Bill Gates' Joke At Davos Leaves Crowd In Splits, Says 'Trump's A Complicated Topic'

I'm very excited about what the US can do with AI. I told the person who runs the NHS, Wes Streeter, if they use AI properly, that alone might get them re-elected. Because the current citizen expectation that the NHS waiting lists will be cleared and that they'll have cheerful doctors who don't feel overloaded, there's zero expectation for that. And yet, I believe if during their mandate there is enough time to really get that going. You should tell President Trump that. Tell him what? I don't know. That if they do this right, he'll get re-elected, maybe, if he thinks so. OK, he's not supposed to run again. I mean the Republicans. And he hasn't ruled it out. Anyway, that's a complicated topic. Dedicate a whole AI cluster to optimization there. So things look a little bit different, but the potential is absolutely the same. The rich world is going to be more regulated, because the bar that you're comparing to. But even so, doctors are seeing today that when patients walk in, they've already talked to the AI. And so you're going to end up with the AI that the patient talks to and the AI for the health care system. In countries like Rwanda, we'd like to start off where it's not two systems. That if the patient's talking to the AI, then as they come into the clinic, that summary goes to the doctor. The transcript comes back. So it's always available to them to ask more questions to, even when they're not in the health system. And there's an opportunity to show a deep level of integration right from the very beginning. It strikes me, Peter, when Bill talks about doctors and how many Africans will not even see a doctor. If we were having this conversation in the US focused around our country, it would be AI is coming for my job. Radiologists are freaking out. There's not going to be a need for radiologists. And in the developed world and low middle income world, it's the opposite, where with the shortage of health care workers, doctors and nurses, AI can really be a solution here. Absolutely. The reverse. We face this issue with there are well over a million Sudanese refugees in Chad. And we had set up mobile clinics with the government of Chad to go into these refugee camps and do screening for TB. Because frankly, whenever you get situations with large numbers of displaced people, you end up with TB. And the question is not replacing any radiologists. There were no radiologists. And so if you want the screening to be interpreted, there is no alternative. So in some ways, I think one of the reasons this may well take off faster in low and middle income countries is because there won't be the resistance from people who say, this is taking my job, and I don't want to change the way we do things. Because in fact, it's compensating for the fact that those people don't exist. But I want to pick up on the horizontal point that Bill made, which is one thing many medical systems in low and middle income countries have excelled at is creating paperwork. There is an enormous amount in many health care systems of literally paper records with carbon copies and all this kind of stuff. And that makes it very difficult to capture, because it's on paper. It also just creates an enormous amount of time for overstretched health care workers. Do you mean like records, patient records? Oh, if you've ever gone to, you'll go to some village, and the community health worker will proudly take out a big kind of thing like this. And they've carefully written in the name of each patient and what they had and all this kind of stuff. And then you think to yourself, well, A, that took quite a long time. But B, how is that captured in any kind of national disease surveillance system or so? And the big difference is that now in Rwanda, your community health workers have an app on their phone. It has the details of the patient. They put it in. It's all recorded. They can look at what happened last time. They don't have to go back through the files. And also, from a national point of view, that data that's being inputted by the community health worker is being captured. So your community health worker, you've got like 60,000? They become, they are your disease surveillance system. And that's incredibly powerful. And then once you've got that kind of level of data capture, you can be applying AI tools for pattern recognition of all sorts of ways of detecting perturbations. This region is seeing something slightly different we didn't expect. So those taking paper out of the system, capturing the data, I think is, that's an incredibly powerful. Can you do that? Can you guys at the Global Fund go and take all those paper stacks and make them digitized? We're certainly investing in it. I would say that different countries are at very different states in terms of where they are on that pathway. But we do face a challenge, right? There's less money than there was. I mean, that is the reality. And a lot of the money that was being invested in things like disease surveillance has stopped. Like recently? Yeah. Why? Well, because major donors around the world have reduced. Present company excluded, right? Well, it's actually quite broad based. We've seen quite a lot of donors reducing funding quite significantly. And that means that the investors, and we face a challenge, which is that, and let me put this in perspective. We've actually just had our AIDS replenishment. We've just raised just under $12 billion, with some donors still to go. Actually, that shows remarkable commitment in this context by the donors who support the Global Fund. But we are going to be allocating less money to countries. And they have had sharper reductions from other sources. So countries are going to face some very difficult choices. Do they invest in underlying system things like disease surveillance and laboratories? Or do they invest in basic life-saving things like first-line treatment of malaria, keeping people on antiretrovirals? And so there will be some very difficult trade-offs there. But I think the thing that's exciting about AI is it allows us to kind of change the equation a bit and maybe get quantum leaps in efficiency and effectiveness that means we get, in a sense, more bang for the buck. And that's what we've got to be. We've got to be really focused, not on the cool tools so much as the, where can we really disproportionately have greater impact? Bill, the funding, is it governments pulling back? What is going on in that environment? Yeah, almost the top givers to global health have all reduced the amount they give. And so, you know, Gabi raised, which does fundraising every five years. They were in Brussels in June for the replenishment hosted by us and Ursula von der Leyen. And we raised, we were down over 20%. Global Fund, actually, we were worried it would be even worse. And so things went better than we expected, but it's still less money. And so the Global Fund board sits there and says, how much do we cut TB versus malaria versus HIV? And that's the situation we find ourselves in. And this has real impact. From 2000 to 2024, we had record reductions in childhood death, much faster than ever in history. In 2025, for the first time, more children died than the year before. 4.8 million versus 4.6 million. And, you know, that's because donors cut money. And if you can't, and some of them cut in a very abrupt, unexpected way that really disrupted things like getting malaria chemoprophylaxis out, getting bed nets out. And so we're, you know, we're dependent on these donors. As Peter said, AI is going to help us do more with less. The overhang is not just the development assistance cut, but also the indebtedness of the African countries. You know, they are paying more in interest than they paid to run their healthcare system. So this is the first time that their net interest costs are very high. And in the past, when this has been the case, there have been debt relief. And, you know, whether the world cares enough and will prioritize that with so many challenges going on, that is very difficult. So the story of the miracle of global health and the very positive story of innovation, including AI, we have to do a better job, you know, getting the voters in these countries to be proud of what they've done. And in the face of very tight budgets, to maintain what is, you know, less than all but the top 10 donors, it's less than 1% of their budget. So in the U.S., it's well under 1% of the U.S. budget. And yet, you know, we've forgotten how to make that case to get people out to see it, to show them the efficiency that, you know, we provide for every dollar that they donate.