Humans already work alongside robots in industries such as manufacturing. 

Now, for knowledge workers, the threat of AI (artificial intelligence) replacement is coming faster than they imagined.

In early 2023, OpenAI's ChatGPT ushered in a new era – one in which AI went from a pipe dream to a very real, contentious issue for workers.

The stakes are high: an April report from Goldman Sachs estimates ChatGPT, and other similar generative AI tools, could increase global GDP by as much as 7%, while replacing 300 million full time workers.

Yet the light-speed adoption and evolution of generative AI tools may now mean knowledge-work jobs that were long considered "safe" could be threatened even faster than workers anticipated.

That includes creative positions that many presumed would be hard to automate, in fields like marketing, music production and graphic design.

Accordingly, researchers have found that the "exposure curve is upward-sloping", says Mark Muro, a senior fellow at The Brookings Institution, who focuses on the interplay of technology, people and places.
 

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It is time for our new weekly look at all things artificial intelligence.

Welcome to AI Decoded, our weekly appointment with some of the most eye-catching stories in the world of artificial intelligence, we're going to take a look this week at how this technology is going to affect work.

Here's a story from the FT who report that it's the high-flying professionals in the City of London who will be most at risk from the advances in generative artificial intelligence.

In line with that, the Times asks whether workers who are replaced by AI should receive compensation.

The paper says the rise of tools like ChatGPT will inevitably lead to certain jobs being replaced.

And in a similar vein, this from Stat Medical News, a warning that even in the hiring process these algorithms could and perhaps already are discriminating without any nuance against certain types of people, notably women who've been pregnant, who will have missed work for understandable reasons.

In other news, Reuters looks at how Google DeepMind is using artificial intelligence to develop the high-tech materials of the future for energy conversion, data processing, all manner of things.

The US researchers have employed it to look at 2 million new materials, which could lead us to a new generation of technologies.

The Sun says ancient texts scribbled on 5,000-year-old tablets are being decoded by AI technology that makes sense of these texts.

It's a system similar to Google Translate, which could render Indiana Jones redundant.

And an equally mysterious text has appeared in Sports Illustrated magazine, who are accused of using artificial intelligence to create authors and writers who don't seem to exist.

With me tonight in the studio, my own super sleuth, Stephanie Hare, author and commentator on all things artificial intelligence.

Welcome to the programme, good to have you in person here with us.

Let's start with this story in the Financial Times Because I think we've all been trying to quantify what sort of difference AI would make to the UK job market.

And now they've looked at this in depth, that different sectors, different occupations.

Well, it tells us that this is something that's going to be affecting professional workers, white collar workers far more than other people.

So that's going to be management consultants, financial managers, accountants, psychologists, interestingly, economists, and then the very hard done by lawyers.

The very hard done, no 1 feels sorry for lawyers do they?

But maybe they should, because actually what you're looking at here is disruption towards people with high level qualifications.

Now, the question is, is it really going to be replacing them or, to take our example of the lawyers, do you need to look at 500 contracts to learn how to draw up a contract?

Or can you use these tools to help you get up to speed faster when you're going through your training journey and then be doing much higher value tasks?

That's the real debate within the legal profession and I think we're going to see that frankly across all of these.

It's really easy to say, oh, these jobs are going to be gone.

I think they're going to change and transform and hopefully people can get rid of the stuff that they find tiresome and tedious and get into the stuff that's actually innovative.

It's hard to innovate if 80% of your job is just grinding.

Right, we have got a problem with your mind, so if you can talk up, we'll try and fix that as we go.

I'm looking at the data on this and I see a third of UK jobs subject to some sort of automation over the next 20 years.

Yeah, but again, is it the jobs or is it the tasks within the jobs?

Now some jobs are going to go, and we've always seen that throughout human history, and then other jobs come up.

So what we are really trying to talk about here is for people who lose their jobs, will they be getting some sort of training, re-education, et cetera, so that they can go into the new jobs, or are we gonna see people getting enhanced in their jobs, their existing jobs, so they stay a lawyer, they stay an accountant, they become kind of a super empowered lawyer or accountant.

This takes us to this story in Times 2 today about, and it's a big question, about whether you compensate people for jobs if they lose jobs to artificial intelligence.

And they've asked 2 people in this field.

1 has an opinion that yes, they should be compensated, 1 doesn't.

Let's focus on whether there should be fair compensation.

This system, these systems are gonna create extraordinary wealth, right?

So you could see a scenario where there could be a tax on AI technology that could pay for those of us who are not in work.

Yeah, so from soak the rich to soak the AI.

Do you think there could be a scenario though where companies that use this, who are looking for cost savings, could be forced to pay such a tax?

I mean, I think we're going to have to really see how this plays out.

Right now, everybody's making a lot of very big statements, but we don't actually know.

So let's imagine a case where we see unemployment spike and we're going to need to retrain people.

You might say, OK, we tax all sort of industries and people who have a lot of money, more than others.

Perhaps this is what we're going to have to do.

So maybe, the question is what would that money be used for?

If it's just going to pay off your national debt or go into your defence industry to start more wars for instance, that might be quite controversial.

If the money is going back and being used to re-educate and retrain your workforce, I don't know if people would have a problem with that necessarily.

When you talk to me about this though, I find it all the more surprising that we don't have an industrial strategy because how can you possibly know where we're going unless every sector, every industry is sitting down saying, this is how we are gonna change.

I mean, there are transformations in every economy all the way back to the industrial revolution.

Well, It's difficult to have an industrial strategy with AI if you haven't had an industrial strategy before AI.

So I wouldn't wish to name any countries, but some of them need to sort of step up.

Some countries do have an industrial strategy with AI.

So the ones who are going big on AI are thinking about that.

I wouldn't wish to name the names, being discreet.

There are other people who do not think there should be compensation because they would say AI is not about replacement, it's about enhancement, as you say.

So get with the programme is the blunt message from some people working with it.

Yeah, and I can see that point because we didn't compensate people when calculators came on or Microsoft Excel and PowerPoint, the bane of every office worker's existence.

That said, I think the Nordic economies offer a really interesting model.

They do hire tax policy that then is used to retrain people who are out of work.

We don't have to reinvent the wheel here.

So we may take inspiration, if it's necessary, from countries that are already doing this but in other ways.

Maybe we've not got to the point where employers are replacing people but we're certainly at a point where employers are turning to AI in their employment decisions and there's this story in Stat News today about algorithms that are programmed explicitly to look for the sort of traits people have.

Now there are some people, I'm thinking of pregnant women, who may be absent from work from time to time for understandable reasons, but there's no nuance in AI that would actually pick this up.

No, and even if you were to try and code your algorithm so that it took into account this is a woman that's being examined to apply for a job, for instance, and you wanted to make it gender neutral and remove and strip out the fact that she had taken some time off from maternity leave, it would still be able to work out that it's a woman through other ways.

We've seen this in all sorts of other areas, and that's called proxy discrimination.

So there are many other ways to figure out somebody's female other than just simply a photo or their name or anything that would be like an obvious characteristic to you and I.

AI can do this in a way that's really subtle.

So the way that they build these models is going to have to be very, very careful and open to investigation.

They're going to have to be transparent and auditable.

Alarm bells ringing for employers on discrimination law.

Let's talk about these thousands of new materials that Google DeepMind is looking at.

I remember going up to Manchester not many years ago to talk about graphene, a new atom thick, super strong material that took years to develop.

These sort of technologies now are coming much, much quicker.

I mean, you think about lithium batteries, for instance.

Yeah, and they used to take, I mean, on average, just to give the audience an idea, 10 to 20 years to develop these types of materials.

If Google DeepMind has truly created something where people are going to be able to cut that time and get us new materials to market faster so we get new computer chips, new semiconductors, new materials to help for sustainability, green tech, climate tech.

This could be a real game changer for us and they've made it publicly available to other users.

Is it putting different pools together, research teams that wouldn't necessarily work together?

So the tool is called Genome, and this stands for what?

It stands for Graph networks for material exploration.

So we're using deep, deep tech, deep AI, deep neural networks.

They are able to make connections between atoms and between the components that will create these materials in ways that humans would struggle to do.

They can do it faster, they can do it at scale in a new novel ways that might not even occur to us.

You're going to tell me that within a year, we'll have discovered the lost ark, right?

We're going to go through all these Mesopotamian and ancient texts, and we're going to find the secrets.

Because for the first time, we can translate them.

Well, I mean if you think about how long it took Champollion to decipher the Rosetta Code, right, and it so exhausted him that he actually had a nervous breakdown and collapsed and needed 5 days to recover.

This would allow us to go through all of these cuneiforms which are 5,000 years old, 12 different languages, there's a million of them.

We'll probably have them all deciphered within a year.

We're gonna have a glimpse into human history at the dawn of time that we've never had before.

I'm guessing that ancient scribes and chiselers also made typos.

It probably would actually start to notice typos and it might even help you to figure out who were the different scribes.

Because different humans have different ways of making letters, just like your handwriting is different to mine.

They might even be making the codes a little bit different.

So it literally would be like Google Translate.

You'd have the Mesopotamian text and then the translation to the side.

I say that so much on this programme because this is moving so fast.

We've just a minute to discuss this last story, Sports Illustrated.

So what, they cut costs to create writers who have personalities?

They came up, I mean, I can't believe we're even discussing this, but it is true.

They came up with fake headshots, fake names, and fake biographies, down to their fake hobbies and interests.

And then they wrote articles, but then they got busted.

So far, I think the Sports Illustrated swimsuit issue is still an actual woman on the cover, but we may see that also become a woman.

I actually think we're going to have a backlash against all of this, and people are going to want real human beings with real senses of humor and beautiful, glorious human error.

Well, there's plenty of that on this program.

Apologies to everyone for the sound quality and the problem with the mics.

When we get AI, it will be much clearer, won't it?

They won't be those sort of technological problems.

We're here every Thursday to explain all things AI, so I hope you'll dip in same time next week.


Speaker 0: You're watching the context. It is time for our new weekly look at all things artificial intelligence. Welcome to AI Decoded, our weekly appointment with some of the most eye-catching stories in the world of artificial intelligence, we're going to take a look this week at how this technology is going to affect work. Here's a story from the FT who report that it's the high-flying professionals in the City of London who will be most at risk from the advances in generative artificial intelligence. In line with that, the Times asks whether workers who are replaced by AI should receive compensation.

The paper says the rise of tools like ChatGPT will inevitably lead to certain jobs being replaced. And in a similar vein, this from Stat Medical News, a warning that even in the hiring process these algorithms could and perhaps already are discriminating without any nuance against certain types of people, notably women who've been pregnant, who will have missed work for understandable reasons. In other news, Reuters looks at how Google DeepMind is using artificial intelligence to develop the high-tech materials of the future for energy conversion, data processing, all manner of things. The US researchers have employed it to look at 2 million new materials, which could lead us to a new generation of technologies. The Sun says ancient texts scribbled on 5,000-year-old tablets are being decoded by AI technology that makes sense of these texts.

It's a system similar to Google Translate, which could render Indiana Jones redundant. And an equally mysterious text has appeared in Sports Illustrated magazine, who are accused of using artificial intelligence to create authors and writers who don't seem to exist. We will tell you all about that. With me tonight in the studio, my own super sleuth, Stephanie Hare, author and commentator on all things artificial intelligence. Welcome to the programme, good to have you in person here with us.

Let's start with this story in the Financial Times Because I think we've all been trying to quantify what sort of difference AI would make to the UK job market. And now they've looked at this in depth, that different sectors, different occupations. What does it tell us?

Speaker 1: Well, it tells us that this is something that's going to be affecting professional workers, white collar workers far more than other people. So that's going to be management consultants, financial managers, accountants, psychologists, interestingly, economists, and then the very hard done by lawyers.

Speaker 0: The very hard done, no 1 feels sorry for lawyers do they? But maybe they should, because actually what you're looking at here is disruption towards people with high level qualifications.

Speaker 1: That's right. Now, the question is, is it really going to be replacing them or, to take our example of the lawyers, do you need to look at 500 contracts to learn how to draw up a contract? Or can you use these tools to help you get up to speed faster when you're going through your training journey and then be doing much higher value tasks? That's the real debate within the legal profession and I think we're going to see that frankly across all of these. It's really easy to say, oh, these jobs are going to be gone.

I don't know if they are. I think they're going to change and transform and hopefully people can get rid of the stuff that they find tiresome and tedious and get into the stuff that's actually innovative. It's hard to innovate if 80% of your job is just grinding.

Speaker 0: Right, we have got a problem with your mind, so if you can talk up, we'll try and fix that as we go. I'm looking at the data on this and I see a third of UK jobs subject to some sort of automation over the next 20 years. That's an awful lot of jobs.

Speaker 1: Yeah, but again, is it the jobs or is it the tasks within the jobs? Now some jobs are going to go, and we've always seen that throughout human history, and then other jobs come up. So what we are really trying to talk about here is for people who lose their jobs, will they be getting some sort of training, re-education, et cetera, so that they can go into the new jobs, or are we gonna see people getting enhanced in their jobs, their existing jobs, so they stay a lawyer, they stay an accountant, they become kind of a super empowered lawyer or accountant.

Speaker 0: This takes us to this story in Times 2 today about, and it's a big question, about whether you compensate people for jobs if they lose jobs to artificial intelligence. And they've asked 2 people in this field. 1 has an opinion that yes, they should be compensated, 1 doesn't. Let's focus on whether there should be fair compensation. This system, these systems are gonna create extraordinary wealth, right?

So you could see a scenario where there could be a tax on AI technology that could pay for those of us who are not in work.

Speaker 1: Yeah, so from soak the rich to soak the AI.

Speaker 0: Yeah. Do you think there could be a scenario though where companies that use this, who are looking for cost savings, could be forced to pay such a tax?

Speaker 1: Potentially. I mean, I think we're going to have to really see how this plays out. Right now, everybody's making a lot of very big statements, but we don't actually know. So let's imagine a case where we see unemployment spike and we're going to need to retrain people. You might say, OK, we tax all sort of industries and people who have a lot of money, more than others.

Perhaps this is what we're going to have to do. So maybe, the question is what would that money be used for? If it's just going to pay off your national debt or go into your defence industry to start more wars for instance, that might be quite controversial. If the money is going back and being used to re-educate and retrain your workforce, I don't know if people would have a problem with that necessarily.

Speaker 0: When you talk to me about this though, I find it all the more surprising that we don't have an industrial strategy because how can you possibly know where we're going unless every sector, every industry is sitting down saying, this is how we are gonna change. I mean, there are transformations in every economy all the way back to the industrial revolution. This is gonna change so fast. How could you do it without a plan?

Speaker 1: Well, It's difficult to have an industrial strategy with AI if you haven't had an industrial strategy before AI. So I wouldn't wish to name any countries, but some of them need to sort of step up. Some countries do have an industrial strategy with AI. The United States is 1. China is another.

So the ones who are going big on AI are thinking about that. I wouldn't wish to name the names, being discreet.

Speaker 0: There are other people who do not think there should be compensation because they would say AI is not about replacement, it's about enhancement, as you say. So get with the programme is the blunt message from some people working with it.

Speaker 1: Yeah, and I can see that point because we didn't compensate people when calculators came on or Microsoft Excel and PowerPoint, the bane of every office worker's existence. Nobody's done any compensation there. That said, I think the Nordic economies offer a really interesting model. They do hire tax policy that then is used to retrain people who are out of work. This exists.

We don't have to reinvent the wheel here. So we may take inspiration, if it's necessary, from countries that are already doing this but in other ways.

Speaker 0: Maybe we've not got to the point where employers are replacing people but we're certainly at a point where employers are turning to AI in their employment decisions and there's this story in Stat News today about algorithms that are programmed explicitly to look for the sort of traits people have. Now there are some people, I'm thinking of pregnant women, who may be absent from work from time to time for understandable reasons, but there's no nuance in AI that would actually pick this up.

Speaker 1: No, and even if you were to try and code your algorithm so that it took into account this is a woman that's being examined to apply for a job, for instance, and you wanted to make it gender neutral and remove and strip out the fact that she had taken some time off from maternity leave, it would still be able to work out that it's a woman through other ways. We've seen this in all sorts of other areas, and that's called proxy discrimination. So there are many other ways to figure out somebody's female other than just simply a photo or their name or anything that would be like an obvious characteristic to you and I. AI can do this in a way that's really subtle. So the way that they build these models is going to have to be very, very careful and open to investigation.

They're going to have to be transparent and auditable. Exactly.

Speaker 0: Yeah. Yeah. Alarm bells ringing for employers on discrimination law. Let's talk about these thousands of new materials that Google DeepMind is looking at. I remember going up to Manchester not many years ago to talk about graphene, a new atom thick, super strong material that took years to develop.

These sort of technologies now are coming much, much quicker. I mean, you think about lithium batteries, for instance.

Speaker 1: Yeah, and they used to take, I mean, on average, just to give the audience an idea, 10 to 20 years to develop these types of materials. It's super time consuming and costly. If Google DeepMind has truly created something where people are going to be able to cut that time and get us new materials to market faster so we get new computer chips, new semiconductors, new materials to help for sustainability, green tech, climate tech. This could be a real game changer for us and they've made it publicly available to other users.

Speaker 0: How is it doing that? Is it putting different pools together, research teams that wouldn't necessarily work together?

Speaker 1: Well, I'm delighted you ask. So the tool is called Genome, and this stands for what? It stands for Graph networks for material exploration. And it's a graph neural network model. So we're using deep, deep tech, deep AI, deep neural networks.

They are able to make connections between atoms and between the components that will create these materials in ways that humans would struggle to do. They can do it faster, they can do it at scale in a new novel ways that might not even occur to us.

Speaker 0: Extraordinary. Really extraordinary. Let's talk about this story in The Sun. Voices from the past. So look, I mean, it can decipher.

You're going to tell me that within a year, we'll have discovered the lost ark, right? We're going to go through all these Mesopotamian and ancient texts, and we're going to find the secrets. Because for the first time, we can translate them.

Speaker 1: It's incredible.

Speaker 0: At speed.

Speaker 1: Well, I mean if you think about how long it took Champollion to decipher the Rosetta Code, right, and it so exhausted him that he actually had a nervous breakdown and collapsed and needed 5 days to recover. This would allow us to go through all of these cuneiforms which are 5,000 years old, 12 different languages, there's a million of them. We'll probably have them all deciphered within a year. We're gonna have a glimpse into human history at the dawn of time that we've never had before.

Speaker 0: I'm guessing that ancient scribes and chiselers also made typos. Would it be able to see through that?

Speaker 1: It probably would actually start to notice typos and it might even help you to figure out who were the different scribes. Because different humans have different ways of making letters, just like your handwriting is different to mine. They might even be making the codes a little bit different. So there's probably...

Speaker 0: So it literally would be like Google Translate. You'd have the Mesopotamian text and then the translation to the side.

Speaker 1: Exactly, yeah.

Speaker 0: That is extraordinary. I say that so much on this programme because this is moving so fast. We've just a minute to discuss this last story, Sports Illustrated. I'm talking of mysterious texts. These are authors that didn't exist.

So what, they cut costs to create writers who have personalities? Yeah. Yeah. And each week, they produce material?

Speaker 1: They came up, I mean, I can't believe we're even discussing this, but it is true. They came up with fake headshots, fake names, and fake biographies, down to their fake hobbies and interests. And then they wrote articles, but then they got busted. So far, I think the Sports Illustrated swimsuit issue is still an actual woman on the cover, but we may see that also become a woman.

Speaker 0: Right. There's no hope for me really, is there? Journalists are in that 7%, aren't they?

Speaker 1: I disagree. I actually think we're going to have a backlash against all of this, and people are going to want real human beings with real senses of humor and beautiful, glorious human error.

Speaker 0: Well, there's plenty of that on this program. Apologies to everyone for the sound quality and the problem with the mics. When we get AI, it will be much clearer, won't it? They won't be those sort of technological problems. Stephanie, thank you very much indeed.

That's it from AI Decoded this week. We're here every Thursday to explain all things AI, so I hope you'll dip in same time next week. Thank you for watching.

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New AI may threaten 'safe' office jobs, say researchers | BBC News