it is when you think
Speaker 1: about you know, um, your own country basically spying on
Speaker 1: your conversations. Um, really, I mean obviously without your consent.
Speaker 1: People are stopped all the time in China and their
Speaker 1: phones are taken and read through like that's a very
Speaker 1: that's a sort of normal day, um, and then using
Speaker 1: that information to put you in a re education camp.
Speaker 1: I mean, I think if most Americans knew that, which
Speaker 1: I don't think they do, um, they would be alarmed.
Speaker 1: But let's be clear. You know, we're we're very far
Speaker 1: from having a re education camps in the US, but
Speaker 1: we do, and it's not on a state level or
Speaker 1: a national level. We do make decisions about people's outcomes
Speaker 1: with stuff like credit schools. I mean the credit schools.
Speaker 1: You know in China it's it's it's ethnically it's explicitly ethnic. Right.
Speaker 1: Well again in China they wouldn't say that, but effectively
Speaker 1: it's explicitly ethnic against the wagers. In the US, we
Speaker 1: have credit schools and guess what most people who grow
Speaker 1: up with a certain amount of privilege know what their
Speaker 1: credit school is, understand the principle of the credit school.
Speaker 1: Get a credit card as early as they can, start
Speaker 1: building their credit, making monthly payoffs, and then when it
Speaker 1: comes time to get a mortgage and buy a house
Speaker 1: and move to a nice neighborhood, guess what, All the
Speaker 1: pieces are in place. But but for for many people
Speaker 1: who don't grow up with the privilege, that the credit
Speaker 1: school comes as a complete surprise at a certain point
Speaker 1: in life that you know, there's even notion of having
Speaker 1: bad credit. All of a sudden, you know you've got
Speaker 1: bad credit without ever having realized that you had this
Speaker 1: credit school you're supposed to be working on. And guess what.
Speaker 1: You can't move out of your neighborhood, You can't get
Speaker 1: what you want, You can't buy your children and things
Speaker 1: they need. So we do have this here. It's not
Speaker 1: state policy, but we've we've effectually outsourced this predictive technology
Speaker 1: about what people are going to do in the future
Speaker 1: to private corporations who who use it to profit from
Speaker 1: us rather than to control us. But we shouldn't beat
Speaker 1: we shouldn't beat China too hard with this stick when
Speaker 1: we have certain analogous practices here in the US. Sure,
Speaker 1: I mean you could even I'm sure there are plenty
Speaker 1: of people who do argue that when we the practices
Speaker 1: of certain actual state level organizations in the United States,
Speaker 1: that we should be concerned about what sort of systems
Speaker 1: they might be using. I'm thinking specifically of the n
Speaker 1: s A because it wasn't that long ago when we
Speaker 1: were having enormous headlines about the n s A and
Speaker 1: its practices of trying to have you know, essentially listening
Speaker 1: points just outside of major UH communications channels, whether it
Speaker 1: was Internet service providers or the telecommunications industry in general,
Speaker 1: and you start thinking, well, if you start applying these
Speaker 1: kind of AI surveillance UH programs, which is you know,
Speaker 1: in essay, is all about trying to detect communications UH
Speaker 1: in that everyone gets lumped into and not just bad actors,
Speaker 1: then you start getting those concerns. And you know, we
Speaker 1: we saw plenty of that even without the AI element
Speaker 1: when the n s A stories were breaking a couple
Speaker 1: of years ago, even just to the point where we
Speaker 1: were seeing people in the n s A behaving poorly,
Speaker 1: like using the information gathered to track down like old relationship,
Speaker 1: you know, like old boyfriends and girlfriends, not an ethical
Speaker 1: use of your power if you're if you're looking in
Speaker 1: on communications. So we know that it doesn't have to
Speaker 1: be a an official state line policy for this to
Speaker 1: either be uh misused in an unauthorized way or put
Speaker 1: to use in a way that maybe it's not immoral,
Speaker 1: but you could at least argue it's a moral with
Speaker 1: a lot of the the business practices, because that's morality
Speaker 1: is not consideration when you're looking at how do we
Speaker 1: make more revenue, how do we make a greater profit? Um,
Speaker 1: And and you know you're just you're essentially you're checking
Speaker 1: off boxes saying, right, here's how we can make this
Speaker 1: more efficient, have a lower cost to us, a greater
Speaker 1: payoff off in the long run. And so we start
Speaker 1: to see how exactly as you were saying, Oz that
Speaker 1: that while you it is easy to point to another
Speaker 1: country and say these policies are clearly uh harmful to
Speaker 1: people and are therefore bad, we also need to make
Speaker 1: sure we're reflecting on the environment that we ourselves are
Speaker 1: in when we I'm sorry, go ahead, oh no, I
Speaker 1: was just gonna make one comment, you know, and for example,
Speaker 1: in the state of Arizona, if you applied for a
Speaker 1: driver's license in the state of Arizona, your photo was
Speaker 1: then put into a database that was being used by
Speaker 1: that was being used for facial recognition, right, and that
Speaker 1: was without driver's consent. Basically, law enforcement came back and
Speaker 1: was like, whoa we you know, we think people know
Speaker 1: that this is going on. You know, that was their
Speaker 1: best answer. It wasn't like, oh, there was you know,
Speaker 1: fine print that people didn't read. It was basically like, well,
Speaker 1: we thought people knew, and so you know, I we
Speaker 1: can't exonerate yeah, sort of our own our home turf,
Speaker 1: because there's certainly I don't even know if you would
Speaker 1: call this misuse. It just seems like exploitation um for
Speaker 1: gain for for basically gains of I think police departments
Speaker 1: that are seeing this technology, recognizing how powerful it is,
Speaker 1: but also realizing that it's something that needs to be
Speaker 1: regulated and not knowing how or not really caring. And
Speaker 1: I think Jonathan, you used the great example of the
Speaker 1: n S a UM, which I think tie is very
Speaker 1: neatly to what we're talking about. Edward Snowden had a
Speaker 1: very haunting phrase which was turnkey tyranny to describe basically,
Speaker 1: once you build infrastructure for something, um, anything can happen.
Speaker 1: And the technological infrastructure we have here in the US
Speaker 1: for surveillance and social control is I mean, we have
Speaker 1: few cameras, you know, there are more distinctions between companies,
Speaker 1: but effectively the infrastructure exists to do what's happening in
Speaker 1: China here. And that's very frightening because you know, as
Speaker 1: we know for Henry Ford's what wonderful pressure to build
Speaker 1: roads in the US. Guess what you build the roads,
Speaker 1: people are going to drive cars and not take the train.
Speaker 1: So once this infrastructure exists, and you add to that,
Speaker 1: you know a leader who doesn't respect norms or wartime,
Speaker 1: all of a sudden the barriers that we think are
Speaker 1: so solid to protect that infrastructure being weaponized against us
Speaker 1: start to road very very quickly. And I think that
Speaker 1: that's the moment we're in right now. And that's another
Speaker 1: reason why he wants to call this podcast sleepwalkers, because
Speaker 1: we don't insist on those norms and legal protections. Bit
Speaker 1: by bit, the infrastructure will have its own logic and
Speaker 1: one emergency after another. Remember the Patriot Act will allow
Speaker 1: this technology to be used against us in ways that
Speaker 1: we currently find sickening and horrifying and terrifying. In China,
Speaker 1: they could easily come home. Yeah. Yeah, it's a sobering point.
Speaker 1: And on that point, I think we're going to take
Speaker 1: a quick break so I can suck my thumb in
Speaker 1: the corner. Okay, alright, Pruny thomicide. Now we've talked about
Speaker 1: some of the differences between say, China and the United States.
Speaker 1: One of the things I thought was interesting is the
Speaker 1: idea that in China you have you have sort of
Speaker 1: a very concrete strategy in place, right, a top down strategy,
Speaker 1: and it's it's pretty much all the companies that are
Speaker 1: working on this strategy are in alignment with it to
Speaker 1: some degree or another. Some are very much in step
Speaker 1: with the state government. Others are to a lesser degree perhaps,
Speaker 1: but still you know, following along the strategy. Meanwhile, in
Speaker 1: the United States, it's much more of this competitive this
Speaker 1: this classic capitalist idea of competition in the space where
Speaker 1: you have all these different pockets that are all trying
Speaker 1: to own a I themselves competing against each other. So
Speaker 1: we're getting lots of interesting innovation, but not nearly at
Speaker 1: the same speed or scale as we're seeing in China.
Speaker 1: Is that is that more or less a correct assumption
Speaker 1: or am I way off base here? No? I think
Speaker 1: that's completely fair. You know, this year, the government that
Speaker 1: President Trump did announce an executive order on AI in February,
Speaker 1: and so that was that was seen as a kind
Speaker 1: of related response to what China are doing. And that
Speaker 1: executive order that the President issued had four major components.
Speaker 1: Number one, to set AI as a national priority of
Speaker 1: the United States. Number two, interestingly, to get better at
Speaker 1: data sharing between the government and private enterprise. Number three,
Speaker 1: it is the ethical guidelines on how AI is used
Speaker 1: in terms of surveillance and military and number four to
Speaker 1: make sure that the United States is doing the best
Speaker 1: it can to educate the next generation of engineers and
Speaker 1: AI scientists. Now, those are all good things, apart from
Speaker 1: maybe two number two, the data sharing um. But guess
Speaker 1: how much funding that executive order came with. I'm going
Speaker 1: to guess that was a big old goose egg. Zero dollars,
Speaker 1: zero dollars. Whereas shen Zen, which is a province in China,
Speaker 1: is spending fifteen billion dollars this year. That's one of
Speaker 1: the many, many provinces in China spending not even federal
Speaker 1: money but state money on AI. So in that context
Speaker 1: you can say, oh, you know, we're getting up to speed,
Speaker 1: we're responding, but you know you've got to put your
Speaker 1: money where your mouth is and we're not doing that. Yeah.
Speaker 1: And on a on a related note, you know, when
Speaker 1: we talk about things like the regulations, the laws in place,
Speaker 1: like how do we how do we then create policies
Speaker 1: that ensure that we're using AI responsibly and productively and
Speaker 1: not in ways that are harmful or destructive, um at
Speaker 1: least to our own set aisions if and hopefully not
Speaker 1: to anyone at all. We tend to see that lag behind,
Speaker 1: just like we do with technology in general. We tend
Speaker 1: to see technology innovations far out distancing our ability to
Speaker 1: to incorporate that into our our legal you know, kind
Speaker 1: of massive infrastructure. Understandably so obviously that that system is
Speaker 1: going to move much more slowly than technological innovation, but
Speaker 1: it does create these pain points, whether it's uh, you know,
Speaker 1: like autonomous cars. You know, you have different states in
Speaker 1: the United States that will allow for some degree of
Speaker 1: autonomous car testing. Meanwhile, you've got companies like Tesla that
Speaker 1: are rolling out vehicles that have autopilot feature, which, to
Speaker 1: the company's credit, they say, is not meant to be
Speaker 1: taken as an autonomous system. But tell that to all
Speaker 1: the people going down the highway who are leaning back
Speaker 1: in their cars with their hands off the wheel. Um,
Speaker 1: you could argue that that false of the responsibility of
Speaker 1: the individuals. But if enough individuals are doing it, you've
Speaker 1: got to start asking what's the value of actually having
Speaker 1: the system in place? Um, we're seeing that as being
Speaker 1: a kind of a disparity as well. Right, We're seeing
Speaker 1: this this gap between what we're capable of and what
Speaker 1: we should be doing, or at least what you know,
Speaker 1: what are legal system says we should be doing. And meanwhile,
Speaker 1: in contrast to that, and and Kara, you mentioned the
Speaker 1: EU a couple of times in our last podcast. Over
Speaker 1: in the European Union, you have committees dedicated to thinking
Speaker 1: about these sort of things and starting to propose potential
Speaker 1: UH strategies or even presenting different options for strategies for
Speaker 1: dealing with AI. Even beyond these these cases that I'm
Speaker 1: talking about, like they're they're going to the point where
Speaker 1: I remember reporting on this a couple of years ago
Speaker 1: for Forward Thinking, a series I used to do where
Speaker 1: the EU was proposed a committee in the EU, or
Speaker 1: rather was proposing the idea of granting personhood two artificially
Speaker 1: intelligent systems, And on the face of it, that sounds
Speaker 1: absurd to a lot of people, the idea of granting
Speaker 1: a non human the concept of personhood, despite the fact
Speaker 1: that in the United States we have corporations which are
Speaker 1: exactly that. But yeah, like, hey, hey, wait, we corporations
Speaker 1: can be people too, and uh can give money as
Speaker 1: long as they can give money to politicians, absolutely, so
Speaker 1: why can't robots. But the point that the EU committee
Speaker 1: was making was not that robots have feelings and we
Speaker 1: should really be considerate of them, but rather there needs
Speaker 1: to be some way to start to establish concepts like accountability.
Speaker 1: In the case where some form of AI constructor or
Speaker 1: robot causes harm in the form of damages or injury,
Speaker 1: how do you are to determine who's at fault. We
Speaker 1: touched on this a little bit in the last episode,
Speaker 1: so to me, it's fascinating that those are discussions that
Speaker 1: are popping up, like very serious discussions in the EU.
Speaker 1: And Oz I think when we met briefly in New
Speaker 1: York a couple of weeks ago, we talked about the
Speaker 1: fact that this is an area of the world not
Speaker 1: known for making incredible advances in AI technology. It's not
Speaker 1: like you look at Europe as saying this is where
Speaker 1: the hot bed for AI development is, but it is
Speaker 1: a region that's dedicating a lot of consideration to the
Speaker 1: implications of AI in day to day lives. Yeah. Absolutely,
Speaker 1: I mean, the EU has been out in front on
Speaker 1: thinking about technology and AI. Um Obviously, g d PR
Speaker 1: was a big act on regulating data and informing people
Speaker 1: about how people's data is being used passed in the EU,
Speaker 1: which triggered a whole series of conversations in the US
Speaker 1: about data regulation which will probably see they're starting now,
Speaker 1: we may see them come into law in the next
Speaker 1: two or three or four years. So the EU, good
Speaker 1: old Europe, despite its stifling effects on innovation I think
Speaker 1: and on technological innovation, is an innovator in terms of regulation,
Speaker 1: which probably sounds like a contradiction in terms and this
Speaker 1: is an area that Karas looked into really closely and
Speaker 1: has some I think, very interesting insights about. Yeah. Yeah, well,
Speaker 1: I mean, as I was saying, to you earlier actually
Speaker 1: on the form I guess it was the former the
Speaker 1: episode before this. Um, yeah, you know, I think it's interesting.
Speaker 1: The EUSE approach to me up very recently, you know,
Speaker 1: was to basically collect a group of fifty two experts
Speaker 1: and you know, create these seven core requirements for artificial intelligence. Now,
Speaker 1: I mean I can name them. You know. One is
Speaker 1: human agency and oversight. The other is technical robut us nous.
Speaker 1: The third is privacy and data governance. The fourth is transparency.
Speaker 1: The fifth is AI that AI systems should be sustainable,
Speaker 1: um whatever that means. UM, AI systems should be auditable.
Speaker 1: As we were talking about with you know, black the
Speaker 1: black box problem, you know, AI should also be available
Speaker 1: to all. You know, this is what we talk about
Speaker 1: in terms of bias, gender bias, um, you know, racial bias,
Speaker 1: all of those things. But I don't I have a
Speaker 1: bit of an issue with it just in that it's
Speaker 1: it doesn't seem to have much action involved in it.
Speaker 1: There aren't many action items. I think I think it
Speaker 1: is important, um for governments to to set standards you know,
Speaker 1: as a as a sort of first step, um, you know,
Speaker 1: and I think it also primes, you know, sort of
Speaker 1: average citizens to be aware of misuse, right, because when
Speaker 1: you set when you set up requirements, it means that
Speaker 1: these are things that can be misused and be misused easily.
Speaker 1: And I will say, you know, whenever I go home,
Speaker 1: every time you go onto website on your phone, notifications
Speaker 1: saying are you willing to let this website put cookies?
Speaker 1: Are you willing to share your data? Are you willing
Speaker 1: to accept targeted ads? And that the net effect socially
Speaker 1: of that reminder that your data is valuable and you
Speaker 1: have a choice every single day fifty times that that
Speaker 1: inevitably caused the shifting consciousness and the shifting citizenship. So
Speaker 1: I do think it's easy to say this regulation is toothless,
Speaker 1: but I also think it can, you know, make people think, oh,
Speaker 1: it's a huge culture. I mean when you just think,
Speaker 1: I mean, think about it. Think about cigarettes, right, I mean,
Speaker 1: it's just not you just don't smoke inside right anyway,
Speaker 1: illegally you can't. But I'm saying, you know, just the
Speaker 1: shift in public perception about smoking, the shift in public respection,
Speaker 1: um perspective about sugar, for example, at least in the
Speaker 1: United States. You know, those were all things that at
Speaker 1: one point, we're not really discussed or talked about, and
Speaker 1: you know, everyone kind of smoke cigarettes and that's what
Speaker 1: people did and you know, then they got lung cancer.
Speaker 1: But you know, I think the there is as long
Speaker 1: as there is a public discourse about privacy, people will
Speaker 1: begin to care more and more about privacy. So I think,
Speaker 1: you know, the EU presenting um these seven requirements is
Speaker 1: a step in the right direction. Absolutely, and if if anything,
Speaker 1: will just make people think about these seven tenants when
Speaker 1: they're going about their sort of everyday lives, and I
Speaker 1: think we'll we'll make companies, um, you know, focus on
Speaker 1: building these requirements into whatever they are developing. You know,
Speaker 1: I think it's important for companies that are developing new
Speaker 1: technologies to think about bias, especially when the people who
Speaker 1: are developing the technologies might be quite homogeneous. So I
Speaker 1: think it's worth saying that, you know, we we tend
Speaker 1: to see the new world order in terms of America
Speaker 1: versus China. You know, not to wave the flag for Europe,
Speaker 1: which unfortunately my my country may longer no longer be
Speaker 1: part of. But it's a it's a huge it's a
Speaker 1: huge group of nations with tremendous purchasing power, and it's
Speaker 1: genuinely significant market for US technology companies. And so you know,
Speaker 1: the effects of this may seem far off and slightly irrelevant,
Speaker 1: but you know, these finds that the EU is already
Speaker 1: slapping Facebook and Google with they're not necessarily materials to
Speaker 1: business yet. But you know, Europe as a voice for
Speaker 1: regulation is an important one because you know, actually these
Speaker 1: new technologies, AI technologies, they tend to affect the poorest
Speaker 1: in society and the most vulnerable in society in the
Speaker 1: most negative ways. So algorithmic discrimination, the replacement of you know,
Speaker 1: of low education, shall we say, jobs like driving or packaging.
Speaker 1: You know, these are things that are being experienced at
Speaker 1: the hard edge by people who don't have much of
Speaker 1: a voice in the political system. And so the fact
Speaker 1: that the EU is is taking up the mantle, even
Speaker 1: though it comes with hypocrisy, like using facial recognition at
Speaker 1: the ports of entry, even though you know that the
Speaker 1: level of the finds that can be applied to companies
Speaker 1: like Google and Facebook can never hurt their bottom line,
Speaker 1: I would say, is an important and valuable thing that
Speaker 1: it's happening. And so you know, I think the EU
Speaker 1: can offer some point of reference for how we may
Speaker 1: think about regulating AI and technology in the US in
Speaker 1: the future. And I think that you know, you've heard
Speaker 1: futurists say we need to have some very serious conversations
Speaker 1: about AI and the ethics of AI and how we
Speaker 1: can make certain we're being responsible custodians of a I
Speaker 1: and UH. To me, that was one of those things
Speaker 1: where it was like, we need to talk about talking
Speaker 1: about this, like that was the conversation for a very
Speaker 1: long time. We need to talk about talking about it.
Speaker 1: It's like having a meeting to talk about when you're
Speaker 1: gonna have your meeting. Have you ever worked in an
Speaker 1: office before? Oh? Yeah, no, I worked in I worked
Speaker 1: in a college administrative office before. So I've had meeting
Speaker 1: about how we can have fewer meetings and this is
Speaker 1: not the way. Yeah. So, so having the EU actually
Speaker 1: take this step, even if you were to argue like
Speaker 1: this is a very early step and maybe there's not
Speaker 1: a lot of teeth to it yet, it is a
Speaker 1: step as opposed to what I've seen elsewhere where it's
Speaker 1: been talking about taking a step but not even doing
Speaker 1: that much. So I'm encouraged by it because it actually
Speaker 1: moves the conversation forward instead of us saying we need
Speaker 1: to have this conversation, the conversation has started. I don't
Speaker 1: think it's over yet. I think that this is a
Speaker 1: good way to actually force more parties to get involved
Speaker 1: and think about it and maybe even start proactively thinking,
Speaker 1: how can I make certain that the thing we are
Speaker 1: building is actually being built in a responsible way that
Speaker 1: isn't going to that we can mitigate as many unintended
Speaker 1: consequences as possible, knowing that that is impossible to do
Speaker 1: uh entirely, but to really try for it. So to me,
Speaker 1: this is this is one of those conversations I could
Speaker 1: have all day long. But I know you guys need
Speaker 1: to get going because there's going to be someone else
Speaker 1: who's going to have to use the studio you guys
Speaker 1: are in, So I'm going to I'm not going to
Speaker 1: have us go all day long on this. Plus, we're
Speaker 1: recording this on a holiday weekend, and I know everybody
Speaker 1: wants to get home, so we're gonna wrap it up.
Speaker 1: But I want to thank you guys so much for
Speaker 1: agreeing to come onto my show. Uh it's a fascinating conversation,
Speaker 1: and you guys obviously have some great perspectives on this.
Speaker 1: And again to my listeners out there, if you haven't
Speaker 1: subscribed to Sleepwalkers, go check it out. It's a really
Speaker 1: well done show. I've been very impressed as someone who
Speaker 1: has a solo show. Most of the time I listened
Speaker 1: to it, I just think, wow, that's that's so awesome,
Speaker 1: that's so great. I wish I were on that show
Speaker 1: every now and then. So hint, hint, if you vernee me,
Speaker 1: you just we love it. We would absolutely love it.
Speaker 1: Let's talk about that. We had a great time today.
Speaker 1: Thank you, Thank you guys, and you guys, if you
Speaker 1: want to get in touch with me, drop me a line,
Speaker 1: say hey, you need to talk about this other topic
Speaker 1: or those guys were great. Have them back on the
Speaker 1: show as soon as possible. Send me an email. It's
Speaker 1: tech Stuff at how stuff works dot com. Pop on
Speaker 1: over to the website that's tech Stuff podcast dot com.
Speaker 1: You'll find the archive for all of my episodes. If
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