[0:00:00] We have one of the most exciting panels here in Davos. We have an incredible group of people on stage. We have the folks who control the path of the next pandemic, much of the world's economy, whether the West survives, and based on the logs, how my kids are doing their homework this week while I'm in Davos. So we have a lot of influence right here. We're going to talk about democracy. We're going to talk about income inequality. We're going to talk about climate. We're going to talk about how companies are transforming.
[0:00:29] But first, we're going to start with the Secretary General. First, let me just do quickly introductions. We have the CEO of Pfizer, CEO of Uber, CEO of Anthropic, President of Alphabet and Google, and the CIO, the CEO of Salesforce, and the Secretary General. We're going to start with the Secretary General. Secretary General, how are you? I'm fine. How are you doing? Wonderful. And how's the group doing? Good, see you all. Wonderful. First question for you. A lot of technological change. It's been interesting to watch the war in Ukraine where, in fact,
[0:00:59] One of the most interesting technologies that has been most impactful has been drones. Tell me, as you see military changing, as you see AI coming, what to you is the most important change that will affect the balance of power in the coming years? Clearly, at the moment, it is the drone technology which is really changing the way we conduct these wars. You see now $400 Ukraine drones taking out a multimillion.
[0:01:27] In terms of cost, Russian tanks.
[0:01:30] We just launched Baltic Sentry. This was a mission, is a mission, or an activity, we should say, in the Baltic Sea, in the East Sea, to fight off the Russians who are getting at our critical undersea infrastructure. We are using sea drone technology there, next to the more traditional technology with ships, etc., and aircraft, but also this drone technology here. And obviously, AI will also be transformative in terms of how we fight our wars. Of course, the...
[0:01:57] The question I'm getting a lot is that I'm really pleading for more money to be spent on defense. And then people are worried that we will spend that in the same way as we did the last 100 years. But that is not the case. Yes, we have to spend more. We are spending now on average here in Europe 2%. It has to be much more.
[0:02:15] I think Donald Trump is right here that we are spending not enough. And anyway, we have to get it into a balance with what the US is spending. But particularly here, we have to look out for the industry base. So what our defense industry is producing. And they are not producing enough. But also, in terms of innovation, we are too slow in innovating. One of the problems here we have is that the better is the enemy of good. It all has to be perfect.
[0:02:43] But it doesn't have to be perfect. When Ukraine is fighting this war on a 1 to 10 scale, they can settle for a 6 or a 7. But in NATO, we can only bring something out if it's a 9 or a 10. We don't have that luxury anymore. So speed is of the essence, not perfection to get these new technologies in. And if we don't, then we have to spend even more. So joint procurement, yes, we have to get the big contracts in. But also in terms of the innovation, if we not innovate faster at a higher speed,
[0:03:13] Achieve in perfection, but getting speed and enough quality done in the right conjunction, then we have to spend even more. And it is already a big drain, of course, on societies, defense spending, and we need more of that. So in that sense, technology is a crucial factor. Well, the speed of transformation is actually a wonderful segue, because when I look at this panel, which covers so many diverse areas of the world,
[0:03:36] One of the things that most people have in common is they are running businesses that are going to be radically transformed by technology. So Mark, I want to go to you. One of the terms that people often say is creative destruction. How do you take a company that is very successful at one thing and radically transform it? You've been talking about doing that at Salesforce. Tell me, what is the hardest thing about the transformation you are going through right now? Well, I really appreciate it, Nick. I mean, I've never been more excited about my job and about my industry.
[0:04:03] I mean, it's incredible what is going on right now. It's really a phenomenon. This is just in a moment that none of us will ever forget. And I'm just thinking about this, talking to so many of my friends here at the World Economic Forum. And we were just in the IBC, the International Business Committee, which was 250 CEOs. And you were running a panel, Nick. And I said to the group, we're going to be the last CEOs. We are the last CEOs.
[0:04:30] Who are only going to be managing humans as our workforce. That from this point forward, like this is the marking that we will be managing not only human workers, but also digital workers. And that is just incredible. And I just look right here at Davos now.
[0:04:48] Salesforce runs all the information management for Davos. It has for more than a decade. So, of course, when you're on the Davos apps and you're going through all the lists of all the sessions and who's attending and all that, and you figure out how to make the most productive use of your week, you're using all these Salesforce technology. But this is the first Davos that you'll notice that right on the Davos app there is an agent. And this AI agent is there to help you, to be your guide.
[0:05:16] To be your partner in making sure that you're able to have a great Davos. And what it does is it goes back and it looks at every session you've ever attended, because all of that is recorded as you badge through the conference. And every session that is available and everybody that's here. And then that agent can say, yes, this is the thing you need to do in Davos to be really successful right now. And it uses the best large language models, but also the best machine learning, the best.
[0:05:45] Intelligence, it delivers the highest accurate results. It's delivering a 95% result for Davos attendees because it has access to so much data that has been collected here over so many years. And it's a great example of very practical AI. And I'll say another example is that we also met in the same meeting, Dave McKay, the CEO of RBC, Royal Bank of Canada.
[0:06:11] And he's got this incredible wealth management business that he runs. And he's a leader in this area. And they've built this agentic layer. Agentic layer means he's built agents around his business that augment his workforce. So in addition to his sales workers and his service workers and his support workers, he uses an agent force, just like we're using here to run the Davos. And so that's just fascinating to me that we are at that moment that we're going to say, yeah.
[0:06:40] This is when humans and AI are working together to create a higher level of success. You know, I really appreciated your agent, Mark, actually, because I was out on the promenade at 2 a.m. and I'd had seven drinks, and the agent, having based its study to all my previous Davos's, said, stop, and sent me to bed. So thank you very much. Ruth, you have this company that has built one of the most successful products in humankind history, a search engine. It's going to have to transform, in many ways, into an answer engine.
[0:07:09] Building a business model around that is hard. It will change the way you make money, and it will change the way a lot of companies that relied on the search engine make money. So explain the trade-offs as you make this transition. Well, first of all, it's great to be here with you and with everyone. Since inception, Google has been focused on long-term investing with a sense that technology changes and we're going to have to evolve throughout time.
[0:07:32] And if you think about it, Google started as 10 Blue Links. It then went to text search. It went to voice search. We're now living in a world with multimodal search. But we've been infusing search with AI for many years now. Billions of people are benefiting, whether it's as simple as autocomplete or searching photos. You just take it for granted. And multimodal search...
[0:07:53] is exciting, what you can do with this product we call Lens. For those of you who haven't used it, you take your phone with the camera, you can take a photo of anything and search through that, find any information, product, availability, price, anything in nature, you name it. 20 billion searches a month through Lens. So this has been a constant evolution, and where we are now, leveraging Gemini,
[0:08:17] is looking at AI overviews, which you can think of as sort of an umbrella, your cockpit, that then helps guide you and takes you to different places. And what we're seeing is more complex queries, longer queries that go into greater depth. It's expanding in terms of demographics. The youth in particular are looking at the ability to ask multi-part queries. And so it's continuing to enrich the search experience, which is what
[0:08:46] Google has been about all the time. And our investment, I'm frequently asked, consistently is around being ahead of and evolving where will search go, given the extraordinary experience that we can deliver for all of that. And this didn't start now, this evolution. We started Google Brain, our first AI.
[0:09:04] Thank you.
[0:09:23] Tech enabled and have the opportunity. If you're not planning and investing for long-term growth, you're going to be sowing the seeds of your own destruction. And so where we're sitting is an extraordinary position where we're leading in science and innovation. So we won, as an example, Demis Hassabis and John Jumper won the Nobel Prize this year for their breakthrough in science. We view ourselves as looking at science at digital speed.
[0:09:48] AlphaFold, which is the greatest contribution to drug discovery. That didn't come out of just recent research. They've been working on it for quite some time. Greatest contribution to drug discovery, the work we're doing in quantum, where we had a breakthrough in quantum computing. You can do a computation in less than five minutes that previously, or today, would take supercomputers, the best supercomputer on the planet, 10 septillion.
[0:10:11] 10 septillion hours to do, 10 and it's 24 zeros behind it. It's extraordinary what we're able to accomplish with science. And so we're already investing, to your question, on where the world will be next. Clearly, the majority continues to be in search, leveraging Gemini. What's that search experience? But we're also leaning into being the leader in science and innovation.
[0:10:34] I often think about how at the Atlantic we can diversify our business models for the age of AI. One of the things I had not thought about was building a quantum computer, but I will put that on my list. Albert, let's go to you. You have to change the way drug discovery works. You're going to have to reinvent how the company works, and you're going to have to not be beaten by new drug development companies that are fully AI-based and are taking the technology that Ruth was just talking about.
[0:11:00] and building companies from scratch based on AI with their agent employees. Tell me how you're thinking about this transformation. First, I need to tell you that I'm super excited about the prospects of life sciences, exactly because of that. It's not only advancements in biotechnology, but also advancements in digital technology. But the two are colliding and they are going to create tremendous synergistic effects. I'm going to use an example of a disease that worries all, the emperor for maladies, cancer.
[0:11:26] There is a new biotechnology that we are using which is called ADC, antibody drug conjugate. I'm going to use, because we have marked here, military terms to describe the war on cancer. The problem is that when you use the chemotherapies that are the most commonly used drugs right now for cancer, you are not killing only the cancer cells, but you are killing also the healthy cells. So you need to be more precise. So that's why we developed something like a GPS-guided missile.
[0:11:54] A medicine that is very precise. We try, first of all, to identify a target that will identify that this is what we want to kill and shoot. So, for example, a protein that is more common in the cancer cell than in the healthy cells. One example, IB6, it's a protein, IB4, excuse me, which is a protein that is expressed in 90% of lung cancer cells.
[0:12:20] So now we know that this is the target. We know that if our missile sees AI before, we'll attack it. In order to identify targets, AI will make that process that usually was taking years, will take it take months. It's amazing. It's exponential, the improvement. Once we do that, now we need something that will be the GPS mechanism that will come and adhere to the target, this protein. So we need to bring an antibody.
[0:12:51] That will go and click to this protein. And AlphaFold, which Ruth spoke about, and it is a good example, because also the inventors took the Nobel Prize this year, it is helping us to accelerate the design of these antibodies instead of years, months. Once you have the antibody, now you need a warhead for your missile. And that will be nuclear or can be tactical, depends on what is the...
[0:13:20] So what is the result of all of that? You link the antibody with the warhead, you release the missile, and it will not explode on any healthy cell. It will explode only on the cancer cells. AI can facilitate each and every of these prospects. Whatever we can do with ADCs in 10 years, we can do with ADCs in 18 months now.
[0:13:45] While you were talking about precision targeting missiles, I noticed that everybody in the panel was interested, particularly the Secretary General. I know how to get his attention. Dara, you're taking your company, you've got all these drivers, you've created incredible jobs, folks who need side gigs, working class jobs. You're about to move into a new era where a pretty significant percentage of your fleet will be robo-taxis. Pretty big change. How are you thinking about...
[0:14:12] Actually, I'm going to ask you the same question I asked Mark. What is the hardest thing for you to get right during this transformation? Well, I think first the potential that we see in terms of AI. I think most persons, most of our experiences with digital experiences of AI, search, et cetera, where we work is the physical world. And we think that AI can have enormous impact on the physical world. And ultimately, the future of transportation that we see is going to be autonomous.
[0:14:39] It'll be electric and eventually it'll be shared as well. So congestion on the streets is something that can be controlled. And for us, the applications of AI are essentially passenger vehicles. Instead of having a human driver, you'll have a robot driver. And we're working with Ruth and Waymo and a number of other companies in developing this technology and really bringing it to market so that everybody can experience it.
[0:15:06] And then also there are applications in terms of package delivery. So you may see here these little sidewalk robots, serve sidewalk robots that are delivering your food. And then, of course, in trucking, we have a business Uber Freight that's connecting shippers to truckers. Those trucks eventually will be driven by robots as well. And the ultimate promise of AI is literally to save lives, right? It's today as we speak.
[0:15:33] This year, there will be a million fatalities on the road as a result of human error. And this digital driver is going to have thousands of lifetimes of driving to train, is not going to be distracted in terms of by texting, by watching TikTok, whatever. It will be a driver that's completely focused on the road.
[0:15:58] It won't have two eyes. It'll have 10 eyes and many different sensor types. So by definition, over a period of time, this driver is going to get better and better and better. And it will start to be more of a reality in our network. Our view is we're working with a number of partners, NVIDIA, Alphabet, Wabi, et cetera, to bring this technology to markets in a safe and responsible way. It's not going to get there tomorrow.
[0:16:27] And there will be a very long hybrid road where sometimes you're going to get a human driver, sometimes you'll get an AI driver or a robot driver. But fast forward 15, 20 years from now, the impact of AI in the physical world and the impact in terms of saving lives and avoiding fatalities is going to be enormous. And we want to play a big part in that transformation. Dario, Dario just said something. He said 15, 20 years.
[0:16:55] And talking to you here in Davos and talking to others, I think one of the biggest differences, you think things are happening much faster. Most everybody in Davos agrees that AI is coming, things are going to change. But when other people talk about years, it's changes that you talk about in months. And when other people talk about decades, it's changes you talk about in years. How fast is the world about to turn upside down? Yes. So I would say that I think the thing that most
[0:17:21] Distinguishes AI from previous technological revolutions is exactly the speed at which it's happening. So I've been in the field for 10 years. I've been watching that curve for 10 years. And me and my co-founders at Anthropic were among the first to document.
[0:17:36] What we call the scaling laws, which is the observation that as you pour more compute into these models with small changes in the algorithms according to which they're developed, they improve very fast on cognitive abilities. And so exponentials kind of start slow and very quickly pick up speed. And I think we're actually, I've become probably in the last three to six months more confident that we really are heading towards
[0:18:05] AI systems that are better than almost all humans at almost all tasks.
[0:18:10] My guess, and I'm still not certain of it, but I think with some of the things we've seen with models starting to be as good as PhD students in areas like math and programming and biology, it is my guess that by 2026 or 2027, we will have AI systems that are broadly better than almost all humans at almost all things. I see a lot of positive potential. That's an understatement.
[0:18:39] for how this kind of AI can be applied. You've heard about a lot of these areas, right? From military applications to in the workplace, to self-driving cars, to applications in biology and health, which are very near and dear to my heart because I used to be a biologist. And I think that's maybe one of the opportunities to offer the most improvements in human welfare.
[0:19:04] In line with the thoughts on longer timelines for self-driving cars, I think what is going to hold us back most in positive applications is the physical world and limitations on human institutions. So I wrote an essay about this transition, about powerful AI. If this really does happen, what will we be limited by?
[0:19:27] And so the term I used in this essay was marginal returns to intelligence. Economists talk about the marginal returns to capital, to labor, to land. A way we're not used to thinking about things is what if we have millions of copies, I called it a country of geniuses in a data center, of agents that are better than humans at everything.
[0:19:50] What limits? Do we just immediately solve all of the world's problems? I don't think that happens. For example, self-driving cars are difficult. So I think we're going to be limited by the physical world, by deployment cycles, and often by laws. If we take the pharma case as an example, we still need to run clinical trials. There's still physics and biology, but...
[0:20:14] I think the AI systems will get better at things that used to be late-stage clinical trials can become early-stage clinical trials. Things that used to be early-stage clinical trials can be done in vitro. Things that can increasingly be simulated.
[0:20:34] So I do think there will be a great acceleration. If I had to guess, and this is not a very exact science, my guess is that we can make 100 years of progress in areas like biology in 5 or 10 years if we really get this AI stuff right. If you think about...
[0:20:53] You know, what we might expect humans to accomplish in an area like biology in 100 years. I think a doubling of the human lifespan is not at all crazy. And then if AI is able to accelerate that, we may be able to get that in five to 10 years. So that's kind of the grand vision. At Anthropic, we are thinking about, you know, what's the first step towards that vision, right? If we're two or three years away from the enabling technologies for that.
[0:21:23] The way we've been thinking about it is, you know, all this describes productivity in the workplace, right? Even very high end productivity for, you know, cures for diseases. So we're working on something called a virtual collaborator, which is the idea of having, you know, an early version of this, not necessarily smarter than a Nobel Prize winner, but capable of doing relatively high end tasks in the workplace that can, you know, that can.
[0:21:48] Open up Google Docs that can use Slack, that can interact with its coworkers to perform tasks over hours to days, and that you only have to check in with every once in a while, like a manager would check in with an employee. Mark said, you know, this will be the last generation of CEOs that only manages humans. We're trying to make that real.
[0:22:09] Secretary Jenner, you want to jump in? Building on this, because what I'm seeing in my work, in my job now, is that what is holding us back in terms of speed of applying AI exactly as you were saying is the traditional structures, the bureaucracies. And basically you have three types. One, of course, is when there is no war.
[0:22:27] Then the only way to leverage this new technology is to make sure that you work with small and medium-sized enterprises, with start-ups who are really leading edge here. In NATO we have all these systems, the IANA and the investment fund, et cetera, to make sure that you work with academia and with the start-up sector. But it's not easy because the system was used of building these huge tanks, huge fire jets, et cetera, and ships, what have you, and not implementing necessarily this latest technology.
[0:22:56] A second level is these what we call hybrid threats, which can be quite scary, these hybrid threats. It can be an assassination attempt on the pulse of Rheinmetall. It can be a cyber attack on the NHS in the United Kingdom. It can be the jamming of commercial flights in the Baltics. And of course, getting at the critical undersea cables like between Estonia and Finland. And then there is a need to apply the latest technology fast.
[0:23:24] And I was happy to see that at least within the NATO system, we were able to do this. But then, of course, leading edge here, cutting edge is Ukraine. What they have to do is to implement every two weeks the newest technologies to stay in front of, in terms of technology-wise, the Russians. But the Russians are copying what the Ukrainians are doing also in two weeks. So these technologies, including the use of AI and how we can speed up the bureaucracies to do this, is really key.
[0:23:52] And I'm absolutely optimistic, like all of you, when it comes to AI. But the question is, what is holding us back to do it even faster? It's AI. Just one other question on AI for certain applications is the cost of an error. Part of humanity is its flaws. And we accept that humans are going to make mistakes, et cetera. Again, you go to these world fatalities. I think one of the questions in certain AI applications,
[0:24:22] Defense may be one of them. Certainly AI in the physical world is. How much better does that AI have to be than a human being? Is 10 times better enough? Is 20 times better? You look at Waymo, for example, based on their safety statistics. Ruth, how much safer is Waymo than human beings probably at this point? Meaningfully safer, but your point is well taken. There is more forgiveness when it's a human driver. And so the question is, when a machine makes a mistake, when an algo makes a mistake,
[0:24:51] How does society look at that mistake and the cost of that mistake versus the benefits of AI coming into the fore? Well, society reacts very badly, right? As we've seen with self-driving cars, which are evidently safer. And the question is, will society change as more technology comes, right? Will there be a backlash? Actually, Albert, let me ask you this question. So what Dara is talking about is building much safer technology and facing a backlash. You built...
[0:25:16] A product that was like the best product the world ever had and probably saved the lives of a bunch of people in this room. And there was a massive backlash. Is there anything you learned from that that will be helpful to people who are bringing in new technologies in the next years that will be useful? I'm sure you're referring to the vaccine, but it was not massive backlash. It was significant. It was maybe 10, 20% of the people. I can tell you at the same time, we received a lot of love.
[0:25:43] From 80% of the people that felt that their mother or father is alive because of us. So let's put things into perspective. The fact that some of the voices are magnified through social media doesn't mean that they are the prevalent voice. But the example that you use is a good one because AI also will face the same problems and probably AI machines will create the problems to AI. They are the ones that they will spread the disinformation about it. And why? Because it's very powerful too.
[0:26:11] And with every powerful tool in the hands of good people, we'll do great things. In the hands of bad people, we can do bad things. And I think that will be magnified. Every single mistake that AI will be doing, as you mentioned, will be magnified to the utmost degree, ignoring that humans are making even bigger mistakes and ignoring that the benefits that we got so far were huge. Ruth, can I ask you a big question that is quite relevant to this? So to me, the most...
[0:26:38] Interesting, I keep a list of questions in AI that I don't really know the answers to and that people disagree on. And the one that I'm most interested in is whether AI will make the world more equal or less equal. Will it increase inequality within countries or will it do the opposite? My view is that technology made the world less equal, right? It rose all boats, but the folks at the top did better. What do you think will happen with AI? Will it condense and collapse income inequality, as some studies show, or will it exacerbate it, as others do?
[0:27:07] Yeah, it's an absolutely critical question and one we're extremely focused on. I think there's a tremendous amount of upside to capture which will address this productively, but there are execution risks that we all need to be focused on. So what we get really excited about is it's in health, it's in education, it's the economic upside. We've talked about health already to an extent, but just to expand a bit, with AlphaFold, as I said, what the team did, what Demis and the team did,
[0:27:36] And so the ability to address disease, all forms of diseases, and do it at
[0:28:03] As I said, at digital speed is absolutely extraordinary. And what does that do to address illnesses everywhere on the globe? The other very much more direct to your question is early diagnosis of disease. Early diagnosis is one of the most important elements in survival. And for me, this is personal. I've had cancer twice, and I know I was one of the very fortunate ones.
[0:28:25] Who went to one of the best hospitals on the planet, Memorial Sloan Kettering, and I had early diagnosis. Not everyone does. 40% of people in the United States will be diagnosed with cancer in their lifetime. Globally, there are other diseases that are actually killing people before cancer does, which goes back to my first point. Early diagnosis is key.
[0:28:46] Google, years ago, developed with AI the ability for early diagnosis of metastatic cancer. Started with breast, went to lung. I spoke to my oncologist about it, and he said the only way to democratize healthcare is with AI, because it means anyone, anywhere, will be able to have the same high-quality early detection that I have. And what we're already using today through Google AI, the research that we've done, is early diagnosis for tuberculosis. 30 to 40% of cases of TB.
[0:29:15] Go undiagnosed because they're in the global south or in poor communities across the United States. That is already happening today. That is not a tomorrow opportunity. Diabetic retinopathy, losing your eyesight as a result of diabetes. So this very much is an opportunity to address inequity. Education, super exciting. In Africa, the average age is 19. Spoke to one minister who said,
[0:29:40] By definition, half of our population is under 19. We don't have enough teachers. And if you can't educate your kids, you can't address that opportunity gap. You know, I grew up, my parents always said, education is your passport to freedom. We firmly believe that. And what we can do, and what the minister pointed out, is AI is operating leverage for the teachers, and it also enables students to get taught through AI, which is extraordinary.
[0:30:06] The problem, the execution challenge, so I talked about cancer. Well, cancer, early diagnosis is one part of a broader ecosystem. In some places, this may be an equalizer in the United States. It will be an equalizer if you have a doctor who otherwise couldn't deliver because you can then go somewhere else for chemo and radiation. But that is not true everywhere in the world. So you need the full ecosystem to develop. The other really important point, probably the most critical, is that a third of the planet
[0:30:34] It's still not connected. It's still not online. So they don't have access to the magic that we're talking about here today. And then you go to the economic upside. The economic upside is profound. The estimates are wide. They're in the trillions. But again, if you go under the cover, the execution issues are what we're really focused on. Now, it's encouraging that the data say, economists at MIT, at Stanford, that it is the
[0:30:59] Early entrance to the workforce and low-skilled jobs that may benefit the most because you have a tutor by your side. That's a positive. More jobs are created historically than destroyed in tech transition. That's the good news. The bad news is when your job is the one that's eliminated, it becomes very binary very quickly. And so we're doing quite a bit of work, as are many others, on workforce.
[0:31:22] Empowerment for workforce training, getting people ready for what those new jobs are. And there are extraordinary jobs that are available. But that's something that we cannot take for granted. And the final point, wherever I travel around the globe, what I hear from global leaders is they want their country to be a part of the digital transformation because they see these upsides, the economic potential, the potential around health care, education, agriculture, you name it.
[0:31:47] And so that's what we're trying to do is make sure that we are partnering up globally in the right way, but execution definitely becomes key. And some of the comments today, I very much agree. At the end of the day, the upside opportunity is so profound that we need to collectively make sure we're mitigating on the downside. We can't miss it. This is a very optimistic panel, so let me try to change the mood a little bit if possible. Mark, can I ask you about something that one of your passions?
[0:32:16] Where maybe things aren't going as well as you might think, which is climate change. So in the last little bit of time, the United States has pulled out of the Paris Accords, we've frozen a bunch of spending that was going into climate investment. It seems, in fact, we're sort of transferring capital from climate to crypto, which maybe isn't the best use of energy resources. All this AI boom, incredibly carbon intensive. Are we going in the wrong direction on an issue of paramount importance where we're already having a lot of trouble?
[0:32:48] Well, it's a pretty big context switch on the panel. I mean, we just heard the incredible benefits of unlimited workforces, the idea that AI is kind of becoming our partner to help us to run our lives, run our businesses, to help us to deliver a new level of productivity without a human workforce. And you're 100% right. We have to keep in mind that we have a vision for the world that is...
[0:33:17] Getting warmer. And the reason that it's getting warmer is because there is more carbon in the atmosphere. The first industrial revolution has really given us about 200 gigatons of carbon into the environment through various human levels of activity. But it's not our biggest worry. Our biggest worry is really deforestation. The planet had six trillion trees on us, and now more than half of those trees are gone.
[0:33:45] And for every trillion trees, we lose 200 gigatons of carbon banking. So just imagine that as three industrial revolutions that we've released into the environment through deforestation. I was very optimistic yesterday, and I guess we should go back, but we mentioned Trump five years ago. On this stage in 2020, President Trump announced the trillion tree initiative. That is that our...
[0:34:13] Our vision was to put a trillion of those trees back on the planet to sequester 200 gigatons of carbon. Of those trillion trees that we want to do, we actually now have commitments and underway on 200 billion. The biggest also happened on this stage last year, China coming in for 70 billion trees. That is a case for optimism. Another case for optimism happened just yesterday here at the forum, not on this stage, but in another stage.
[0:34:41] The president of the Congo announced the world's largest forest reserve as part of the trillion trees. I think there's nothing more important than reforesting our planet if we want to make our world cooler and to counter what we've done in the industrialization. And number two is we can also see that the oceans are getting warmer. We've just had two back-to-back El Nino years. And I've heard now several reports talking to folks here from around the world that
[0:35:09] We see coral bleaching happening in areas where we have not, even just in the last six months. So whether it's coral bleaching, overfishing, whether it's creating more marine protected areas, getting to our vision of protecting 30% of the oceans by 2030, and getting the plastics out of the ocean. We're on the verge of the UN High Seas Treaty. This is probably one of the most fundamental things the United Nations can do this year.
[0:35:38] And the second is the UN Plastics Treaty. We have to get the plastics out of the ocean. So we can all think about this as a case for optimism in the environment. And AI is an accelerator on all of these ideas. So net-net, do you think that AI, its ability to help us model plastic flows in the ocean, for example, and figure out how to extract it more efficiently and maybe build carbon capture systems, net-net, AI will be positive for climate, even though it has huge energy costs?
[0:36:06] Net-net, I would say that the most optimistic thing that I've seen in getting the ocean plastic out of the ocean is, number one, making sure it doesn't get in the ocean. So robotics has advanced with AI, and we see entrepreneurs like Mark's colleague from the Netherlands, Boyan Slat, who has developed robots that sit in rivers in critical areas in Asia or in...
[0:36:33] in South America that prevent this plastic from getting in the ocean in the beginning. That just wasn't possible 10 years ago. Now we see, you know, the ability to extract millions, hundreds of millions, billions of tons of plastic that's already in the ocean, but we have to also keep it from going there. We also announced a plastic initiative here at the World Economic Forum. How do we get to bioplastics?
[0:36:56] This idea that the plastic that's in the ocean is kind of the nuclear waste of our age. It's going to be there for a long time. We already see the infusion of that plastic into plankton. We now know the fish are eating the plankton, ingesting the plastic. And we know where that goes in our food chain right into our bodies. And I don't think any of us want what's happening. And I don't want to go into the details because it just, you know.
[0:37:21] Turns out it'll take away the case for optimism around human health. But we want to have a healthier food chain, and getting plastic out of our food chain is so important. Well, since in Davos I only eat green room granola bars, I haven't had any plastic, but I do think this is an extremely important cause. Dario, let me go back to your essay, which you mentioned earlier, Machines of Love and Grace. One of the most interesting parts, and I think something that ties into what Ruth was just talking about, something that has come up on stage, is the prospect for...
[0:37:50] Sort of stable democracy where people trust the government. And it's an extremely optimistic essay, but what's so interesting is there's a point where you're not as optimistic, and you say you're not sure whether AI is more enabling for democracy or more enabling for authoritarianism. So explain what you mean, and explain what you think, and then we'll have the others comment on that, because that's pretty important. Yes, so I think here we've mostly talked about all the positive applications, and I'm very excited about them.
[0:38:20] I tend to be optimistic about places where markets work well, about human scientific advancement leading us forward and AI scientific advancement augmenting them. I think places where I'm less optimistic are around the political system. If we look at the last
[0:38:41] 100, 200 years of history, there has been sort of a trend towards democracy being more ascendant, democracy being more dominant. But it's been an extremely noisy trend. If the moral arc of history is long, this is perhaps the longest part of it. And so this is one of my deepest worries. If we go back to the country of geniuses in the data center, which I think we will likely have in two to three years,
[0:39:07] Imagine what that country of geniuses in the data center could do in the hands of an autocracy. We take 10 million virtual minds that are smarter than any Nobel Prize winner and, let's say, put them in the hands of China.
[0:39:23] What could they do in terms of a surveillance state? The power of dictatorships has traditionally been constrained by the need to have humans who carry out the will of the dictator. That has limited how terrible the dictatorship can be. There is a chilling possibility that AI could remove some of those limits and make possible something like a 1984 or darker. On the international stage,
[0:39:48] You know, is it possible that AI could drive these very powerful drone fleets or this, you know, all-seeing ability in terms of intelligence analysis that, you know, that could give autocracies an advantage against us? And so, you know, I think this is one of the most important issues for us to attend to, because I think unlike the positive benefits, which take work, but the wind is at our back.
[0:40:16] This is very serious, and I'm not sure it's going to go right. Very quickly, because a couple people want to jump in. Is the fear that AI in the hands of a dictatorship is more useful and powerful and entrenches them more than AI in the hands of democracy, or that there is something about the nature of the technology that creates instability that then leads to likely dictatorship? I think both. I'm worried. I think both about...
[0:40:41] Kind of the international side of things, like will autocracies get ahead of us? Will they be able to do this better than us? And I worry about internal constitution as well. So, you know, one worry I have is AI stabilizing to autocracies and destabilizing to democracies. I think we can fight that.
[0:41:01] Some of the ideas I've had, and probably over the coming year, we as an individual company will work to try and promote these, is can AI improve the quality of democratic governance? One area is public services. Many public services are not delivered in a technologically sophisticated way.
[0:41:21] Can we use AI to reinvent democracy, to inspire citizens that their government is doing things, I guess, efficiently, to use the modern language, but is also delivering robust services and making their lives better?
[0:41:38] Can it do better at enforcing and augmenting people's lives? Can it lead to better deliberative decision making? About a year ago, we did some research with something called the Collective Intelligence Project, which was focused on...
[0:41:54] Can AI allow people to debate and discuss with each other and come to the truth better? Can it summarize positions? Can it encourage better processes of democratic deliberation? Can AI be involved in the system of justice? Again, we have to be careful with that, but can it be done in a way that enables us to
[0:42:20] Give the same rights to everyone in a more uniform way, right? Can AI enhance the promises that democracies make to their citizens in order to do a better job of kind of delivering on the ideals that democracy represents? All right, Ruth? I think there's so much important content in what Dari said. I just want to double click and do a couple of points.
[0:42:48] It's imperative that the West stays ahead, that the US stays ahead with all that we're doing with AI. Because the best approach is to have the strongest defense be ahead. And that's what we've done as an example with cybersecurity. You need to be ahead of those who might want to disrupt, take things down, and attack in the wrong way.
[0:43:12] And so that requires a pro-innovation regulatory environment that doesn't put sand in the gears. We need to be bold and responsible, but we need to make sure that we have the ability to maintain the lead currently. I think the U.S. is ahead in models by at least a year, in chips by at least a year. But if we were here a couple of years ago, that gap was wider. It is narrowing, and we cannot take for granted that we will continue to be in the lead. That is point number one. Point number two is a geopolitical point. And I would say there's an issue that's actually present here.
[0:43:41] What I didn't say is they want to work with...
[0:43:53] Companies in the US, they want to be aligned with the West, the values, the products, the services, the uplift that we provide. But they're also very clear that in the absence of us being there, they will be part of the digital transformation, and they will partner elsewhere. And so I think it's imperative when we think about, for example, US policy, the AI diffusion rule that came out a couple of weeks ago. How can we engage and work with our allies globally? It's about the technical infrastructure that enables the product solutions that reflect
[0:44:22] Western values. It's about the education that you can then also provide. So I think those are really key. And I absolutely agree with Dario that we should each see anyone running the public sector. There's a massive opportunity to deliver better services.
[0:44:39] More efficiently in a way that says we are working for you. And the number of examples in provisioning service, doing it around the globe where you can respond in a more timely way to needs, whether it's payments, whether it's information that says we are working for you and we are doing it efficiently. And one of my favorite stats that has actually
[0:45:04] A bunch of lessons that come out of it is Google 20 years ago started on this journey of Google Translate. We now translate in 260 languages. We added 110 languages in the last six months alone as a result of AI. The point is, wherever we are, even, for example, in the state of Minnesota in the United States, when they said we want to be more productive,
[0:45:27] They asked us to deliver these services and solutions initially in four languages. They then added 26 more languages. We are there to serve. The other point is it's a vertical lift. So it underscores this 260 languages, 110 in the last six months. Anybody who's on the front foot of leading a company or a country, you need to move fast because that's what AI is doing. And if we're not, the other guys are.
[0:45:50] All right, we're out of time. But Mark, I want you to give one final thought to wrap up how we're going to save Western democracy here. Well, I would say that AI on balance is very good news for the Western democracy because it gives you access to a huge...
[0:46:03] Fund of wisdom and information. And many of my friends have shut off Google and are just using AI tools, even as a search engine, to get to the latest insights, etc. So I do believe we can be generally optimistic. The reason why voters are not any longer voting for the centrist parties and are flocking to the extreme right and extreme left wing is because the centrist parties, the liberals and the Christian Democrats and the Social Democrats,
[0:46:27] have not given answers to the two biggest issues of this time, and that is migration, one, and two, how to rebalance climate change with making sure that our economies stay competitive. And if we don't do that, and the centrist parties are not allowing for answers to these questions, then it is not the voters turning in the wrong way, it is the centrist parties delivering a bad deal. And this has nothing to do with AI, this is just basic politics. You have to deal with the issues the voters want you to deal with.
[0:46:56] All right, thank you very much. Fabulous panel, fabulous discussion, lots of big topics. Thank you all, and now let's go have lunch.