The challenges of prediction | Nobel Prize Dialogue Tokyo 2025 | The Future of Life

Let's just start by how hard it is to predict the future. Ada, your work, Unraveling the Structure of the Ribosome, took an awfully long time. Did you have an idea of how long it might take and what the results might be? Honestly, no. I hope that I can progress the knowledge. I did not really expect to solve all the problems, the entire problem. So you set out on a problem you didn't think you were actually going to be able to solve? Well, I didn't predict myself to solve, but I thought that I will provide the world with the tools that could be used for solving. And I thought that if I'm young enough, and I was at that time, maybe I will reach it myself, but I couldn't even dream about it. Well, that's interesting. So you set out on a course hoping that you might get somewhere, you might help along the way, but not knowing exactly what the result will be? Sure. If I knew the result, I didn't have to work. Quite so. Bill, you work especially with quantum mechanics. If we turn to quantum mechanics, there's a field where no one ever predicted what the future might hold. Yes, I think that's right. This year, as you know, we're celebrating the International Year of Science and Technology. It's 100 years after the beginning of what we now call quantum mechanics, with the development by Heisenberg of matrix mechanics and Schrodinger of wave mechanics. But thinking about if you'd ask this question, this kind of question to people like Heisenberg and Schrodinger, what will quantum mechanics lead to? I'm sure they would have given answers like, well, it will help us understand the structure of atoms better. We'll understand something about the structure of molecules better. We might even be able to learn a little bit about how chemistry works by understanding things at the microscopic level. I cannot imagine they would have predicted mobile phones, that they would have predicted the entire range of semiconductor electronics that we have today that has transformed the lives of almost everyone on earth. I can't imagine they would have been able to foresee that. In my own experience as a boy, I can remember people that predicted by now, all of us would have our own personal rocket ships, and we would commute to work using them. No one was thinking that we would have the ubiquity of computers, everyone having many computers in their own home. As late as the 1980s, there were computer companies that said there is no reason why anyone would ever need to have a computer in their home. That company, of course, went out of business. But they were so wrong about the predictions. I've seen it in my own career, for example. I would say all the things that were important that came out of the work that I've done were things we did not anticipate. Maki, you have an overview of all of science. You have an overview of all of science, the Japanese Institute of Science. So would you like to talk about just historically the challenge of knowing what is going to happen? Okay, so at the moment I'm serving as president or manager, I would say, to cover the five institutes for the natural sciences, including Astronomical Observatory of Japan, and some of the molecular science, and physiology, and basic biology. I remember when, I think it was in 2017, when Osumi-san got the Nobel Prize in biology field. He worked a long time in one of my institutes. People were so surprised. They were not at all ready, meaning that predicting somebody to get Nobel Prize or somebody to get a super result from science, the prediction is very, very difficult. What we all know is that we need to have various science, the basic science, to be ongoing all the time, even though we do not know what will come out from this field. And so looking for the various variety of field in natural sciences, I would say don't focus too much. We have to believe our belief in science, the scientists' belief, and let them go. So that is what I think the most important thing to encourage in natural sciences. I hope I'm answering to your question. Absolutely, you're answering. Beautiful. Thank you very much indeed. Ada, now you're back. So if I'm allowed to add a little bit, ribosome is a particle that many of it belongs to every living cell or animal or butterfly, whatever. Whatever has to live has to have a ribosome that reads the nucleic acid instructions, the genetic instructions, and produces proteins according to it. As I said, it has about 100 components. Few of them were known when I started, not all, but it was known that they exist. And how they function and how they exist and how they are was the aim of my studies. Since very, very good and known scientists tried to do it before me and failed, I thought that if I also fail, it's not so bad. I will be as good as those that already did not reach it. But I expected to move a step or a few steps further. It took 20 years, but we solved the whole problem. And it's correct for every living cell. So I'm very proud of it, but it's not my pride that matters. It's what it added to science. And since then, several groups, several institutes went into studying other larger proteins, larger ribosomes, smaller ribosomes, ribosomes of bacteria, ribosomes of elephants. And there is a lot of progress in this matter. I don't think I have to give a lecture now about all what you do is knowing the ribosomes, but at least ribosomes are known. Thank you very much indeed. All three of you have set the scene very nicely, that basically you need to allow basic science to flourish in all sorts of different directions, and it's hard to predict when things will be known, and it's hard to predict what the benefit of knowing those things will be. Nevertheless, those that are providing the science funding and society in general wishes to get results from it. They wish challenges to be solved. They want to move forward. So there has to be some kind of roadmap and decisions about what gets funded and what doesn't get funded. And this also fits very much into the challenge of prediction. So, Maki, would you like to start? I mean, you do need a roadmap for funding. You do need a roadmap for science. How do you create a roadmap against a backdrop of basically not quite knowing what's going to come to fruition, what's going to be successful? I would say that roadmap should be necessary, but it shouldn't be so strict. The portion between the basic science part and the focusing part is very important. To my understanding, if you want to have a fruitful harvesting, for instance, you're not just putting some seed to a specific place, but before that, you have to make the soil comfortable to grow the plant. Maybe you need to bring in the water. Maybe you have to structure the land. So this kind of basic environmental structuring is very important. Maybe science is not equal to the agriculture, but I think it's quite similar. We have to have a reasonable environment, reasonable condition, and reasonable people to work in this society. And so preparing for this environmental issue is the most important thing. And then the second important thing to look into the roadmap is you have to look into the people who are making the growth a little bit quicker than the other. Then you can just push a little bit to these areas, but don't forget to feed the other area simultaneously, because that will be the next harvesting candidate. So writing a clear roadmap for what comes next is not easy. But to have this kind of structured roadmap consideration, I think that is quite important. The people usually, especially in our country, people are eager to catch up with the other countries. We are very good at looking for something to catch up with, but we are not very familiar with leading the community. So if you come close to the top, the people start, let's see, this is quite good. So let's look for something that is not good yet. So every time we think that somebody is coming to the top is not sufficiently feeded, but somebody behind will be the winner of this roadmap. And this is not good for Japanese point of view. And I would like to encourage the Japanese people how to make a realistic roadmap that will push the top of the top to the top. The analogy of, if you like, tending the garden is a really beautiful one for nurturing science. Thank you very much indeed. Bill, would you like to comment on this? Yes. Well, I think that you've articulated very clearly the importance and the challenge of figuring out how to fund science. And you have to have support for fundamental science where you have no idea what the results will be. Because if you don't fund those kinds of things, long-term progress will never happen. And you also have to fund near-term problems where it's clear that you need solutions to these problems now. And I'm troubled to think that perhaps the best way of doing that is to have people in charge who have vision. Now, the trouble is that's a very difficult thing to guarantee that people should have vision. In the United States, there is a committee on science as part of the Congress. And in the room where they meet, on the wall is written, without vision, the people perish. So somebody had enough vision to write that on the wall. Now, whether you can learn how to accomplish that, I don't know. My late great laboratory director, Catherine Gebby, was the overseer of four Nobel Prizes in her organization during a relatively short period of time. And people often asked her, what is your secret? And she said, hire the best people. Give them the resources they need and get out of their way. Now, a lot of people will say that. She actually did. Please, Ada, yes. So I'm trying now to say, why did I go into this area or this field that was known to be impossible? It's because I had a problem. I had an accident. It doesn't matter. I found a pamphlet of one of the air companies that says that they are going to the North Pole in the winter. This was the name of this article. And they say that in the North Pole, in the winter, there are no life being evolving. The bears are waiting for the summer in order to make families. The polar bears. The polar bears, of course, in the North Pole. And I thought, why does it happen? Because I had time, I had my accident, so I had time to do less active work. I thought that this happens because in the winter, the chances of staying alive of the little babies, if they are made, are very low. So the bears are already stopping the production of the new little bears. It was correct. I found out that if I take any cells and cool them to minus 10, minus 5 degrees Celsius, the cells stop growing, but they don't die. They stay. So I thought this is what the bears are doing in the winter. But I didn't really want to work on winter bears and killing bears in order to understand ribosomes. This was too much. I looked for other conditions. In Israel, there is a sea. In Israel, it's called the salty sea. In the world, it's called the Dead Sea. It's not fully dead. There are two types of bacteria living there, but they don't function very well in the salty water. I thought I should focus on them. It's much easier than bears. I don't have to wait for winters and so on. This was the way to go. It shows that inspiration comes from everywhere in the garden. You never know where the ideas are going to arise from. In research, you have to keep everything flourishing. Another thing that I think this shows is that you often learn something new when you go to the extremes. That's what you were looking for. Afterwards, after a few years, over 10 years, I went to atomic piles and went to the sewage of the atomic piles and found bacteria there that I could stop and look at their ribosomes. Life everywhere. Bill, everybody's outlining a very lovely scenario for science where you let things flourish and you get out of the way of good people and just hope it will happen. Actually, that's not how it happens. The National Academy of Sciences produces five-year plans. How do you square the desire just to let it all be and the need to direct? It's a difficult thing. You mentioned the National Academy of Science coming up with these often reports. We do them every 10 years. I've been involved in a number of them. We've never been able to predict the most important things that were going to happen in the future. That didn't mean that we didn't have some perspective about what was hot, what was developing. It's just important to understand it's not the whole picture. I guess the answer is you do the best you can. You're not going to do a very good job of prediction, but that doesn't mean you shouldn't try because you need to give some direction. This kind of flexible roadmap that you've described, it has to begin someplace. What about the desire for society to see things solved, to see a result from the science? Maki, people are clamouring for solutions to problems now. What would you say to people who say, come on, where are the results? I think this is my understanding. The social problems are quite clear, but the way how to solve this is not seriously determined. There are many routes of solving things. Of course, science and technology can contribute to solving these problems, but I think the new invention is somehow a little bit more deep and it does not come directly to the social solution, but it grows to become one of the solutions. If we want to solve the social problem immediately, what science and technology can do is, to my understanding, there are many known science and technologies. In order to apply these science and technology to the solution, I think we need to think about how the private sector or government will choose the answer. Sometimes, it costs a lot. If you just think about cost performance, they just throw it away and then some of the solution may not be resolved. We have to be very careful. The scientists can give some answer, but what to select and what to put into the social activity is somehow the government or the private sector's people's decision matters a lot. Up to some point, we scientists can contribute, but finally, I think the decision of the government or the decision of the private sector, this pays for the human beings or does it pay for their benefit and they think they have to choose. Time goes quickly. We have just a short time, so Bill, please. I think it's really important for scientists to tell the stories. In addition to saying how wonderful our latest results are, it's a good idea for us to tell the stories. It's one of the reasons why UNESCO declared the International Year of Quantum Science and Technology, to give us a chance to emphasize the stories about how basic fundamental research led to wonderful results. One of the stories I love to tell is about how when Einstein's theory of gravity came out, it was declared that only three people in the world understood it. If the engineers who developed the satellite navigation system had not understood it, it wouldn't have worked. So something that was completely useless 110 years ago became essential to something that we use every day. It's such an important point and it's something we will come back to later, especially in the afternoon, this idea of bringing society with science, the smooth communication of what is happening at the bench to society at large. It's such an important point. Thank you very much indeed. Adra, I'm going to turn to you for a last comment. What do you think people should bear in mind today as they think about how science and technology might change life? That's a big question. It's a big question. The answer is even bigger and not known to me. But on the surface of it, a scientist that has an idea which is not completely crazy, only partially crazy, should be acknowledged and maybe even addressed and supported. Thank you very much indeed. Thank you to all my panel. It's been a joy talking to you and to start this conversation off today. Thank you. Thank you, Adam.