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Stand clear of the doors. Welcome to in the City. A podcast from Bloomberg about the story is important to the City of London. I'm Francin Laqua. This week a discussion of Europe's productivity problem and whether AI is perceived as a silver bullet or a threat. We're joined by Matt Britain, President of Google EMA. Matt, thank you so much for joining us. I mean, you've ever seen Google's business and opera in the region for ten years now,
having joined Google in two thousand and seven. Before that, you worked in newspapers, technology and even road for TEAMGB at the nineteen ID eight Soul Olympics. So we need to talk about the Olympics. But you know, there's so much about AI and people understand it. People are excited, people are fearful. Where are we in this AI race?
Thanks for having me, and I suppose it's been my joy and privilege to see how people harness technology over the last twenty to thirty years, and I think, you know, through that period, I think we're in the third big shift. At first, I think was the birth of the Internet. So I was at university and the Internet application you could use was email, and it wasn't mind blowing because there was somebody sitting next to me sending me the email.
That was where it going to come from. And then when I started in the world of work, we saw the birth of the World Wide Web, which is actually invented as I was leaving university. And obviously I've worked for twenty years in a company in roles that have depended upon that innovation, but that wasn't earth shattering until it became accessible to everyone. And Google's played its part through Android and through Chrome and making it easy for people to use the web. And now we've got this
AI revolution. And I suppose the way I think about AI is it's about spotting patterns, making predictions and learning. AI is not new. We've been working on it for about ten years. And Google Translate, my favorite product, is a great example of that, really understanding language well. But what is new, I think is the emergence of chatbots and people thinking, oh AI and chatbots are going to change everything, and I think it's a much broader based
technology than that. So we don't yet know how it's going to be harnessed, but we can begin to see some of the opportunities and some of the risks of AI.
So, Matt, one of the industries where actually, you know, AI has been applied for good is everything to do with health and protein folding, and that leads to many more discoveries like DeepMind.
Yeah, so this is one of the things I think is most exciting is the scientific discovery impossibility. So there were one hundred and seventy five thousand proteins. They're the building blocks of life, they're essential for drug and disease research, one hundred and seventy five thousand of them, where researchers are painstakingly through observation come up with a three D structure.
And deep Minds saw the opportunity to use AI that spots patterns, makes predictions and learns to uncover the three D structure of all the proteins, and in a matter of months they did just that. So we went from one hundred and seventy five thousand to two hundred and fourteen million and we chose to make that available for free in a database so that anyone researching a disease
or looking at drug discovery can use it. And today two million people are using the database of proteins in their day to day work, and I think that means we'll see faster disease research, drug discovery, and breakthroughs that are for the general good. That's something we made available for free, and I feel proud of that because it's
built on the back of all that painstaking research. We also have Isomorphic Labs, which is a commercial venture, and we're working in partnerships with Novarta and other drug companies to look at commercial opportunities to bring those discoveries to market.
Mattter, how difficult is it to decide what it goes out in the open world so that everyone can use the underlying models, and how much you want to keep it at it for Google?
Yeah, So what we did with Alpha fold and now I'm proud of this, you know, and Google's history is always about trying to be open about innovation. When you think about search, it's connecting to your website, not ours. What we did was we said, well, you know, we've built this on the hard work of all those people who got to the one hundred and seventy five thousand proteins, and it's too important a discovery to keep behind a paywall,
so we made it available to everyone. Now. We also have a commercial operation called Isomorphic Labs that's looking, as others are to sort of exploit those those databases to try to find commercial opportunities, and we're working with Novartis and other farmer companies to do that because obviously you're going to need to commercialize these things too. So I think that's a smart but generous way of operating in this space, and that.
Of course changes vaccines, that changes the way we do trials. Is there a part Is there an industry that's not been disrupted yet by AI that you think? Well?
I mean from sine, I think we're at an incredibly early stage here, And you know, I talk a lot of business leaders as you do, and to governments, and I think last year was like the wow, you know, oh my god, this is amazing. Have you tried this yet? Et cetera. People could see for the first time in
their practical ways, this is quite capable. But now we're into the how, and we're relatively short of concrete case studies yet of the genuine positive impact all the risks that can come right, but we're starting to see them so in an interesting area. So you know, one example that many of your listeners will sort of be aware of. If you think about fraud and money laundering in the banking sector, it's something like a two trillion dollar problem globally.
And our team worked with HSBC spotting patterns, making predictions and learning to identify patents that could be fraudulent transactions, and they were able to massively reduce false positives but massively increase the number of potential transactions to look at. And so that's a good example of applying this technology in a very practical way that can create value.
When you speak to a lot of the banking chief executives, they'll say units thanks to us that we spotted a pattern, for example, on the algorithm that led to a stopping a fraudulent case trying to get access money in a central bank, and the other that is great. It also means that you can replicate a voice pattern to access money when it's not needed.
Technology is a tool and it can be used for good and it can be used for ill and I think we need to be really cognizant of that when we're designing and building things, to try to sort of factor in things that make it harder to use it for ill. But also we need rules and regulations, and that's why things like the AI Act in Europe are important. It's too important not to regulate AI and it needs to be regulated well, and that means sort of being dynamic,
you know. The way to think about regulating AI is to think about the benefits that are possible and then how do we protect against the risks. And another example we're working on is breast cancer screening. Right, so one in seven women in their lives are going to be affected by breast cancer, and yet access to mammograms and simple diagnostic knostic technology is limited and so spotting patterns,
making predictions learning. We work with the NHS here in the UK to look at thousands of mammograms, train and AI. Now the AI can diagnose the science of breast cancer as well as a clinician. It does not mean that clinicians are irrelevant. Actually, what it means is you come in and you get an answer quicker. It means that clinicians can help on the edge cases and the people need treatment, and so the outcomes for patients and clinicians
are both better. And I think that's a good and we're in the process of looking at how to scale and roll that out. That's a good example of how I think AI will work. It's humans and technology working to get better outcomes as a result of the collaboration and partnerships. I think the brand AI isn't a very helpful thing. It's a set of tools that are smarter and different from some of the tools we've had.
But is there a danger in Europe regulation at the stifles innovation because if you regulate too quickly then you don't know where it could go.
Yeah, I think there's a real danger of that. We do need regulation, and the regulation needs to be clear on the sort of rules of the road. But if you look in Europe. In the EU, over the last five years, there have been over one hundred pieces of regulation around digital technology one hundred and those pieces of regulation typically are implemented in different ways at different speeds
in all the twenty seven member states. Now think about that as a barrier to innovation for a moment, that's really hard to contend with and you might say, actually, it's something which makes it particularly hard for startups and scale ups or European single country companies, whereas a large organization like a Google or a Microsoft can absorb some
of the costs of doing that. But even for us, you know, and our competitors, we've had to slow down the launchers of some of our AI based product products in Europe. So what's the right thing for the European consumer? You know, it's interesting Mario Draugi, who's I think really well respected, is working on a proposal for the EU
around competitiveness. So one of the big opportunities of AI, I think is can it help us get more people into work, help people be more productive and drive growth which we all need.
Is it difficult and too complex to understand what the roles of tomorrow will be with the jobs of tomorrow.
We're in a moment where the headlines about you know, what could happen to work almost write themselves, and you know, jokingly you might say they can write themselves and you just put a prompt in, but nobody really knows. And actually, again it's an opportunity for us to seize the moment, and so how do we want the world of work to be? You know, I think there's lots of drudgery work that none of us would really like to do it,
and our jobs that can go away, you know. And there are many technologies that we use today that people feared when they came in but actually just made us much more productive. So I think for most jobs, the
most likely outcome is you'll be more productive. You'll be able to spend more time on things that only humans can do, like what So I think, you know, think about your work, you know, think about your work before the advent of the internet, and how easy it is now for you to research stories, to find leads, to reach out to contacts. How do you think about your
work tomorrow? Well, you know, we have a product called Notebook LM where you can put in a whole bunch of files that you might be researching, videos, audio, transcripts, and then you can ask questions of the AI about specifically those those documents and artifacts that you feed in and that can really help you synthesize, get summaries and so on. So I think, you know, that's a small example, but an example of how new, more powerful tools will help you to do you do your work differently.
Matt when you look at, you know, some of the public services. I keep on being told by heads of the departments that actually their computers don't even match, you know, and this is not necessarily NHS, this is other parts where they should match. So is there a danger that in an already divided society where some people have a lot and others don't, that this you know, social divide will grow even bigger with AI if we don't think about it holistically. I guess yeah.
One of the things that most exercises is, you know, over the long term, do the divisions within countries and across countries widen? And I think technology historically has actually helped us if you look at the long view, has helped us to sort of see millions, billions of people lifted out of poverty. We're at an all time high, I think in terms of women's education and so on and so forth. So sometimes the big picture misses the small. But you're absolutely right, we need to avoid it haves
and haves, not situation with technology. What's kept me working at Google for so long is, you know, we're all about making technology work for everyone. You know, whether you can type or spell, doesn't matter, whatever language you speak doesn't matter. We want it to work for you. And I think with AI it's the same. We need to really think about how do we harness technology for everyone.
What the opportunity is. Well, you know, today somebody without a formal education can now write almost as well as you, and I could probably not quite as well as you, but as well as I could much better. That's a huge that's a huge opportunity. I can communicate with somebody, you know in Thailand and I don't speak type, but I can communicate in pretty good tie now thanks to
these tools. So you think about that. I actually think we're going to see an opportunity for many people who don't have access to the formal education sector to participate much more fully in the world of work.
Whose job is it to think about retraining? Is it private companies, is it actors like you and other AI proponents, or is it governments?
I always think about three words when I think about this. It's bold, responsible, and together. So bold is about making sure we pursue the biggest benefits of innovations, and we've talked to some of them. Responsible is about from the start thinking about misuse mistakes and how we kind of design that out and create the rules of the road. But then together, and I think that's the most important bit.
You know, when you look at these sort of scientific breakthroughs, it's not our job, and it can't be fully government's job, and it's not the individual's job. It's a collaboration. So you need government and companies and communities to work together to harness technology for good, to decide what the rules of the road are. You know, governments have to regulate.
That tends to be a slower process, but principles and responsibilities can be and there companies come up with codes of practice and can be scrutinized, and that's an important thing there. But then communities actually are the places where you really want to define what is and isn't acceptable, and those things can vary across countries.
As we know, we've seen some pretty extraordinary pictures on the riots in the UK. How far does the responsibility go for some of the tech platforms, some of the social media actors to keep that in check with disinformation.
I mean, at first I want to say that Hart goes out to families in the community in Southport who are affected by that horrible attack at the start of this, and then we've seen this series of riots across the countries, sort of somewhat disconnected from the reality of that. Of course, you know, I think the real world and the internet, or the real world and the digital world are the same place and the same rules should apply, and the role of media, both social and traditional media in this
is something we should be looking at. How do we deal with this? Google, I suppose you know two things. One, Search is often the place that people come to try and find out the truth, and that's why we work with news organizations around the world on search and on YouTube, so that when you ask about news, you're pointed to credible news sources. Now there's a difference of views across those news sources, but you can find a selection and that's a key role that we play, and that's why
we work so closely with news organizations. Second thing for us, though, is to have policies that are clear about what we will and will not allow on our platforms. On something like hate speech. It's not easy, so people would say, you know, on YouTube, you know, you seem to be pretty good at keeping it clear of pornography, but actually if you ask people in the street, you have pretty
clear agreement on what was and was not pornographic. But on something like hate speech or incitement of violence, there are lots and lots of shades of gray. And about ten years ago we had a real challenge on YouTube with videos and across the web, but YouTube as well, videos that were about sort of inciting extremist behavior, hate speech and so on. And we work with one hundred and fifty expert organizations to come up with policies which
we then had people classify video. We then use the classified videos to train AI and then we published transparently how successful we are. So I can say that today over ninety percent of videos that violate our violent extremism policies never get seen by a single human, and then the rest of them we can take action very quickly. So in the case of the UK, our teams are able to move quickly to remove violative videos and channels than they've done.
So how difficult is it to actually know where this piece of disinformation comes from? If it's from a state actor, is it more difficult for Google to channel than if it's from an individual?
Yeah, So if a zoom out from the UK situation for a minute. What we see is, yes, there are an array of actors who try to intervene in the democratic process for example. So you know, we have a team that looks after election integrity across our platforms and in the recent EU elections, they're absolutely working closely with the election authorities training people on how to use the tools, et cetera. And we have a threat analysis group that
shares with governments and key agencies. What we're seeing because we've got lots of popular products, so we see lots of attacks. Well, I can say is in the EU elections actually it was sort of more old style attacks. I think Microsoft suffered some attacks on accounts for example, rather than that was feared. You know a lot of fake AI generated imagery. But just as we have tools that people can use to generate with AI fakery, the technology we've got to be able to detect it is accelerating.
And so we've been using AI on YouTube, as I just mentioned, extensively for years to classify and address videos.
Are we over estimating how quickly some of the AI products will take over? We had this amazing interview with the Bumble founder and she was saying, you know, for dating, for example, you're going to have a personal assistant that kind of dates for your online and then reports back on who's a super suitable match. I mean that feels like science fiction.
I don't know, bumble, I should just be clear, But I think it's up to us, Like you know, none of them, this is inevitable. And this is my point about like this is a moment where we have to sort of engage into this stuff and take control. So some people might want that for dating. I'm not sure I would, but you know, you'd have a choice. Or maybe you've got an advisor who said, here at some better suggestions or whatever. That's great. Same as you know,
reading the news. Actually, I might want to have a little bit more dissonance in my consumption of news, and maybe an a I could suggest that. Or I might want to have an expert summary of a long running story, and if I could come to Bloomberg and your AI assistant would give me a brilliant summary of some of your best journalism around a complicated issue, that would be useful. But I think we have a choice, and it's up to us to make those choices.
Who's it up to the consumer, or is it actually you know companies like Google to decide. I mean, if we were all to be given you an assistance that can help you in everyday life, is it too soon to say whether that's a good or a bad thing?
Let me step back. I think where we are is we've got this broad based technology. We're beginning to see the potential, but most of the applications of that technology have yet to be invented. So we can get lots in generalizations. But you know, a specific example about how it might work with dating we could talk about, or how it might work with newsroom productivity we could talk about, or how it helps call center agents. Gives you better examples, So I think we need to look at the applications.
How do you hire it at Google? I've heard from some tech companies that it's all about morals and values and it doesn't really matter if the candidate knows that much about technology to start with.
Yes, absolutely, we try to hire people of good character, but also people who are collaborative, curious, creative, good communicators. I think the most important things when we're hiring are those skills of curiosity, creativity, collaboration, communication, Because we're asking people to invent technology that didn't exist before, and we're asking people to sort of explain that technology to the world, to listen and engage with governments and companies and partners
on how we do that. What I'd say to people thinking about, you know, maybe choices for their children today with their children, I think it's really important we have a broad education. You know, innovation comes from interdisciplinary collisions, right, and I don't think we should be overly focused on STEM. I think we do need representation so that people building
the technology have to be representative of everyone. And that's been a challenge and one of the reasons we've published our own data on diversity and trying to improve particularly representation representation of women and minority ethnic groups in the engineering side of Google. We've made progress, but there's more to do, so i'd encourage people. You need it broad based education, but those skills about curiosity, creativity, collaboration are going to be more.
Important in the future early days. But how do you judge this new government in the UK and how they engage with technology.
We don't make it want to make any political comment other than to say that I think the UK's had a long period of instability, and if you're an international investor and company like Google, having clarity and a sense of stability is important. I think also there's a recognition that the UK needs growth and that's an absolute priority, and I think harnessing technology across sectors can be one of the key ways in which we activate that growth. Growth. Secondly,
harnessing young people and their talent and their desire. It's something that feels like it may have been a bit neglected, and you know, I really think that's an important thing for us to do as a country. So I think there's a big opportunity for the UK.
Matt, you've rowed for a team GB. Congratulations. There's a lot. I mean is that, you know, we talk more and more about sports, and actually what you learn in sports, especially at that level for applications in business, what did you learn from it?
I rowed when we were much less successful than we are today. But I have to say that, you know, I went to business school, I worked in a consulting company. The stuff I used most in my day to day work I probably learned from sport. And it's that being clear about defining a goal and then bringing people together around a vision of what's possible and collaborating. I always say to my teams, you know, get the best people in your boat, and then let's make sure we row together.
And so there is something about that sort of skill of competing and collaborating together. The same applies to how we partner with companies. You know, we're going to be competing, we're going to be collaborating, we're going to be learning from each other, and we need to have a grown up approach to doing that. And I think I learned a lot from Sport about those things.
Matt, thank you so much for joining us.
Thank you.
Thanks for listening to this week's In the City from Bloomberg. This episode was hosted by me franc I Laqua. It was produced by Summer Sami, production support from Isabella Ward, and sound designed by Moses and Dan Brendan Franz Newman is our executive producer. Sage Bauman is head of Podcasts Special thanks to Matt Britten. Please subscribe, rate, and review wherever you listen to podcasts