Digital Disruption

00;00;01;28 - 00;00;40;23

Sarah O'Connor

I met very few people that had completely lost their jobs because of AI or robotics, but nor were some of these people saying that they felt that they'd been freed up from the boring or the monotonous parts in order to spend more time on the fun, creative, human relational parts? In fact, I started to hear people who said precisely the opposite seemed to be happening, that they were somehow being kind of crunched now into systems that were paced by machines and appraised by machines, and in which they felt as if somehow they had to act more like machines themselves in order to keep up and to comply with the way their workplaces were changing.

00;00;40;25 - 00;01;04;00

Sarah O'Connor

It's like we can't allow ourselves to just do less for the sake of doing this, and we're kind of resisting this, and it all feels too much if you listen to the language you use. You know, we say things like, I'm burned out or I need to disconnect or I need to switch off. You know, all of these phrases or phrases that you would use about machines, not about like fleshy mammals that are composed mostly of water.

00;01;04;01 - 00;01;17;03

Sarah O'Connor

They don't burn out, they just need a rest. And so, yeah, I think we've sort of slightly started to confuse ourselves with our own tools in a way that is not necessarily helpful.

00;01;17;05 - 00;01;38;20

Geoff Nielson

This is a show about the future of tech and the future of work. I'm Jeff Nielsen, and today we're diving into how AI and automation are actually impacting our work. Look, I'm sure you've already heard that AI is going to wipe out half our jobs, or that we're headed for some sort of post job utopia. And both of those claims should immediately set off your bullshit detector.

00;01;38;26 - 00;02;00;29

Geoff Nielson

So what is actually happening? My guest today is award winning journalist at the Financial Times, Sarah O'Connor, and she's obsessed with answering that question. Sarah has spent the last year with people and companies whose jobs are on the front lines of automation, from an Amazon warehouse to translation services to more surprising places like a mine in northern Sweden.

00;02;01;02 - 00;02;24;06

Geoff Nielson

She has so many deep, amazing stories and I had the chance to read her new book, We Are Not Machines, and it just never ceases to amaze me how much original research and thought leadership she brings to a space dominated by empty hype. So I'm really excited to pick her brain to understand whether AI can make us more human, or risks turning us all into machines.

00;02;24;06 - 00;02;31;06

Geoff Nielson

It should be an amazing conversation. Let's jump in.

00;02;31;09 - 00;02;50;16

Geoff Nielson

Sarah, thanks so much for joining us today. Really excited to have you. Really excited to talk about the future of work. And I mean, let's just jump right into it and maybe start with sort of a meaty question. But you know, we've all heard the rhetoric coming out of the mouths of AI CEOs about how this technology and how all technology is going to change work itself.

00;02;50;24 - 00;02;56;02

Geoff Nielson

I'm curious from your perspective, what are you seeing happening to work?

00;02;56;03 - 00;03;17;21

Sarah O'Connor

I was becoming quite frustrated with the way that discourse was going. It sort of seemed to me that we were becoming sort of an audience to these very big prognostications, mostly from the leaders of the technology companies themselves. You know, either these big utopian visions that are always going to be great, you know, everyone will be able to work less.

00;03;17;24 - 00;03;36;00

Sarah O'Connor

We'll be able to offload all of the sort of the dull, the boring, the monotonous parts of our jobs onto AI and automation, and then we'll be freed up to spend more time doing the kind of human, creative stuff that was the sort of the utopian vision. Oh, and by the way, we might just work three days a week or something, spend the rest of the time in our hammocks.

00;03;36;03 - 00;04;01;23

Sarah O'Connor

And then, of course, you know, we've had lots and lots of these dystopian visions that actually 50% of white collar workers are about to be wiped out, that before long, because the machines are getting so much better, there'll be hardly any tasks left that humans are better than machines at. And therefore we need to think about some radical transformation of the economy in which most people can no longer earn a living based on the kind of labor that they can contribute.

00;04;01;25 - 00;04;23;15

Sarah O'Connor

And these sort of annoyed me for two reasons. I think. The first one was that they were all really predictions. They were all saying things about what might happen in the future. But I know because I write about the world of work for the feet and have done for more than a decade, the AI is already starting to change the world of work, that it is, entering all kinds of different workplaces and beginning to change things right now.

00;04;23;20 - 00;04;42;12

Sarah O'Connor

And yet, we were hearing not so much about what was really happening, and a lot more about what might happen at some indeterminate point in the future. And then the other thing that I thought was problematic was that all of these predictions were coming from people that are really at the top. You know, they are either coming from the technology companies themselves.

00;04;42;12 - 00;05;10;06

Sarah O'Connor

So, you know, obviously have a product to sell. So they're not necessarily the most impartial of observers. Or sometimes they were coming from like very sort of senior and interesting economists who, you know, I have a lot of respect for the work that they do, but what they have been doing is really quite an abstract sort of mapping exercise where they they've sort of taken every job that exists in the economy, and they've tried to break it down into all of its constituent tasks, as if that's a kind of easy thing to do.

00;05;10;07 - 00;05;29;08

Sarah O'Connor

And then they've sort of tried to map the capabilities of large language models against all of the tasks that exist in various jobs to come up with these lists. And I'm sure you've seen loads of them, because journalists like me like to write about them. You know that 60% of jobs in the economy are exposed to AI, or maybe it's 20%, or maybe it's 90%.

00;05;29;09 - 00;05;50;04

Sarah O'Connor

And, you know, they're all very different, these estimates. And they're not very useful either, really. Because for a job to be exposed to AI, it doesn't really tell you. Is that job going to get better as a result of AI being involved? Is that job going to get worse? Is it going to be degraded or skilled in some way, or indeed, is it going to be displaced altogether?

00;05;50;04 - 00;06;09;20

Sarah O'Connor

So to know that your job has like a 60% chance of being affected in some way is not actually a particularly sort of useful piece of information, it seemed to me. And the kind of journalism that I really like to do at the feet is to get out of the office, get my reporter's notebook, get my comfy boots on, and just go and find out what's happening on the ground.

00;06;09;21 - 00;06;32;18

Sarah O'Connor

So what I did in this book was I basically tried to go and find people and workplaces that were, as I saw, on the frontlines of this new kind of phase of technological change. So people who were already starting to experience the full force of disruption. So I spoke to software developers and translators. I went inside a new Amazon warehouse, which is now kind of crawling with robots.

00;06;32;19 - 00;06;56;07

Sarah O'Connor

I went down a mine in Sweden, which now has self-driving trucks and loaders kind of roaming around under there. I spent several days shadowing some community nurses in the Netherlands, and the question that I really had was the question that you just asked me, which is, well, what's actually happening? And I wanted to know it from the people it was actually happening to, because I felt like their voices, weirdly, weren't really being heard very much in this debate.

00;06;56;15 - 00;07;15;06

Sarah O'Connor

And to answer your question, that was a long preamble, I guess. Do I see your question? The story that I started to hear from? Lots of them, not all of them, but lots of them, was one that didn't really fit with utopian vision or the dystopian vision. So I heard from people who weren't being completely displaced from their work altogether.

00;07;15;06 - 00;07;54;00

Sarah O'Connor

I met very few people that had completely lost their jobs because of AI or robotics, but nor were some of these people saying that they felt that they'd been freed up from the boring or the monotonous parts in order to spend more time on the fun, creative, human relational parts? In fact, I started to hear people who said precisely the opposite seemed to be happening, that they were somehow being kind of crunched now into systems that were paced by machines and appraised by machines, and in which they felt as if somehow they had to act more like machines themselves in order to keep up and to comply with the way their workplaces were changing.

00;07;54;02 - 00;08;15;25

Sarah O'Connor

And I felt like that was a story that wasn't really being told. So was worth sort of being explored further. And one example of that would be that Amazon warehouse that I mentioned. So, you know, Amazon warehouses of old were basically just like massive great warehouses. And you would walk around between all these aisles and pick items off the shelf.

00;08;15;27 - 00;08;41;24

Sarah O'Connor

You might walk sort of 10 or 15 miles a day. So it's like a very hard physical job. And as we all know, like Amazon is quite technologically advanced company. And so although the job itself was quite manual and quite straightforward, not particularly technical, they layered on quite a lot of sort of algorithmic surveillance systems to make sure that people were working fast enough and were keeping up with the sort of targets that Amazon expected of them.

00;08;41;24 - 00;09;11;11

Sarah O'Connor

That was what the job used to be. So when I went to this brand new warehouse that I knew was full of robots, my vision for how that might have gone was basically that there would have been like a one for one swap. So instead of humans walking around, they'd be like humanoid robots, sort of like, you know, jerkily walking from shelf to self and doing the exact same thing that the humans used to do, and that the humans would either have just kind of lost their jobs altogether, or maybe they would have been sort of upscaled, you know, they would now be maintaining the robots or supervising them, sitting at screens doing something that

00;09;11;11 - 00;09;40;26

Sarah O'Connor

was a bit more kind of white collar ish. That's not really the way it's playing out inside these warehouses. And that's partly because, and this is true for lots of different types of automation, is that, you know, what these new tools can do is often do some parts of a job, but not the whole job. And so for the Amazon workers, the bit that is still quite hard to automate away is human dexterity.

00;09;40;28 - 00;09;58;09

Sarah O'Connor

Like, our hands are unbelievably flexible and extras, and we are really adaptable. So, you know, if you're working in an Amazon warehouse, you might have to pick like a tiny nail varnish bottle off a shelf. And then the next thing you have to pick up is like a massive, great stack of books or a dinner set or something.

00;09;58;10 - 00;10;16;23

Sarah O'Connor

And for robots to have that level of adaptability and dexterity, like that's still kind of beyond them, I think it will be forever. But it is for now. So what Amazon has done is basically just redesign the whole workflow around what robots can do and what they can't do, and they've plugged the humans in to do the bits that still can't be done.

00;10;16;24 - 00;10;34;24

Sarah O'Connor

And so what that kind of looks like in practice, I went inside one and had a look is that now the warehouses can actually be a bit smaller because you don't need aisles between all the shelves anymore. All the shelves are kind of packed very tightly together in the middle of each floor. And then there's a big perimeter fence that surrounds all the shelves.

00;10;34;25 - 00;10;57;19

Sarah O'Connor

And along that fence there are gaps. And the human workers stand in these gaps in the fence and what the robots do, the robots are kind of big, low things that are a bit like robot Hoovers, but much bigger. They slide under the shelving units and they bring the shelves to the workers. So now as a worker, you stand there and a robot brings you a shelf, and then a light illuminates where you need to look on that shelf.

00;10;57;19 - 00;11;12;25

Sarah O'Connor

And the screen shows you a picture of what you need to pick off that shelf. And you pick it off. And then another light illuminates which box you should put that into next to you. So you do that and you push a button, and then that robot takes that shelf away, and the next robot brings the next shelf in.

00;11;12;26 - 00;11;29;07

Sarah O'Connor

Now this is like much more productive and efficient from Amazon's point of view, because instead of, you know, if you're walking around between all these different shelf locations, you might be picking, you know, I don't know how many items per hour, but in this new system, you're probably going to pick sort of 3 or 4 times as many.

00;11;29;07 - 00;11;46;23

Sarah O'Connor

So it's much more productive, but it still requires a lot of human neighbor. And the question that I was sort of left with having, you know, I've reported on the old warehouses and I've been into these new ones, is like, did this job get better or worse? Like, is this actually an improvement in the conditions in this work?

00;11;46;24 - 00;12;12;26

Sarah O'Connor

Have people been freed up to to feel more human in any way? And I think it's got better in some ways and worse in others, if I'm honest. So Amazon says, and I think that this is true. Is this a safer job now it's less physically demanding. You know, walking around all day. It's really hard work. You know, I used to interview workers who were getting blisters on their feet and they would, like, cover their feet with Vaseline before they started a shift because it was so physically demanding.

00;12;12;26 - 00;12;43;03

Sarah O'Connor

So I think it's true that it's less physically demanding. And we know that like injury rates in Amazon warehouses, which used to be quite high, they've been sort of declining as the level of automation has been going up. So all of that seems like a good thing. But what some of the workers told me who work in these new warehouses is it is even more boring and it's more lonely, you know, because now you're standing there and it's just you and the robots, really, and you're not even sort of walking past people and having, like, a brief conversation.

00;12;43;06 - 00;13;03;26

Sarah O'Connor

So, yeah, I mean, one of my interviewees, he'd asked for a transfer to this new warehouse because he thought it would be quite exciting working with robots and maybe there would be more opportunities for progression. But actually, he just he said he he felt like a robot himself in the system. And in the end, he got a transfer back to the old manual warehouse where he got to do things the, the kind of old fashioned way.

00;13;03;29 - 00;13;25;19

Sarah O'Connor

And, and what that brought home to me is that actually, it's not necessarily a given that when you introduce automation into a job, it will necessarily take away the dull parts and free people up to work less or to work more fluidly or in a more human way. You know, it can. It can potentially go the opposite way.

00;13;25;22 - 00;13;48;23

Sarah O'Connor

And that's the that's the sort of the blue collar side of that. But I also spoke to some white collar workers who felt kind of similar, that they were experiencing some of the same things. And one example of that would be translators. So, you know, I have think going into this had imagined that translators would simply have been wiped out by, you know, we all know that machine translation is pretty good now.

00;13;48;25 - 00;14;24;18

Sarah O'Connor

And but that's not really the case. There are still a lot of human translators out there, but the nature of that job has also changed quite profoundly. So some of the people I spoke to, they translate the subtitles for TV shows. So that might be like a Disney show or a Netflix show. And what has happened to those people is that rather than that being quite a kind of creative job, where you sit and watch the program, you think about how would I render the meaning of this sentence or this joke, you know, into my home language in a way that still conveys the right level of kind of emotional intensity or, you know, captures

00;14;24;18 - 00;14;43;06

Sarah O'Connor

the humor, which is really actually quite difficult because a lot of jokes in English are they're puns. They're like word based jokes. That's really tricky. But when you get that right, that's quite satisfying for a translator. Now, my favorite example of this is the Asterix stories. I don't know if you ever read Asterix or if that's a big thing in in Canada.

00;14;43;09 - 00;15;09;05

Sarah O'Connor

Yeah. So I mean, the the English translations of Ashoka was originally in French. The English translators were absolute geniuses. You know, some of the the ideas they came up with. So my favorite example is that Obelix dog in the original French version was called Ed feasts, which means obsession. But the English translators called him dogmatics with an X at the end, which, you know, if anything, is an even better joke, right?

00;15;09;06 - 00;15;45;06

Sarah O'Connor

And so what the translators told me was that when you get it right, when you think of some clever way of translating something, it's an intensely satisfying job. But what's happened to them is that now, rather than translating from scratch, the agencies that sort of intermediate a lot of this work, they're taking the English subtitles, they're getting a machine to translate them, and then they're giving that machine translation to the human translators, and they're telling them, now, your job is to check this for accuracy, to tidy it up, to make it feel a bit, a bit better, a bit more human.

00;15;45;09 - 00;16;05;07

Sarah O'Connor

But that's that's quite a different job from the translators point of view for a few reasons. One is that they're now expected to do this at twice the pace, but for half the price. And so the job instantly kind of speeds up and feels a bit more intense. You know, you've got to really rattle through this now in order to maintain your weekly or monthly income as a, as a freelancer.

00;16;05;07 - 00;16;30;00

Sarah O'Connor

But also that is quite difficult to do actually. Like if you care about quality and accuracy, which, you know, these are professionals, so they do care about that. To check a translation that's been given to you against an original text is actually kind of quite, quite arduous, you know, to keep going between those two texts and you don't get into the same sort of creative flow status when you're actually doing that translation from scratch.

00;16;30;01 - 00;16;52;00

Sarah O'Connor

I mean, to my shame, I don't actually speak any other languages, but I'm sure a lot of your listeners do, so they might resonate with this a bit more. But yeah, apparently you can get into quite a pleasant flow state when you're doing this from scratch, but doing it this other way is kind of cognitively more uncomfortable. And one of my interviewees, you know, he started out in life, he's from the Czech Republic.

00;16;52;00 - 00;17;12;19

Sarah O'Connor

He started out working in a factory, you know, windows and doors factory. And what he said was that this job that he used to love, that used to feel creative and enjoyable, had sort of been stripped of those creative bits and had been sped up, but also sort of routinized in this in a way, and that it felt more like a production line job than the job that he used to love.

00;17;12;21 - 00;17;42;15

Sarah O'Connor

And and this feels quite sad to me because this is, I think, not what any of us would want, really. You know, I think there's a sort of an expectation that whether it's the utopian version of the future or the dystopian version, one kind of consistent thing between those is that there'll be less work somehow, and whether that's sort of spread out evenly, and we're all doing less and doing like a four day week, or it spread out in a kind of problematic way, and lots of people have nothing to do.

00;17;42;18 - 00;18;07;09

Sarah O'Connor

I don't think many people have anticipated that we might actually still be quite busy, but not necessarily in a way that that feels good to us. And so those are a couple of quite sort of gloomy examples for you. But I did also find some much more positive examples, and I'm happy to talk about them to and why why things are going well in some places and badly in others.

00;18;07;12 - 00;18;35;20

Geoff Nielson

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00;18;35;20 - 00;19;06;18

Geoff Nielson

From AI strategy to cybersecurity to vendor negotiation, Infotech has you covered. Check it out at the link below and don't forget to like and subscribe. So it's interesting. And you know, in my reading of it, there's definitely a flavor of of dystopia there, I guess, because when I hear those stories, you know, I certainly don't hear about jobs that now are, you know, hot air value or, you know, more, more rewarding in some way.

00;19;06;19 - 00;19;39;13

Geoff Nielson

I, you know, have these sketches of basically humans being traded. Sort of I have these sketches of humans being treated as dexterous, moist robots or machines. Right. Like it's all it's all machines. But some of those machines happen to be human laborers. And like that on some level is deeply depressing. And you you used to phrase a couple of times that I really liked, which was was more human like, how can we make work more human, which may not be Amazon's top priority or any of the employer's top priorities.

00;19;39;13 - 00;19;56;12

Geoff Nielson

But I'm curious, you know, from your perspective, you said those were some of the gloomier stories. What are some of the more optimistic stories? What are some of the examples you saw of this being done better, and what do those have in common?

00;19;56;14 - 00;20;23;14

Sarah O'Connor

Yeah. So I'll give you a couple, I guess from the white collar world, I would say that software developers are probably an example of people who are feeling much more positive about this transformation. I mean, not not all of them. It has been a kind of massively disorientating time, I think, for software developers. But, you know, you might have imagined that it could have gone quite similarly if a software developers and translators.

00;20;23;16 - 00;20;47;09

Sarah O'Connor

Right. Because for both of these professions, one core, really core part of their skill set for translators is translating things between two languages. And for software developers, it's being able to write code. Suddenly now machines are pretty good at doing it. But for the software developers, it seems to have been going differently in the sense that for the translators, I think the part of the job that they really loved was the act of translation.

00;20;47;09 - 00;21;07;12

Sarah O'Connor

Whereas for a lot of the software developers that I spoke to and, and my brother is a software developer and my dad is a software developer, so there's kind of slightly is like runs in the family for them, like sitting down and physically writing out the code was more of a means to an end, and the end was to solve cool problems with computers.

00;21;07;13 - 00;21;33;12

Sarah O'Connor

Right? And so if you have like this new tool which enables you to solve more problems by actually writing the code so that you can kind of go up a level of abstraction and think a bit more about what are the different problems. Talk more to your customers or your clients or your employer about what needs to be solved and how that what we are kind of seeing there is rather than a de skilling, we're seeing a sort of an upskilling, I think.

00;21;33;12 - 00;21;57;04

Sarah O'Connor

So, you know, and you can see that even in the labor market data that the the demand for senior software developers, people who have a lot of experience, you now have taste and judgment and the ability to manage their kind of doing quite well in this new world, you know, because now some of these new tools, they're sort of like power tools, but you need to know how to use them responsibly and wisely.

00;21;57;05 - 00;22;15;26

Sarah O'Connor

And so if you are in that lucky position of already being quite ensconced in your profession, then you can just use this stuff to be much more productive and to do many more things. And now this is not like an entirely positive story, because what a lot of those people are also saying is they're kind of burning out to.

00;22;15;27 - 00;22;47;02

Sarah O'Connor

So similarly, they're not finding that they're getting all of their programing done by lunchtime and then lying in the battle afternoon. You know, because it turns out that white collar work just expands to fill the time available often, which I think is something we're all sort of familiar with from our own jobs. But software is the sort of thing where actually there's probably been a lot of kind of latent demand for software that hasn't been met because it's quite expensive to hire software developers, and whereas suddenly it's much, much cheaper.

00;22;47;02 - 00;23;11;20

Sarah O'Connor

You can, you know, each software developer can do more stuff. So an economist would call this Jevons paradox that sometimes if the price of something goes down a lot, demand for it simply goes up. And I think that's sort of what we're seeing in software. So that means that these, these these guys are actually incredibly busy. And because you can do more stuff, it sort of it resets expectations of what is natural or what is possible.

00;23;11;20 - 00;23;27;14

Sarah O'Connor

And you know, I think at the moment a lot of that is driven by the software guys and that they're sort of exhilarated and they're having fun. You know, my my brother, who he now sort of controls, like a swarm of AI agents who are sort of doing his bidding. He says he feels a bit like he's superhuman.

00;23;27;15 - 00;23;46;06

Sarah O'Connor

You know, he can just do so much stuff. So it is it is exhilarating and satisfying, but it can also be quite cognitively exhausting in its own way. And another example I would give, and this is from the sort of the blue collar world, but I think is an interesting counterpoint to that. That Amazon warehouse is the Swedish mine that I mentioned at the start.

00;23;46;06 - 00;24;12;23

Sarah O'Connor

So this mine now the job of being a miner there has completely transformed. So it used to be that the miners would drive around a kilometer and a half below the surface of the ground. This is like way up in the north of Sweden. There's sort of pine forests, there's reindeers, and then you go down. I went down right to the bottom, and at the bottom it's like it's dark and it's humid and it's really claustrophobic and it's kind of there's a lot of mist or steam in the air.

00;24;12;23 - 00;24;32;16

Sarah O'Connor

So it feels really horrible to me. It felt horrible. And even the miners, you know, I don't think love being in these mine shafts. Right. And it used to be that they would drive these vehicles around that would do the all the jobs that needed to be doing. Now they're self-driving vehicles. And so the miners are sitting in a control room and they're looking at a kind of bank of screens.

00;24;32;16 - 00;24;55;21

Sarah O'Connor

So they're watching what the self-driving vehicles doing. They've got a pedal, they've got a joystick, so they can take over remotely if they need to. If the self-driving vehicles kind of get into trouble or get confused or get stuck. But for the most part, you know, their job is now really different. And I wondered whether this would to them feel like an upgrade.

00;24;55;29 - 00;25;16;10

Sarah O'Connor

And actually, I think it did. You know, I interviewed one of the miners who was like, look, it's it's quieter, it's safer. I'm now I'm listening to the ice hockey on the radio, or I'm listening to Spotify because we've got Wi-Fi down here in this mine now, and this is definitely a better job. And I think there are a few reasons why they feel good about it.

00;25;16;10 - 00;25;40;16

Sarah O'Connor

And one goes to, I think, a sense of control. So for the Amazon workers, it was almost like they were have you heard this term human in the loop. It's used in sort of lots of different contexts. And I think for the Amazon workers, they were humans in in the loop of a pretty like automated system in which everything was running to a kind of an intense timetable, and they just had to keep up.

00;25;40;16 - 00;25;53;21

Sarah O'Connor

But it felt to them like the robots were really the ones that were in charge and were setting the pace. And you can hear that just in the language they use. You know, one of them said to me, you know, the robots are moving and you've got to move with the robots. You know, these robots are so fast, they're killing us.

00;25;53;22 - 00;26;13;16

Sarah O'Connor

Whereas for the miners, the way they would talk about these self-driving vehicles was like, the vehicles are doing their bidding. So he would say, you know, I'm going to send it here. I'm going to send it there. It felt much more that they were in control and that this was a tool that they were using. Whereas for the Amazon workers, it felt more as if they themselves had become a tool.

00;26;13;17 - 00;26;34;23

Sarah O'Connor

You know, that they were they were, as you put it, they kind of the fleshy appendages that the robots didn't quite have yet. And that's a that's like a psychological difference, but I think quite a profound one. And and then the other difference is that, you know, in that mind they have they have sort of very Swedish institutional arrangements.

00;26;34;24 - 00;27;00;27

Sarah O'Connor

And, you know, I don't know how much you know about Sweden, but trade unions are very powerful. They're both at a sexual level, but also at an individual company level. And so what what has to happen is something called code determination. So when an employer brings in new technology to a workplace, that is going to quite profoundly change the way work gets done, it's the law that they have to sit down with the workers and go over it first.

00;27;01;00 - 00;27;27;04

Sarah O'Connor

And this isn't like a kind of management still has the prerogative. Management ultimately still has the final say. It is their rights to do stuff, but they do have to at least talk about it first. And in this mine, you know, I had imagined that that could be a sort of recipe for sclerosis. So in the UK, where I'm from, unions and employers have quite a kind of antagonistic relationship for the most part.

00;27;27;04 - 00;27;51;22

Sarah O'Connor

And unions often see their job as like fighting management in some way. And but in this Swedish mine and I think in a lot of Swedish workplaces, they have such a lot of kind of muscle memory of how to do this, of how to negotiate technological change, that these new machines and these new AI systems are being negotiated in a way that they are already very familiar with.

00;27;51;29 - 00;28;13;13

Sarah O'Connor

And and I think both sides sort of recognize that each other has a right to be at that table and to to talk it through. And there were lots of interesting ways in which they had figured out things that could otherwise have been difficulties. So one of the tensions when they wanted to bring in the self-driving trucks was, where should the miners be now?

00;28;13;15 - 00;28;35;29

Sarah O'Connor

You know, actually, do the miners even need to be underground? Surely they can be on the surface. And that's what the employer wanted. They were like, the control room should be on the surface. That is most efficient. It makes no sense. It's safer. Whatever. But the miners wanted to stay underground. They didn't want to stay on the surface for a very good reason, which is that you get paid more if you work underground in the Swedish economy.

00;28;35;29 - 00;29;01;13

Sarah O'Connor

And who's going to agree to something that involves a pay cut? Right. And so they talked it through and they came to what one of the union leaders described to me as a very Swedish compromise, which was that they put the control room halfway down the mine. So there's a kind of halfway point where there's a canteen, and now you walk through the canteen and you get to the control room and like from the outside, you might look at that and say, that's weird and inefficient.

00;29;01;15 - 00;29;31;00

Sarah O'Connor

You know, that makes no sense. But actually, I would argue to you that that's more efficient because what it enabled them to do was just to move forward with the whole idea, you know, that otherwise they might have ended up stuck in this place where the miners were resisting because they didn't want to get the pay cut, and the employer was insisting and they would have got nowhere, or they would have ended up in some kind of industrial strife, whereas actually doing something that seems a bit odd enabled them to just get that technology in and get it working.

00;29;31;03 - 00;30;03;01

Sarah O'Connor

And so, yeah, and then I guess the other thing is that because the Swedish miners have union members on the board, it means that they have access to a lot of information about what is truly happening with the company. And my sense as a journalist at the feet is that when I report on companies where things are going wrong between employers and workers, what's often part of the problem is like a complete breakdown of trust, which is linked to a kind of lack of information about what's happening.

00;30;03;03 - 00;30;24;23

Sarah O'Connor

Whereas I think because the the Swedish Union have seats on the board, they were well aware that actually for this mind to continue to operate, for them to keep digging down further, they had to find a way to do it more cost effectively, and that the alternative would have been to just stop digging. And at that point, no one has a job anymore.

00;30;24;23 - 00;30;44;16

Sarah O'Connor

And so everyone is aware that there is a good kind of business rationale for doing this, and they have some shared interest in making it work, whereas, you know, you could have imagined a scenario where that information was lacking. And the miners sort of suspected that this was a pretext for something that was just trying to kind of get rid of them entirely.

00;30;44;16 - 00;30;48;24

Sarah O'Connor

So, yeah, there were lots of ways in which.

00;30;48;27 - 00;31;09;28

Sarah O'Connor

This enabled things to go better. But I think the key is like, who who gets a seat at the table when these decisions get made? You know, who has the right to to have their say. And is it possible to to kind of manage these technological transitions in a way that doesn't kind of degrade some of the trust that exists in the workplace already?

00;31;10;01 - 00;31;32;24

Geoff Nielson

So I'm going to I'm going to push you a little bit to answer the question you just posed, because I think it's a it's an incredibly important question. And it's so interesting hearing about this, this Swedish model, because I'm sure where you are in the UK, and certainly with my experience across America and Canada, that's just not my experience with unions or the kind of environment they're operating in or the outcomes that you get.

00;31;32;24 - 00;31;59;15

Geoff Nielson

So. So I am curious, Sarah, what your impression was walking away from the mine and seeing the solution that they had come up with, the, I guess, the framework or the governance that had gotten them there. And, you know, to ask your question back to you, who should have a seat at the table and how should you best go about coming up with some of these, you know, job changing or function changing decisions?

00;31;59;17 - 00;32;27;14

Sarah O'Connor

I mean, I think the answer is that everyone should have a seat at the table. And the question is, how do you do that in a way that doesn't lead to chaos or sclerosis? Right. And you know, what I was sort of wary of doing was concluding in this, well, you know, Britain and Canada and the US and all these other countries should find a time machine and, you know, reinvent 200 years of industrial history in order to have the Swedish model, because, like, clearly that's not going to happen.

00;32;27;15 - 00;33;03;23

Sarah O'Connor

Like we all start from where we are, and most of us do not start from the traditions of Swedish collective bargaining. So, you know, you have to be realistic about that. But, you know, all of that said, I think that there were some lessons that managers from all kinds of different companies could absorb. And one of them, I think, is that, you know, as I said, giving people a seat at the table does not necessarily have to mean ceding the possibility of getting stuff done, and that, in fact, it can do the opposite.

00;33;03;25 - 00;33;29;12

Sarah O'Connor

And, you know, we're already seeing a lot of employers are getting kind of frustrated about AI adoption levels in their companies, and they're sort of banging their heads against the table and saying, why? Why are more people not adopting these tools faster? And, you know, when you look in the details, often the reason is that people are really suspicious about what their employers are planning in the long run, or they simply have found that the tools don't work very well for the job at hand.

00;33;29;15 - 00;34;03;25

Sarah O'Connor

And and I think that is also quite an important point about giving more people a seat at the table, is that actually you are best placed to know how your job works and which tools would be useful and would not be useful, and being sort of pressured to use a set of tools in a way that, you know, fundamentally doesn't work very well, it looks as if it will be faster, but creates a bottleneck somewhere else in the process, which means that in fact, it's slower because you've got to find five more people to review it or whatever it might be that the people who are doing the work are actually best placed to tell

00;34;03;25 - 00;34;23;06

Sarah O'Connor

you how to make it more efficient. And so if you can create some kind of forum or environment in which people feel able to talk about that, then things do often go better. And then, you know, the other lesson I think from that, from that experience, was that you don't always have to take technology as it's given to you.

00;34;23;06 - 00;34;43;10

Sarah O'Connor

So, you know, another interesting example that the the Swedish managers gave to me was that they once they had WiFi working underground, it became clear to them that they could introduce a kind of real time positioning system so that they could know where all the miners were at all times. And, you know, from a safety point of view, this is obviously a good idea.

00;34;43;10 - 00;35;06;23

Sarah O'Connor

But when they sat down to negotiate over it, what they realized was that some of the workers were all in favor of this because they too could see the safety advantages. But some of them were really nervous and skeptical because they were worried that it would have a secondary purpose of enabling a kind of surveillance managerial system, which wasn't the culture there, and that they didn't want to become the culture.

00;35;06;24 - 00;35;22;17

Sarah O'Connor

And, you know, one of them literally said, we don't want to be treated like Amazon workers here. We don't want you timing. How long we spend in the bathroom like that is not what we want. And we're worried that this technology, even if that's not why you're doing it, that over time it could become used for something like that.

00;35;22;19 - 00;35;41;07

Sarah O'Connor

And so what they did was they they went back to the technology vendor, the company that had made this software system, and they said, can we pay you to make an adjustment for us so that rather than seeing the names of everyone, we have a kind of anonymization feature so we can see where everybody is, but not who they are.

00;35;41;08 - 00;36;01;03

Sarah O'Connor

Everybody has these anonymized number tags. And and we have agreed in advance that there will be certain situations where we can do that data if there's an emergency or if there's been an accident that needs to be investigated, and both the union and the employer have passwords and they can put them in together in order to anonymize it.

00;36;01;06 - 00;36;27;11

Sarah O'Connor

And this, I thought, was quite a good solution because it fundamentally allowed them to reap the kind of the safety benefits, but without losing something that was sort of quite precious, but also a bit invisible, which was the sense that actually people respected and trusted each other in the workplace. And the Swedish employer, I think, had never really wanted to have a micromanaging system that wasn't their intention from the start, and maybe they would never have even used it for that.

00;36;27;11 - 00;36;55;29

Sarah O'Connor

But in a sense, that doesn't matter, because if that's what people start to suspect, then it already changes the kind of the culture. And the reason I tell that story is that, you know, it's just a reminder that it is. You don't have to take everything out of the box and just deploy it, you know, and often these, these systems, these AI models, whatever they are, the tools, they've been designed by people who don't know your own company necessarily, who don't know exactly how it works or what would work for you.

00;36;55;29 - 00;37;33;13

Sarah O'Connor

And it is possible to kind of question the premise of it and say, do we want all of this? Would we like this to be different? You know, right now we're starting to see that some kind of forward thinking companies are experimenting with getting kind of cheaper AI models and kind of open source or open weight models, and then fine tuning them themselves, often using their own employees who are kind of experts in their jobs in order to actually create tools that are more useful for their own kind of corporate context, rather than these kind of big black box frontier models that they're getting from places like opener, AI or anthropic.

00;37;33;13 - 00;37;48;26

Sarah O'Connor

And I think over time we might see more of that, where actually you're seeing people crafting tools that are more responsive to what their needs actually are. And if you're going to do that, then you really need your employees, you know, because they're the ones that are going to train it. And so you need them to be on board with this.

00;37;48;26 - 00;37;56;26

Sarah O'Connor

And the only way to do that is to make them feel that they are. Yeah, that they're a part of it somehow and not having it sort of foisted upon them. I think.

00;37;56;28 - 00;38;22;22

Geoff Nielson

I really like that insight. And, you know, the approach there and the way to do it. There's an implication there, though, that I want to pick out a little bit and sort of devil's advocate because there's there's implications there that that is better, that having anonymized workers is better, that the Amazon approach is bad, and that we lose something by just breaking people down into, you know, these small mechanical tasks that that is worth pushing against.

00;38;22;22 - 00;38;49;00

Geoff Nielson

Because I'm sure, I'm sure there are business leaders. I'm sure there are listeners to this that say, like, why that is, that's going to be most, you know, optimal, most efficient. And that's the way we should run our business versus listening to the employees. And it reminded me, Sarah, actually, of a story I've heard of yours that you haven't told, which is the the story of the nurses and of the sort of the elder care and the health care.

00;38;49;02 - 00;39;06;02

Geoff Nielson

Can you talk a little bit about how in that space, you know, you've come across and nurses have come across multiple care models, one that's more mechanical, I guess, and one that's more human. And the insights you got out of that.

00;39;06;05 - 00;39;29;15

Sarah O'Connor

Yeah. I mean, I think that you're, you know, you're right to kind of question that premise. And clearly there are different kind of valid ways of running a business that will might give you kind of similar outcomes in the short run. But I would argue that over the long run, creating work that workers don't like to do is going to is going to cost you in some way or another.

00;39;29;21 - 00;39;49;29

Sarah O'Connor

And it might be that you can kind of continue to just bring more people in and live with like a relatively high labor turnover that works in some sectors but doesn't work in others. So nursing is a is a good example of where I think it really doesn't work to do that kind of tailoring stick, you know, break, break things down into their constituent chunks.

00;39;50;01 - 00;40;07;01

Sarah O'Connor

But that is how how it works in a lot of places. So, you know, in the UK, for example, we have domiciliary care workers who will go from, you know, from one house to another and they will go and they will kind of help people who need help in their own homes, probably because they're elderly or very unwell.

00;40;07;03 - 00;40;28;16

Sarah O'Connor

The system here has been we've sort of attempted to do this in an efficient way, whereby that the commissioning of these services is often done by local authorities, like local governments, who are fundamentally on the hook to pay for a lot of it. And they they kind of like auction off almost all of the tasks to a whole range of different private providers who then sort of bid for them.

00;40;28;20 - 00;40;46;13

Sarah O'Connor

And while that does push down the cost, what it means is that you have, you know, if you're an elderly person and you're relying on some domiciliary care, some carers to come into your home, you might have sort of 5 or 10 different people turning up in a week. You know, nobody gets to know who you are or what your issues are.

00;40;46;17 - 00;41;04;26

Sarah O'Connor

Each of those people might come in and they've only got ten minutes to do what they need to do, or 15 minutes. And so a that doesn't lead to a satisfying job because as as someone who has gone into a caring profession, you actually fundamentally have some empathy and you want to do a good job and to look after people.

00;41;04;26 - 00;41;22;21

Sarah O'Connor

And when you're rushing in for ten minutes and you're on the clock and you've got to give someone a shower and you don't have time to listen to them when they want to talk about the fact they're feeling lonely or whatever, that that doesn't feel good to you. And but also it doesn't really work well as a care model because things get missed.

00;41;22;23 - 00;41;40;25

Sarah O'Connor

You know, when you've got 5 or 10 different people coming in, nobody really gets to know the patient and what's happening. And so in the in the example that I wrote about in the book in the Netherlands, I went to see some nurses who work for a company called birdsong, who have basically tried to turn this whole efficiency model on its head.

00;41;40;25 - 00;42;10;02

Sarah O'Connor

And so what they do there is they for a start, there are no managers in this company, really. It's a very kind of flat company. What you have instead is sort of autonomous teams of nurses and they are higher qualified. So rather than breaking down all of the different tasks that might go into caring for a person and getting a qualified nurse to do the more medical tasks, and then getting someone who has no qualifications to go in and make them a sandwich, or to give them a shower.

00;42;10;02 - 00;42;32;11

Sarah O'Connor

In this model, basically, the well qualified nurses do the whole thing and they are able to form like long term relationships with their clients. And they work in these small teams like maybe 6 to 10 nurses in one neighborhood, and they figure out between themselves how to do the job, so they figure out where their office is going to be, and they come up with the rotor themselves.

00;42;32;11 - 00;43;00;16

Sarah O'Connor

And if they need to hire someone new, then the team does that together. So it's like it's quite a radically different system. And, you know, it actually doesn't work for everyone. A lot of people can't cope with that level of responsibility and autonomy. Like it's definitely not for everyone, but for the nurses who are doing it and who like it, it creates a very different outcome because, you know, you're getting to know a person rather than seeing them as like a series of tasks that you have to complete.

00;43;00;16 - 00;43;30;26

Sarah O'Connor

And that actually, it turns out, is more efficient. Because when you have well qualified people who are forming these trusting relationships with clients, it turns out the clients need less care overall. So what birth has found is that they are getting much higher sort of satisfaction ratings from their clients, but they have to deliver far fewer hours of care in order to do the same level of provide the same level of kind of care and service.

00;43;30;27 - 00;43;47;04

Sarah O'Connor

And for the nurses, it means that, you know, one of the nurses that I spent some time with, I said to her, like, do you not feel sometimes that you've got all these qualifications and medical knowledge? Do you not feel that it's like a bit of a waste of your time to go in and make someone a sandwich, you know, and give them a wash?

00;43;47;04 - 00;44;04;23

Sarah O'Connor

And she was like, well, no, because you're not just going for the sandwich, you know, you're going to check how she is. You're going to have a look at the environment. And, you know, she said that it might be that you if you're going in every day, you notice that three days in a run, that sandwich is barely eaten and it's in the bin.

00;44;04;23 - 00;44;21;08

Sarah O'Connor

And if you've been there every day, then you can notice that and you can say, hey, you know what's going on? Why is the why are you not eating your sandwich? And she said, it might be that that person is dying because the appetite is one of the first things to go, or it might be a sign of a certain kind of cancer.

00;44;21;08 - 00;44;38;28

Sarah O'Connor

Or it might be that actually, she hates that kind of cheese, and you didn't know that. But if you have a different person going in each day, nobody's going to spot that. And so a lot of a lot of problems get missed in this system that looks more efficient, where you're deploying lots of people to do lots of different tasks in a way that don't.

00;44;38;28 - 00;45;06;23

Sarah O'Connor

When you have the opportunity to have one kind of better paid professionals forming an actual relationship. So, you know, nursing is a very different profession to running a warehouse. So I'm not claiming that the same things, the same lessons apply right across the board. But I do think that, yeah, we kind of we often prioritize this idea of efficiency in the short run without noticing that sometimes that is wildly less efficient in the long run.

00;45;06;26 - 00;45;32;20

Geoff Nielson

Well, that's that's exactly it. And that's what's really frustrated me is it seems like there's been this push to try to transform nursing into a warehouse job that's, you know, and I was chuckling to myself because you said like, oh, these autonomous nursing teams and the way you describe it and tell me if you disagree, like, sure, we can we can describe it as radical based on what people tend to be doing now.

00;45;32;22 - 00;46;02;00

Geoff Nielson

But I have to imagine it's not all that different from what nursing looks like 100 years ago. Like, I feel like this is what has always worked, and then we've fat like, I don't know, we've tried to warehouse ifit it's gone. It's gone terribly for the nurses and for the people receiving care. And, you know, we don't we don't need to get too deep into this, but it just feels like in basically every advanced economy in the world, health care has completely gone to shit.

00;46;02;07 - 00;46;25;28

Geoff Nielson

And I'm sure you've got some horror stories about the NHS. You know, Canada, the US, you name it. Like everyone is complaining that health care is getting more and more expensive and it's getting worse and worse. And I don't know, I'm just curious if you if you feel like there is some lessons to be learned there to to try and undo, I don't know, to try and reverse course on the trajectory that we, we found ourselves in.

00;46;25;28 - 00;46;30;12

Geoff Nielson

And it feels like, at least to me, we're going in the wrong direction.

00;46;30;14 - 00;46;51;26

Sarah O'Connor

Yeah. Well, the guy who founded this company, he himself had been a community nurse back in the day in the Netherlands, when this was the way it was always done. So you're exactly right. You know, this is, in a way, going back to the future. And he had believed that this was a really good way of running things, you know, being based in the neighborhood, getting to know the clients.

00;46;51;28 - 00;47;12;14

Sarah O'Connor

And he had ended up working for one of the big kind of health care companies in the Netherlands. And he watched. He was in a managerial role. He watched as the layers of bureaucracy increased and the kind of the task and time model got introduced. And he could see that actually it was becoming more expensive and less efficient.

00;47;12;14 - 00;47;29;22

Sarah O'Connor

And that was why in the end, he left and tried to kind of create this completely new model. And one of the sort of questions that I had in my head while I was there, which I think is the question that you're asking me now, was like, if this if this is so good and it seems as if it is, why isn't everyone doing it?

00;47;29;23 - 00;47;54;26

Sarah O'Connor

You know, and actually, a lot of people have been sort of entranced by this model. And so Josh, who is the guy who founded it, has been invited to give speeches. And like lots of different countries, Harvard Business School has gone and done like one of their famous case studies about it. And everyone likes the idea in principle, but has struggled to replicate it in their own countries.

00;47;54;26 - 00;48;21;17

Sarah O'Connor

And that's definitely true for the UK, where I live. And I think it's partly sort of institutional. So it depends a lot on the kind of the wider institutions that exist in a particular healthcare system, and it's not always easy to plug in this kind of model. It depends a lot on funding. So in the Netherlands there's like a health insurance model, whereas in the UK, as you know, we have the National Health Service.

00;48;21;19 - 00;48;45;17

Sarah O'Connor

And also I think it's it's it's sort of cultural, you know, it's really hard when you've become used to doing something in quite a kind of structured, formalized way to suddenly completely break out of that. And then I think the final reason I asked Jennifer, who was the nurse in the Netherlands, who I spent some time with, like, why do you think more people aren't doing this?

00;48;45;17 - 00;49;17;08

Sarah O'Connor

And she said, well, because, you know, a lot of managers are not going to vote for their jobs to disappear. You know, there are no managers in that company. There's no layers of management. But the people who would have to make those decisions to get rid of those managers are indeed the managers themselves. And so there's just a kind of a sort of a stasis that tends to exist, I think once a once the structure exists and once everyone has their own little place within it, it's very hard to become radical about how to how to do things differently.

00;49;17;10 - 00;49;42;03

Geoff Nielson

I think that's well said, if a bit depressing. But, you know, hopefully, hopefully we can have more leaders who have the courage to implement something like that. And, you know, the other piece you didn't mention that was on my mind as well is just the like the tyranny of metrics and what you're measuring and how I can see a world where if you're measuring everything like a warehouse and it's these little bits of efficiency, you feel like, oh, I've got the right model.

00;49;42;03 - 00;49;56;07

Geoff Nielson

But you know, if there's, as you said, longer time horizons, things that are maybe invisible in that world, you end up with something that's suboptimal for everybody.

00;49;56;09 - 00;50;18;11

Sarah O'Connor

Yeah. And I mean, you know, we've been talking about this at the level of like companies or sectors, right. But I think that the same thing is probably true at the level of us as as individuals. It feels as if we've become obsessed with this idea of productivity, of becoming more productive, of optimizing ourselves in some way, and almost as if we are machines, you know?

00;50;18;12 - 00;50;40;20

Sarah O'Connor

And what we need to do is to kind of fine tune ourselves. And again, you know, I feel like that is a real misunderstanding of who we are and risks something being lost, you know, and you see that with, you know, the kind of the watchers that we all wear that are tracking our steps and our heart rate and how well we slept to, you know, the books that we buy.

00;50;40;21 - 00;50;59;12

Sarah O'Connor

You know, I even like books that are about how to rest and how to relax. Like, I don't know if you've noticed, but often there subtitles are something about why this would help you be more productive in the long run. And there's one that's called rest. There's actually a very good book that the subtitle is why you get more done when you do less.

00;50;59;15 - 00;51;17;03

Sarah O'Connor

You know, it's like we can't allow ourselves to just do less for the sake of doing less. And even, you know, when we're sort of when we when we're kind of resisting this and it all feels too much if you listen to the language use, you know, we say things like, I'm burned out or I need to disconnect or I need to switch off.

00;51;17;04 - 00;51;52;07

Sarah O'Connor

You know, all of these phrases or phrases that you would use about machines, not about like fleshy mammals that are composed mostly of water. They don't burn out, they just need a rest. And so, yeah, I think we've sort of slightly started to confuse ourselves with our own tools in a way that is not necessarily helpful, you know, and like, I am not a kind of a disbeliever in productivity or economic growth, like I'm a Financial Times journalist, like here in the UK, we've just had a decade of no productivity growth and no economic growth.

00;51;52;07 - 00;52;12;09

Sarah O'Connor

And let me tell you, it hasn't been much fun. Are like median wages are like lagging behind a lot of comparable countries. Now. People are not particularly happy. We can't seem to keep a prime minister for longer than a couple of years because everyone's fed up. So, you know, economic growth is good. And the way you achieve that is by achieving greater productivity.

00;52;12;09 - 00;52;41;02

Sarah O'Connor

But that, you know, the way productivity happens on a macro level is quite different to what we often think about. You know, it's not each person becoming 10% more productive in their day to day jobs. It's much more like we invent whole new services and goods. You know, we use these new AI tools to create new markets or do things completely differently, rather than we all just need to kind of speed up and squeeze an extra 10% of effort out of ourselves.

00;52;41;02 - 00;52;51;02

Sarah O'Connor

And I think, you know, there's a there's a risk that we often conflate one with the other in a way that isn't helpful to us as individuals or us as as an economy.

00;52;51;04 - 00;53;18;18

Geoff Nielson

I was speaking with a future of work expert from Microsoft a month or two ago, and he was talking about, he used the phrase I really like, depressingly, the invasion of work and how it feels like work has kind of invaded our whole lives, and people are chasing that, oh, how do I just get 10% more done? Or, you know, oh, now that I have, you know, AI tools, people expect me to be able to do more and it just sort of, you know, chases us and that becomes the the battle we're going to fight.

00;53;18;18 - 00;53;44;08

Geoff Nielson

And I agree, it doesn't feel like it's a road that necessarily leads us anywhere. There's there's something maybe adjacent. I wanted to talk about, though, Sarah, which is one of the phrases you used in the book that had sort of the most profound and resonant impact on me, which is you said we've lost faith in ourselves. That was one of the, I think, kind of concluding sentiments you had.

00;53;44;08 - 00;53;55;14

Geoff Nielson

And I was wondering if you could, you know, unpack that a little bit. What does that mean? What led you to kind of conclude that? And, you know, what do we what do we do about it?

00;53;55;17 - 00;54;19;17

Sarah O'Connor

Yeah, I think this is a sort of feeling that I had at various points along this journey of reporting and writing this book, and I think it comes from being bombarded by these messages about the superiority of machines. You know that AI is already better than most people at most things and is only going to get better still, you know?

00;54;19;18 - 00;54;39;23

Sarah O'Connor

And not only will it be better at your job, but it might be better at expressing empathy or forming relationships or anything that you could imagine. There's going to be a machine that will be able to do it better. And, you know, often when people are selling these systems, they compare them to what they see as the limitations of humans.

00;54;39;24 - 00;55;14;19

Sarah O'Connor

Right? So, you know, when I was writing about the recruitment world, there would be endless kind of marketing spiel from the companies that are creating these sort of AI recruitment tools that say, humans are so biased, you know, and they are so unreliable and they're so inconsistent that actually we need to find machines that will be able to be much fairer and all the rest of it or even, you know, I read a paper recently by some academics which were arguing that AI empathy is actually in many ways superior to human empathy because it's indefatigable.

00;55;14;21 - 00;55;38;05

Sarah O'Connor

You know, an AI system will never get tired of expressing empathy towards you. And I would say that actually, that is a fundamentally different thing, you know, and that to to compare ourselves to these machines and then find ourselves wanting is to misunderstand the nature of who we are. Like, actually, the fact that you can.

00;55;38;08 - 00;56;00;04

Sarah O'Connor

Lose empathy eventually, that you cannot express it permanently and not feel something for someone all the time. That's not like a limitation of empathy, that's just a feature of it. But that's because we are humans. And actually to put yourself in someone else's shoes is something that is quite taxing. And you know, what the machines are doing is not empathy is giving an illusion of it.

00;56;00;04 - 00;56;28;16

Sarah O'Connor

And yes, they can do that much more efficiently and 24 over seven. But what I worry is that if we start to compare ourselves with these machines, we will see ourselves as lacking things that they have, rather than just seeing that we are fundamentally very, very different creatures, you know, and therefore we can respect and value what is good about ourselves and respect and value what is useful about machines.

00;56;28;16 - 00;56;48;23

Sarah O'Connor

But we don't need to think that they have to be the same thing. And actually, you know, one of the like conclusions that I had after doing this reporting is that in spite of what a lot of people in Silicon Valley say, I do not think it is true that machines are one day going to be able to do everything we can do, but better.

00;56;48;25 - 00;57;09;10

Sarah O'Connor

You know, I do not think that a machine will one day be able to sit as Jennifer, the nurse that I spent time with. She specializes in palliative care. You know, I do not think that a machine will be able to do what she does when someone is dying and sit next to them and hold their hand and let them know it's okay, now it's time to go.

00;57;09;13 - 00;57;25;00

Sarah O'Connor

Nor do I think they should, you know. And this is the the other thing that I think we've sort of lost a bit. Part of the way we've lost faith in ourselves is that we've we've started to ask a lot of questions that start with the word can and will, you know, like, can a machine do my job?

00;57;25;00 - 00;57;46;12

Sarah O'Connor

Will a machine do my job? Will. Will machines take away all the jobs? We're not asking questions that begin with the word should like should they do that? You know, what do we actually want from this technology? What do we want it to do? And and what areas do we think that actually they don't belong. And that's well within our rights and responsibility to decide, but only if we remember that we are both capable of that.

00;57;46;12 - 00;58;03;26

Sarah O'Connor

And, you know, we have to we have to kind of rise to those decisions. Now, I'm using the word we there. And a lot of people would say, well, hang on. There's it's easy to say we in the kind of abstract, but a lot of people have not very much power, and a few people have a lot of power, and they might not necessarily all have the same incentives.

00;58;03;27 - 00;58;38;08

Sarah O'Connor

And I think that's definitely true, but I think that there is a danger in allowing ourselves to believe that this is all just happening to us and that we have no power to shape it, you know, and the the massive kind of heterogeneity of stories that I encountered in in the process of writing this book, I think goes to that point that actually there are so many things that determine how technology will change the world and change the way we interact with the world and how we feel about our work, and what the technology itself can do is only one part of that.

00;58;38;10 - 00;58;56;10

Sarah O'Connor

All the other parts are things like what? What managerial decisions get made, who has a seat at the table? What is the balance of power in the workplace? What regulations might we want to put in place? How do consumers feel about this? What do consumers value and what do they absolutely hate and are not willing to pay money for?

00;58;56;10 - 00;59;18;21

Sarah O'Connor

And all of these are actually human things. And yes, not everyone has the same power. But certainly this is none of this stuff is just going to be determined by technology alone. And so I think, you know, developing more faith in ourselves, both as quite remarkable creatures that can do things that machines can't do, but also just remembering that actually, we're the protagonists of this story.

00;59;18;24 - 00;59;26;04

Sarah O'Connor

You know, the technology is not the protagonist. We are, I think, is going to be very fundamental to how the next sort of 10 or 20 years goes.

00;59;26;07 - 00;59;57;09

Geoff Nielson

It's it's a really important message, I think, and it sort of a sober reminder in a lot of ways. One of the one of the other nuggets I picked up that, you know, I think you were kind of hinting at there is this sort of I don't know if I want to call it managerial hubris, but at least like an inclination to adopt technology because of a concern that if you don't adopt it, there will be a negative, you know, social or, you know, business reaction like, oh, I'll be a Luddite.

00;59;57;10 - 01;00;07;17

Geoff Nielson

People will think that I'm not, you know, advanced enough. And to your point, it feels like that could be extremely dangerous and lead to a lot of bad decisions.

01;00;07;20 - 01;00;38;00

Sarah O'Connor

I mean, we're already seeing some of those in action, right? I mean, some companies that rushed to implement AI systems or to push their employees to use these tools before they were necessarily ready or good enough. There have been some really embarrassing snafus, you know, companies that have put out reports that are full of hallucinations, lawyers who've been like, called in front of judges to explain why they've sent in documents to the court that actually have completely made up cases in them.

01;00;38;00 - 01;01;04;00

Sarah O'Connor

And so, yeah, I think there is a natural human fear of being left behind. And I think that the AI companies have very much noticed that and played upon it. You know, FOMO is definitely real in the in the C-suite, just as it's real in, in any other kind of context. But, you know, anyone who is familiar with management literature will know that there is such a thing as a second mover advantage as well.

01;01;04;02 - 01;01;27;12

Sarah O'Connor

You know, it wasn't it wasn't Myspace that took over social media. In the end. It was it was Facebook. It wasn't Ask Jeeves. That was the Google of its bay. You know, it didn't last all that long. So, you know, I think there are plenty of good reasons to try and sort of keep a lid on that anxiety in order to be a bit more rational about what you do and how you do it.

01;01;27;12 - 01;01;50;27

Sarah O'Connor

And that doesn't necessarily mean like just having to be first. Obviously, sometimes there are first mover advantages. That's clearly true as well. But yeah, I mean this this sort of broader anxiety that I, you know, I can I can hear it, I hear it not only from business leaders but also from politicians sometimes of being scared of looking like your anti progress, your anti-technology.

01;01;50;29 - 01;02;14;21

Sarah O'Connor

And I think it's really interesting and it's so odd because we don't really do that with other categories of products. You know, like in my view, it's perfectly okay to say I am very much in favor of this use of AI, and I'm very much not in favor of that use. You know, I am firmly in favor of protein folding, but I do not think it's a good idea for AI to clone musicians.

01;02;14;21 - 01;02;39;07

Sarah O'Connor

And so there are no it's not possible for musicians to make a living anymore. And, you know, nobody sort of sits down and thinks, oh God, if I say that I don't like heroin, people will think that. I also don't like paracetamol. You know, that's not a kind of trap that we allow ourselves to be put into. But I think we do a little bit with technology, which I think we just need to kind of shake ourselves out of it, really.

01;02;39;08 - 01;02;59;21

Sarah O'Connor

There's, there's no good reason for it. And the Luddites, by the way, I think are kind of pretty much misunderstood because they that word is now sort of used as someone who's sort of just kind of reflexively anti-technology in all its forms, because they're sort of commodity and don't like it. But actually, the Luddites were not necessarily against new technology or machines.

01;02;59;21 - 01;03;29;01

Sarah O'Connor

They were against a very specific way in which some new machines were being used to do their work. And when they went into those factories to destroy the machines, they would only they were very kind of careful about which machines they destroyed and which ones they didn't. And they would only really destroy the ones that were making the particular kinds of products that were undercutting their own skills and which was, you know, quite rational in, in that moment, there wasn't really any other thing that they had that they could do.

01;03;29;02 - 01;03;45;16

Sarah O'Connor

So, yeah, I think that we could all do with being a bit more calm and rational and not so sort of frightened of being seen to be anti-technology. Yeah. Technology is not one thing.

01;03;45;18 - 01;04;06;12

Geoff Nielson

I think that's well said. What what gives you hope for the future of work, for the future of technology and how all of this plays out? One of the themes I noticed is sort of indecisive about whether or not you're an optimist, you know, like you have these these moments of sheer optimism and then these moments of pessimism.

01;04;06;12 - 01;04;10;11

Geoff Nielson

And so, you know, what gives you hope?

01;04;10;13 - 01;04;31;28

Sarah O'Connor

I think that's I think that's well observed. I think that's definitely true. You know, I and probably most people I would imagine right now kind of go through phases of feeling optimistic and feeling pessimistic and as if things are going in the wrong direction. But I think by the time it got to the end of writing that book, I felt more optimistic than when I started.

01;04;32;03 - 01;05;00;27

Sarah O'Connor

And that was really because of the people that I kind of met along the way. You know, I interviewed an awful lot of managers and workers, and what that brought home to me was that, you know, we have this tendency and I think it comes from looking at those sort of economic forecasts a bit too much. We have this tendency to sort of assume that people are like, just passive objects and they're going to be either swept away or they're going to benefit, you know, they'll be winners and they'll be losers.

01;05;00;27 - 01;05;17;00

Sarah O'Connor

And, you know, we as individuals just have to kind of wait and see which one we're going to be, you know, like just stand there with a lottery ticket in our hands and hope for the best. But actually, what happens when technology does enter your workplace and does start to change your work is that people respond to it.

01;05;17;00 - 01;05;41;14

Sarah O'Connor

People do things. You know, people are not passive about this at all. And everyone that I met was doing something to try and make sure that this transition went better for them. And, you know, whether that was joining a trade union and fighting for better conditions or pivoting the kind of work they did to move into a different area that was more likely to be enhanced by air than destroyed by it.

01;05;41;15 - 01;06;03;18

Sarah O'Connor

You know, whether that was thinking of whole new things to do. You know, I interviewed a young person who was really struggling to transition from doing his MBA in New York to getting a job in investment banking, because, as we all know, AI has kind of massively started to intermediate the recruitment process in a way that made it really hard for him to even get his face in front of a human being.

01;06;03;18 - 01;06;33;06

Sarah O'Connor

And he was like, well, do you know what? I'm going to use these AI tools to start my own company, and I'm going to come for their business one day. You know, there are all kinds of ways in which we have more agency than we sometimes sort of think that we do. And so, you know, I think that's why I ended up being more optimistic and that I thought that actually, of all of the sort of policy responses that are possible, I think the ones that will be most successful are things that enable people to find their own way through this.

01;06;33;06 - 01;07;06;06

Sarah O'Connor

So, you know, having safety nets that are robust enough that you feel able to leave a job that has become unpleasant or unsatisfying to you, having support for people to start their own businesses, which thanks to AI, is now much easier than before. You know, everything that basically makes it feel like this is something that we can navigate for ourselves, I think is going to be the way to go, because fundamentally, people do like people do find their own way through, and they don't really wait for other people to find solutions for them.

01;07;06;08 - 01;07;25;19

Sarah O'Connor

You know, people are remarkably adaptable, and I don't want that to be a kind of, oh, well, everything will be fine because people will just adapt. Like, I don't think that's the case, that we have to be very alert to the various risks and the, the, you know, the ways in which we can say yes and no, the different types of technological change.

01;07;25;19 - 01;07;33;00

Sarah O'Connor

But I do think that as human beings, we are really, really good at figuring it out.

01;07;33;02 - 01;07;33;24

Geoff Nielson

While said.

01;07;33;25 - 01;07;36;06

Sarah O'Connor

Did that leave you more optimistic? Were you not convinced?

01;07;36;07 - 01;08;07;07

Geoff Nielson

No. It did. I really appreciate that. And I think it's a great note of optimism for, I guess, the workers of the world. The very last question, though, Sarah, that I wanted to ask you was, how would you kind of frame that for business leaders or for technology leaders, the people who can maybe affect a little bit more change in organization when it comes to the future of work and, you know, technology adoption or use or lack of adoption, what message would you want to leave them with?

01;08;07;09 - 01;08;38;07

Sarah O'Connor

You know, I have a lot of sympathy for people in management positions right now. I was just recently in Cambridge talking to a whole bunch of senior managers, and I do not envy them because, you know, there are a lot of really difficult decisions to be made right now, some of them quite consequential. And also, you know, I think a lot of people are having to manage workforces that have some people who are profoundly enthusiastic about AI and about these new tools and, you know, all in and are trying to figure out new ways to do their jobs.

01;08;38;07 - 01;09;10;16

Sarah O'Connor

And then, you know, in the same workforce, you will have some people, inevitably, who kind of hate AI for one reason or another. Either they just don't think it's necessary or they have moral objections or environmental objections. And so managing a workforce that has such a kind of a riot of feelings, I think is really difficult, but I think the message that I would want to kind of leave them with is what we talked about before, which is, you know, if you want this to go well for your company, I think you're going to have to bring people with you.

01;09;10;16 - 01;09;53;05

Sarah O'Connor

And and I think it's important to think about how to use these tools to enrich the jobs that you have, rather than to accidentally strip them of something that might have actually been quite precious to people. Because once that happens, it's quite hard to come back from that sometimes. And I think the best way to avoid those dangers is really just to talk to people, you know, to find out how people are feeling, to give them the opportunity to experiment with these tools in some kind of sandboxed or guard veiled way, and so that people feel that they have some control over this.

01;09;53;06 - 01;10;14;27

Sarah O'Connor

I mean, really, my view in the end of all of the different workplaces that I went to was that the places where it was going better were the places where people felt they had some agency and control over how to use the tools, where to use the tools, what tools to use, could they shape the tools themselves? All of those things make people feel much more confident and optimistic about the future.

01;10;14;27 - 01;10;41;04

Sarah O'Connor

And I think that that is something that manages can do if they want to, and if they have the, the kind of the people skills, I guess to do that is not necessarily easy. And it can be tempting to think that it would be more efficient to just force something on people. But I think the lesson of some of the stories that I encountered was that there are definitely dangers to doing it that way.

01;10;41;07 - 01;11;00;09

Geoff Nielson

It makes complete sense to me, and I love the the lessons there, the sharing of the lessons. Sarah, I wanted to say such a big thank you, not just for coming onto the program today, but for actually doing the journalism, the research, going out and talking to people, for collecting these stories, for sharing them. It's fantastic, and I loved hearing about it.

01;11;00;09 - 01;11;02;00

Geoff Nielson

Thank you so much.

01;11;02;02 - 01;11;15;03

Sarah O'Connor

Oh thank you. I mean, I didn't write this in the book, but I do sort of hope to go to that point about there are some things that machines won't be able to do, and you sort of hope that, in a way, this book is a manifesto for the sort of journalism that machines won't be able to do.

01;11;15;04 - 01;11;33;00

Sarah O'Connor

You know, I don't think ChatGPT is going to put its comfy boots on and go down a mine in Sweden and talk to the miners about how it feels. And then, yeah, I hope that there will continue to be value. But on that kind of journalism, because it's yeah, it's great fun to do and I hope that it helps to enrich our understanding of the world a little bit.

01;11;33;01 - 01;11;44;01

Geoff Nielson

I'm glad you said that. It's it's real journalism. It's important journalism. And yeah, I am happy to be an advocate for it. And, you know, a megaphone for it.

01;11;44;03 - 01;11;47;18

Sarah O'Connor

Oh, thank you. Thank you for having me.

01;11;47;20 - 01;12;12;03

Geoff Nielson

Most viewers don't know this, but Digital Disruption is developed by Infotech Research Group, a leading advisor to technology leaders around the world. If that's not you, you don't need to care. So skip ahead and enjoy our content. But if you are a technology leader, Infotech helps IT teams get projects done faster, better, and at a lower cost. Infotech provides unlimited access to practical tools and expert guidance.

01;12;12;03 - 01;12;27;03

Geoff Nielson

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