The Influence of AI on Human Communication

Pushkin Tim here with an exciting announcement about the Cutionary Club, our Patreon community for Cautionary Tales listeners. So many of you joined our live table read earlier this year that we're doing it again Join me and my production team for a live reading of an unreleased episode about the people who almost invented the iPhone fifteen years early and the surprising reasons they failed This will be a chance for you to see how the stories we tell are developed in real time And ask your burning questions about cautionary tales It's on the eighth of July at five PM UK or noon Eastern If you join the Patreon before then or if you're already a member, you'll get your exclusive invitation Patreon d. com slash Putionary club. That's Patreon P a T R E O n d. com slash Pautionary club This is an iHart podcast Guaranteed human. When you own your own business, you own every decision. 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Mrs. Goodaair is enjoying a leisurely breakfast while she reads the morning paper. It's april eighteen twelve, and the headlines are dominated by Wellington's military successes in Spain A strange noise s her from her reading sounds like the Iiron gates to her home Rattling She rushes upstairs to get a better view and sees the mob For it is a mob more clearly They're throwing stones, making lewd gestures and shouting for her to open the gates twowo men appear to be wearing dresses, proclaiming loudly to be General Lud's wives. She knows exactly what this is about. It's about what's in her husband's mill next door So why are they at her house Her husband, John Goodaair, is out of town She hovers at the window, unsure of what to do The mob leaders grow impatient They shout to their comrades that it's time to move on and begin marching through the streets of Stockport. They weave through the town, they smash windows and break down factory doors. By noon, the mob has swelled to over two thousand men Soon they run out of targets, so they turn back to where they began. John Gooda's Enormous Mill place many of them have spent their working lives Once a symbol of pride in their craft, now a symbol of everything they feel is wrong with the industrialized world Break down the doors, smash through the windows, and destroy all they can inside Every last frame, every last spindle The mob has grown so large that even the Iiron gates to the Good Air home can't hold them back This is good air has already gone A wise move. Mlood ides burn the house to the ground I'm Tim Harford, and you're listening to cautionary tales live at the Bristol Festival of Economics Loyal listeners will remember this is not the first time the Ludites have featured on this podcast Two years ago, I told you about the failure of the Ludite Revolution The weavers who were incensed that automation was devaluing their craft in genereral Lud's rage against the machines Today, the Lodites seem more relevant as the so called AI revolution threatens to overturn the world of work So should we be smashing up large language models or is resisting as futile as it was for the Luddites? Who's going to be most affected? And have economists been asking the wrong questions all along I'm joined by a very special guest, Sarah O'Connor. She's a financial Times journalist with a specialism in technology and work. And she's written a book called We are not machines. future of work She is the perfect person to guide us through what's coming next And she's got plenty of cautionary tales to tell us Welcome, Sarah Hello, Tim, Thankk you for having me. Oh it's a pleasure. We've got to get something out of the way first. Sarah O'Connor, have you seen the Terminator movies yet No. You're gonna have to watch them. It's a point of principle. Yeah, it now feels like stubbornness. Yes. so you might have noticed that my name bears a faint resemblance to the heroine of the Terminator films. Growing up occasionally, people made Terminator jokes to me, and as a result, I never watched them on principle because it annoyed me So about a decade ago, I went accidentally sort of globally viral when I very simply tweeted a news story that I'd seen come out which was that a robot had killed a worker in a Volkswagen factory and didn't realize that this would cause the internet to break. So yeah, so people just found it very hilarious that someone called Sarah O'Conor had written about robots. and for about a decade, people have occasionally sent me You know, terminated gifts posters of the Terminator films with my face phhotoshopped ear. And as a result, no, I have not watched those. Okay. The book is fantastic We are not machines What's the headline? What you what are you basically driving at with this book ate what when I'm tryrying to say in the book is that You know, we're all sort of drowning in information predictions about AI and what it might do to the world of work. And a lot of those are coming from either economists or the big tech executives who have created large language models and are marketing them And both these sources are unreliable for different reasons. Yeah, the tech guys have something to sell, right? And so they have their own motivations and then you know, economists, I think are trying their best to figure out what's going on, but the The way in which they're doing that, I think is very feels very abstract to me As someone, you know, I'm a reporter at heart. So my favorite thing to do is to like get my notebook, put my boots on and go and meet people and stand outside the factory gates and talk to people about what's actually happening. And so over the past few years I've just felt very frustrated that everything that I'm hearing about this is coming from people who are either looking at spreadsheets and models or who have a product to sell. And I just wanted to hear less about what these men say is going to happen and more about what's already actually happening from the people that it's actually happening to. So in the book, I basically went to find people and places and workplaces that are on the front lines of what's already happening. so people who are encountering autonomous robots in their workplaces or are working with or for or around large luggage models and they're starting to change the way they work. And when I did that, what I realized was that Now, I wasn't really hearing this very utopian story that This is liberating me. This is freeing me from dull, dirty, dangerous work and making everything fantastic. But nor was I really hearing a lot of stories that were like, My job has been completely wiped out What I was hearing instead were stories about quQuite profound changes to the nature of people's jobs and how they felt about their jobs and whether they enjoyed their jobs or not. And some of those were quite ionary tales, you know, there were A lot of people who were saying, actually what's happening to me is almost the opposite of this idea that Technology is going to give us space to be more human. People were finding themselves sort of crunched into systems that were paced by machines, run by machines in which Judgment was being overtaken by machines in which creativity was being sort of compressed or contained by machines. And I thought actually, if that's what's beginning to happen to people, then everyone should know about that and we should try and talk about why that's happening and whether there is a way to avoid that because fundamentally, I don't think that's what anybody wants. Before we sort take a trip to the cutting edge, I just I wanted to go back couple of hundred years, we began with the Ludites. Are they still relevant? Do people misunderstand the story of the Ludites? Yeah, I think they are still relevant. I mean, Ludite is just now used as a sort of a flippant term for somebody who's sort of reflexively anti technology and just doesn't like any new tech. But actually the Luddites, they weren't really fighting against technology full stop. They were fighting against the way in which machines were being put to a new use, which was to them out of the equation These sort of knitting and wide frame machines, they weren't displacing work entirely, what they did was they allowed people who had no skill and no experience to make a less good quality productroduct And in that sense, as we might come ono, it actually has an awful lot of similarities with some of the technologies that we're seeing today. Instead of knitting a stocking, you knit a massive bit of cloth that you can make a bunch stockings out of and you just cut them into strips and then you make the stockings, the stockings are terrible they fall apart. so you've suddenly got Interesting well paid jobs being replaced by boring badly paid jobs expensive, high quality work being replaced by Crappy work. E if they were lower quality, they were also a much lower price and that I think that was a deal that a lot of consumers were willing to make So let's talk about warehouses. The picture I have in my mind or the picture I had in my mind before I read the book was in fact, I realize a picture painted for me by you about ten years ago onene of the things that some workers in these p was they had this earpiece that the Jennifer unit basically just a voice in their ear telling them where to go in the warehouse, what to pull off the shelves You don't need them to think about the best way to get around the warehouse or to remember anything, justust tobey the voice in your head. So this sort of creation of these flesh robots So I was reading this article by you about ten years ago and thinking that that sounds bad But of course that's ten years ago So how accurate is that image of of what is now happening, what's changed Yeah. so quite a lot has changed and actually I think that article from ten years ago and that sort of reporting that I've done. And just to clarify, the Jenifer unit isn't something that's used in Amazon warehouses, but it is used in some other warehouses. really informed the way I used to think about technology. So yeah, I met and interviewed a lot of people over the years who worked in jobs in which they were basically expected to work like robots. I used to think Well, you know, bring on the damn robots then. you know let's get real robots in to do these jobs. L this is a waste of kind of human potential. and this is a great example of where automation would be brilliant. so I used to be quite a techno optimist in the sense that I thought there were huge numbers of roles that actually could and should be automated. So what's happened now in Amazon warehouses, at least in the one that I went to visit is that the robots have arrived, but not really in the way that I had imagined. So I'd basically imagined like a one for one swap, right? So instead of a person walking around, you'd have like a kind of human humanoid robot doing it. Yeah, but it's never actually like that, is it? It's never ever like that. Like a robot accountant is Basically Microsoft Excel. account is not C three PO sitting in your chair.ing away how it work laptop. No, exactly. And it's not how it works in Amazon either. I went to visit a new Amazon warehouse, which has their sort of latest automation technology. And the way it works now is that rather than you as a worker walking around for like maybe ten miles a day, just weaving between all of these shelves and picking things off Now on each floor, there's a big fence and around the perimeter of that fence the workers stand stationary in one place. and inside the fence are the robots, but the robots are basically like giant roombers. And what they do is they drive around inside this perimeter fence and they pick up the shelves and they bring the shelves to the workers And so you now as a worker, you stand in one place and a robot brings you a shelf and then a light illuminates which part of the shelf you need to look at and a screen gives you a picture of what the thing is you need to pick off And I tried this out, I think I had to pick off like a mobile phone case with a dolphin on it. So you know you pick it out and then another light illuminates which box that you need to put it into and you push a big button. And then that robot takes that shelf away and the next robot's already queuing up for you with the next shelf and you do the same thing. How long did you do it for Two minutes. Okay. How long How long do they do it for? Ten hours a day forty hours a week with two thirty minute breaks. And so this is not what I had imagined when I sort of cheered on the robots and thought this would be great You know, in some ways, I think that job is better. It is less physically demanding than walking around for ten hours a day. Amazon says that it's safer, so they have fewer injuries and accidents. and I think that's probably true But if anything, I think it's also become more boring and more monotonous. and also it's still not that Easy on the human body to stand up for ten hours a day and because the They're now much more productive, right? because not you're not walking around from one place to the next. And so the products are coming at you. And so you're bending, you're lifting, you're twisting over and over and over again. So I think it's still qu quite a physically demanding job and arguably like a bit more monotonous and a bit lonelier Presumably there are people who did the old job and now do the new job. so what do they think Well, I interviewed one worker who had volunteered to transfer from a manual old fashioned warehouse to a new one and he wanted to go back He said, actuallyctually, I don't like working with the robots. It's too intense, it's too exhausting It's really lonely. I don't get to talk to anyone anymore. and yeah, he's now transferred back to his his old warehouse. By way of contrast, you also visited a mine in Sweden. So how is automation taking off there Yeah, so this mine in Sweden was right up near the sort of fringe of the Arctic circle and they mine copper there and various other minerals And it is one of the most sort of technologically advanced mes in the world, or say they say, So it used to be that miners would drive vehicles around below gass so very deep down It's horrible down there. It's like really dark, It's really humid, claustrophobic. And now the vehicles are autonomous, so they drive themselves And the miners sit in a control room. They can take over the vehicles if they need to, but a lot of the time they're just they're sitting there, they're watching what's happening on big screens, they're in a comfy chair And they're listening to Spotify, they're listening to the ice hockey and the ones that I spoke to were quite satisfied with this change in their working conditions is the fact that the Swedish mine workers are happy and the Amazon workers best ambivalent about the way their job works What explains the difference? So I think there's a few differences. One difference is that you know the reason that in Amazon, they don't have humanoids walking around doing the whole thing is technology is not ready yet. And so in some ways Humans are still kind of plugged into a system which is like part robot, part human. But it is increasingly being paced by the capabilities of the robots Whereas I guess for the miners, they do not need to be in the cab anymore. and so that means that there's the potential for a much kind of greater improvement in there health and safety, but as well as that, I think there is a governance thing. so I don't know how much everyone knows about Sweden, but they have a very distinctive kind of labour market whereby trade unions are very powerful. And there is a rule that any new technology has to be bargained collectively about before it happens. And so Before they introduced this new technology, they had to sit down with the workers and they had to talk about it and how it would go and what the workers' concerns were and what the company wanted to get out of it. And you know, more broadly in Scandinavian countries, what you find is that when people answer surveys about how they feel about technology People are like much more positive than they are in the UK or in the US. And I think that's because they have a sense that they will have a seat at the table when those decisions get made Thank you, Sarah. You're listening to a special caautionary conversation recorded live at the Bristol Festival of Economics A the break My guest, Sarah O'Connor telling a cautionary tale about language translators artificial intelligence Stay with us runun a business and not thinking about podcasting Think again, more Americans listen to podcasts than ad supported streaming music from Spotify and Pandora. And as the number one podcaster, IiHart's twice as large as the next two combined. So whatever your customers listen to, they'll hear your message. Plus only IiHart can extend your message to audiences across broadcast radio think podcasting can help your business? Think iheart. Streaming, radio, and podcasting. Let us show you at iheartadvertising.ot com. That's iheartadvertising dot com Tim here with an exciting announcement about the Cutionary Club, our Patreon community for Cautionary Tales listeners. So many of you joined our live table read earlier this year that we're doing it again Join me and my production team for a live reading of an unreleased episode. about the people who almost invented the iPhone fifteen years early and the surprising reasons they failed. This will be a chance for you to see how the stories we tell are developed in real time And ask your burning questions about cautionary tales It's on the eighth of July at five PM UK or noon Eastern If you join the Patreon before then or if you're already a member, you'll get your exclusive invitation Patreon. com slash cautionary club. That's Patreon. P A T R E O N dot com slash Cutionary club We're back. This is the Bristol Festival of Economics. I am Tim Harford and my special guest is financial Times journalist and author. Sarah O'Connor So Sarah Phaps the canary is in the coal minine are the translators. When I thought about translators, I just thought Oh, You guys are just allve lost all your jobs because of Google Translate. It's all gone But actually your The story you tell in the book is a lot more interesting and more complex than that. Yeah. so I interviewed some translators for my book. One of them is a guy called Peter He lives in the Czech Republic and he translates subtitles for TV shows which is a great job. I mean, he toald me lots of things about why it's more difficult than you might imagine to do that. So for example You know, in English, we just have one way of saying you, but in lots of languages, including Czech There's like a formal tense of you and an informal tense of you. And so when you're writing the translated subtitles, you have to think like, how well do these characters know each other? Like what tense would they be speaking in? And that might change through the course of an episode or through the course of a series. And so there are lots of kind of interesting judgment calls that you have to make and then you know, translating jokes is another thing that's incredibly difficult because so many jokes are like culture specific, or they're like plays on language. We're in a bookshop. We are the guests of waterstones in Bristol. must be some asterisks and obliqus somewhere in the bookshop. Yeah, they're the perfect example, right? So Oelix's dog. in the original French is called I fixes, which means obsession And the brilliant English translation is dogmatics. You know, so like there's so much sort creativity and humor involved in being a really good translator and so like this is a great job for people that enjoy doing that sort of thing. But what's happened to him and to people like him is that he has not lost his job entirely. Like it's actually quite hard to get a machine to translate things with that level of cultural knowledge and understanding say Just to explain slightly the way a lot of translation works is A lot of translators are freelancers and there are agencies that will take work from you know a TV studiA and then parcel it out to fewreeelance translators. And what those agencies have started to do is to take something Get it translated by a large language model or a different kind of machine translation service and then give it to the translator and say, Hey, can you just check that this is right and maybe like just finesse it a little bit, polish it, make it sound a bit more human? And this has become the kind of bet noir of lots of translators because what they say is that is A, you know, you expected to do this much faster And B, you're expected to do it for much less money But in fact, if you care about quality, it's very difficult to actually check a translation is accurate. And then even things like trying to make it sound a bit better. that's actually what the translators told me was it's actually quite hard to do when there's already like an answer in front of you And it feels much less creative and more kind of cumbersome and less enjoyable. And so a job that was sort of creative and challenging and interesting has become faster harder, more monotonous feels more mechanical and fundamentally kind of less satisfying And I think that is a real cautionary tale and when I was speaking to them, it made me think a lot of the Luddites because What the translators will tell you is that the end product is less good quality. And there were even some studies that have checked this. So there was a big study that looked at a bunch of subtitles from TV shows before and after the introduction of machine translation post editing And the quality has kind of deteriorated. It's the stockings again. It's the stockings again, exactly. And I guess partly, obviously we care about the quality of jobs That's important. but I guess one of the interesting questions from the point of view of The consumer Be the whole idea here is even if individuals get worse jobs, the consumer gets more choice, more quality, lower prices I always do sort of wandere is is the product. actually better. and will the market deliver. kind the right trade offs or are we actually just going to make all kinds of mistakes and we end up with crappy products that we don't want. I'm just wondering whether I know I don't sound like an economist here I'm wondering whether we're just going to get stockings that fall apart and translations that we that are joyless and but some manager somewhere was convinced by some AI salesman somewhere that it would be that it would be fine Yeah. I mean, I think this is one of the things that I realize working on the book is that You know, Economists when they're sort of doing their modeling about which jobs might be displaced or degraded or changed by technology. they look at like, how good is the technology and compare that to how good is the human But actually like can a robot do my job as well as me? is not always a particularly useful question. Can someone persuade my boss that a robot can do my job as well as me? is a more relevant question, or Would my customers or consumers be content to have someone do my job less well than me, but for a much cheaper price? With the case of the translators Is this fundamentally about the technology? This just happens to be a thing that computers can do at a certain speed with a certain quality kind of is maximally disruptive. to the job of being a translator is it actually more to do with The fact, for example, that all these people are freelancers, is it actually to do with economic power and not to do with technology at all I think it's to do with both But I think you make a good point, which is that Often this question about like what will AI do to the world of work is seen as a technical question But it's not just a question of the technical side, it's also a question of like consumer choice and institutions and culture and bargaining power and economic power. So yeah, I mean, partly The reason it's been very disruptive to translators is that The translating is like the Basically all they do, like that one task of like translating something, if you're a freelance translator, that is pretty much your whole job Whas for a journalist, writing an article is like actually quite a small part of my job. My job also involves doing a lot of reading, going out to interview people doing stuff like this. And so 's more it's more disruptive in some particular professions depending on like how much of your tasks are automatable And then also yeah, like your your market power, right? If're if you're a freelaner then that's a very different thing to being a well protected miner in a unionized mine company in Sweden Can we talk about coders? Because superficially programmers software coders It seems quite like translators. It turns out that For some reason, large language models seem to be pretty good at coding, at least that's what I'm told. I wouldn't know, but People say it's pretty good So are coders in the same position as translators? Suddenly I've got all this terrible code and kind of they want me to do twice as much work for half the salary. Do they feel the same way as the translator Most of the ones I interviewed do not feel like that I think coding is an example of a job that in many ways actually has probably been enriched and made more fun and more productive by this new technology. And I think the reason that it is playing out different is partly this thing about bargaining power and where you sit in the sort of economic chain. But also, if you're a computer programmer, like what you really care about and love is not literally sitting there and writing out lines of code. What you love doing is like solving problems And so what the Tols do, they might automate some of the kind of the actual literal coding, but they're not automating kind of really fun creative problem solving bit It just allows you to like try things out or do stuff faster. This is the promise. This is what they keep telling us it's going to do for all the jobs,? It's going to do the boring stuff so you can do the fun stuff. And this is why they're so enthusiastic and think it's brilliant because for their jobs, it is pretty brilliant. What is it, then determines whether your job is like translating or whether your job is like coding And is it under our control or not? Yeah, so I think One of the things that I've realized And I now really flinch when I hear it and I flinch when I think that I've probably said it sometimes as well in the past. is that I think we're really using some of the wrong metaphors when we talk about this. so I don't know if you'veiced this, I find that like technology executives in particular, but also sometimes economists We'll talk about like there's a tsunami of change coming or there is a new wave of technological change I think it's misleading because it makes it sound like it's akin to a natural phenomenon. like it's something that's just happening that just came out of nowhere and it's going to happen to us. And it invites us to think that Best all we can do is A prepare for it and B get ready to mop up after it And you know these metaphors, I think are really useful to technology executives in their conversations with policymakers because know nobody wants to look like the fool who thinks you can hold back the tide, right? And so It invites you to think of this as something that is happening anyway and you know that there's very little that you can fundamentally do about it. But that's not true at all. That's never been true. Technology is stuff that is made by people and implemented by people. And there is a huge variety, as we've just discussed, in the ways in which it can play out in different occupations in different countries and in different parts of the labour market, and a lot of that is dictated by the choices that people make and the things they choose to value. You can do something about this because you can write columns in the Financial Times telling Sam Altman that he's being a nughty boy. What can Ordinary people who do not have newspaper columns and who are not running AI companies justust regular people, what can they do to to help direct this change in a more productive empowering way. I mean, I think People do and are and will direct and determine. this next progression of technological change because that's what's always happened. I mean, some people obviously have more power than others, particularly in terms of like what kind of working conditions they may or may not have to accept, but you know, everyone that I interviewed in my book, is responding to what's happening and you know, whether that is that they are going on strike or forming a union or whether it's that they are changing their profession or figuring out some new way of doing what they do in a different way. Also as consumers, you know, a lot of the questions we've been talking about is like, well, what will the market accept? We are the market, you know, so it's kind of up to us to decide whether we AI music or real music.'re so flat that no one's ever said I'm the market before. You are the market. The nicest thing anyone's ever said to me, That's. How to compliment an economist? Absolutely So you heard it, fight, fight back, stand up, show, show, show the man why you're better than the machine. Sarah and I are going to talk about large which models? afterfter the break. Run a business and not thinking about podcasting? Think again. More Americans listen to podcasts than ad supported streaming music from Spotify and Pandora. And as the number one podcaster, IiHart's twice as large as the next two combined. So whatever your customers listen to, they'll hear your message. Plus only IiHart can extend your message to audiences across broadcast radio If think podcast can help your business? Think iHart. Streaming, radio, and podcasting. call eight four four, eight four four iHart to get started. That's eight four four, eight four four iHart Tim here with an exciting announcement about the Cutionary Club, our Patreon community for Cautionary Tales listeners. So many of you joined our live table read earlier this year that we're doing it again Join me and my production team for a live reading of an unreleased episode. about the people who almost invented the iPhone fifteen years early and the surprising reasons they failed This will be a chance for you to see how the stories we tell are developed in real time And ask your burning questions about cautionary tales It's on the eighth of July at five PM UK or noon Eastern If you join the Patreon before then or if you're already a member, you'll get your exclusive invitation Patreon. com slash Cutionary club That's Patreon. P A T R E O n dot com slash Cutionary club We're back. I'm Tim Harford. We are live at the Bristol Festival of Economics and this is a cautionary conversation with expert in Atificial intelligence, expert in Worplaces, author of We are Not Machines, Sarah O'Connor. who is also my colleague at the Financial Times the The title of the book is We are not Machines You've given us some really striking examples of demands of made of workers to be more machine like being under constant surveillance, having to move. in a very kind of weird and unnatural way U I wanted to bring it back to the experience a lot of white collar workers have of sort of sitting at a computer every day and suddenly discovering there's this thing called Chat GPT Do you think that chat GPT. Is this making us more Machine like and we don't know it So this is something that a lot of the translators that I interviewed brought up. I think because they they're linguists so they have a like an ear for language and how it's changing. but a number of them said to me independently that they had noticed that the sorts of language that we are using is becoming narrower. and flatter and more homogeneous. and I wonder if that is partly because we are using ChatTPT more to write our LinkedIn posts and our emails. and maybe that even sps into the way that we communicate with one another. So I think there are certain risks there. But also, you know, I think large langles models do clearly have the capacity to do that thing that we talked about at the start, which is like take away some of the boring stuff. And I think there are plenty of examples of people doing that, whether it's like Oh now I don't have to take any minutes for this meeting Or now I don't have to spend two hours Googling three relevant research articles. But I do think it's also It's very easy to start also using it for things that maybe in the past we would have put a bit of human care and attention into like you I think a lot of people are using ChGBT now to write wedding speeches or speeches at funerals and that sort of thing, which You know, you might once have thought would were among the more human tasks that we did Although I have heard a few wedding speeches, Chat GPT would have done better than some of them. So you know, yeah Rising tide lifts somebats A you Are you frightened or are you hopeful for the future? I'm a lot more hopeful now than I was when I started writing the book actually And I think that's probably because of The people that I met along the way So like another of these sort of metaphors or like cliches that we often hear is, you know, people will say, well, you know, inevitably there's going to be winners and losers You know, theres there's dangers and opportunities And that sort of invites us to think like, o I better just wait and find out if I'm going to be a winner or a loser and like, you know, fingers crossed I'll be a winner, but you just kind of got your lottery ticket and then you wait and see that's not actually what people are doing. L people actually are maneuvering themselves and trying to figure out what they can do to make sure that things work out well for them. Like everyone is is shaping and determining this. So in that sense, I ended up more optimistic because I think that we have a lot more agency to figure out how this goes and to make sure it goes in a way that we want, then we're sometimes led to believe Thank you so much, Sarah Let's take some questions So We got a question from a cautionary club Member Emily. byy way, anybody wants to join the cautionary club It's very wonderful. You get the podcast ad free, you get bonus episodes, all very good. And you get your question read out live at the Bristol Festival of Economics. So Emily says there's a research institute called METR which found that both the expected and the perceived deficiency improvements from using AI in software R and D. were substantially overstated She asks, Do you think businesses are likely to scale back AI investment until the efficiency gains promised are demonstrated Hm. They sunk so much money in at this point that they feel they have to justify the expense I think it remains to be seen. I think that METR study was really interesting. becausecause what it sort of highlights to me is that You know, we were talking about this distinction between tasks and jobs And that actually your whole job might disappear, but some tasks within it might change But when you think about something at the level of an entire organization You've also got to think about jobs and systems And so you know computer programmer on his or her own might have become much more productive if they can use a coding AI system. but actually if there are still bottlenecks and other parts of that system, you might not really see the benefit of it. you know you might just create lots and lots and lots of code, but then you still you still don't have enough people to review it, for example, or you know, whatever it might be. And so I think what a lot of companies are finding is that suuddenly being able to do certain tasks within jobs much more or much faster doesn't necessarily mean that you're going to see the same kind of productivity outcome filter through to the whole organisation The other thing I would say is that we're still like in the very early stages of companies trying to figure out how to use these new tools effectively. And what I think we might start to see is companies kind of redesigning workflows around what the machines can and can't do. I mean, in a way, that's exactly what Amazon has done, right? I mean, it's completely changed its workflow in order to make the most of the machines that it has available to it at the moment and plugged humans in to do the bits that the machines can't do. But I think it's still a really open question. know, particularly with large language models. I mean the kind of the hallucination problem, I think is quite could be quite existential for a lot of high risk professions, you know, certainly You know, we're not going to be using large language models at the FT to write our articles because we just can't possibly trust them not to hallucinate. Yeah. I mean, I always fine when I'm using large language models. The first question is, will anybody else ever see any of this? and if the answer is yes, then it's unusable. If it's just for me, then sometimes it comes up with useful ideas, but like I absolutely cannot trust it at all to produce anything that anybody else will ever see So anyway. More questions. there were loads of questions. canan we get the mic someomebody looking quite young and fresh face there. What a question from Hi. I have a question, which industry do you think is most at risk of AI