白宫反科学吗？对话 OSTP 主任迈克尔·克拉齐奥斯

Michael Kratsios，欢迎来到 All-In Interview。

Michael Kratsios, welcome to the All-In Interview.

谢谢邀请。很高兴来到这里。

Thank you for having me. Excited to be here.

你是白宫科技政策办公室主任。能简单介绍一下这个职位是做什么的吗？你在这里做什么？

So, you are the director of the Office of Science and Technology Policy here at the White House. Can you just tell me a little bit about what that role is? What do you do here?

好的。科技政策办公室成立于 60 年代，负责协调整个政府的科技政策。美国很独特的一点是，我们没有专门负责科学技术的部门。我们有很多机构分别承担科技事业的一部分。我们有国家科学基金会做基础研究。我们有能源部管理国家实验室。战争部有广泛的研发项目，比如 DARPA。所以，白宫或整个政府中唯一能协调所有这些努力的办公室，就是我领导的这个叫 OSTP 的办公室。我们要做的是与总统合作制定国家科技议程，然后最终在所有机构中实施。

Yeah. So the Office of Science and Technology Policy was created in the 60s to coordinate science and tech policy across the administration. So very unique to the US is that we don't have an agency that does science and technology. We have lots of agencies that do pieces of the science and technology enterprise. We have a National Science Foundation that does basic research. We have a Department of Energy that runs our national labs. The Department of War has extensive R&D programs like DARPA for example. So the one office in the White House or in the administration broadly that's able to coordinate all those efforts is the office that I run called OSTP. And we try to do is work with the president to set the national S&T agenda and then ultimately implement that across all of our agencies.

你之前也担任过这个职位，对吗？

And you had this role before. Is that right?

上一届政府中，我是美国首席技术官。所以，如果你看 OSTP，它既管科学也管技术。在特朗普第一任期，我负责总统的技术事务。

So last administration I was the chief technology officer of the United States. So, if you think about OSTP, it does science and it does tech. And in Trump one, I ran the tech portfolio for the president.

那么，我先问你，这届政府反科学吗？

So, let me kick off by asking you, is this administration anti-science?

这届政府并不反科学。我最自豪的一件事是几周前发布了一份新报告，叫《科学，新黄金时代》。我认为任何读过这份报告的人，最可能看到的是，这届政府深切关心美国的科学和技术事业。我们真的希望美国成为下一个伟大科学发现的故乡。我们希望赋能年轻科学家。我们希望创造一个生态系统，让我们最伟大的科学家在美国各地研究最困难的问题。对我们来说，我们正在尽一切努力，像我刚才提到的，协调所有机构，帮助实现这一目标。

It is not anti-science. I think one of the things that I'm most proud of is the release of a new report a couple weeks ago called Science, a New Golden Age. And I think anyone who reads that report, I think what we will most likely see is an administration that deeply cares about the American science and technology enterprise. We really want the US to be the home for the next great scientific discoveries. We want to empower young scientists. We want to create an ecosystem that allows our greatest scientists to work on the hardest problems everywhere in the US. And to us, we're doing everything we can to align all of our agencies like I just mentioned to be able to help make that a reality.

但回到刚才，我要给你看一份来自《自然》杂志的民调，那是科学期刊之一。他们调查了 2000 名读者，都是科学家。根据民调，86% 的人在选举中支持卡玛拉·哈里斯，唐纳德·特朗普只有 6%。为什么会这样？总统和这届政府被视为反科学的看法是怎么回事？

But going back, there's a poll I'm going to give you from Nature, which is one of the scientific journals. They polled 2,000 of their readers, which are all scientists. 86% supported Kamala Harris in the election according to the poll and Donald Trump polled at 6%. Why is that? What is going on with the perception of the president and this administration as being anti-science?

对我来说，我认为科学界在过去几十年里迷失了方向。我认为美国一直是历史上一些最惊人科学变革的发生地，政府在其中许多变革中发挥了重要作用。如果我们回顾曼哈顿计划或阿波罗计划，这些是只有美国政府才能汇聚整个生态系统来实现的 seismic 事件。老实说，我认为在过去 15 或 20 年里，科学被深度政治化了。我们不再问那些非常困难和重要的问题，比如什么是科学方法？我们应该如何接近它？我们应该质疑其中一些结论吗？相反，我认为它被某种教条所主导。我认为它在新冠期间达到了高潮和顶峰，突然之间，有某个特定的人，如果你不同意他说的话，那么突然之间你就是反科学。对我来说，我认为这是你能得出的最反科学的结论。我真的认为我们必须回归基础。这就是这届政府正在努力做的。

To me, I think the scientific community has lost its way over the last few decades. I think America has been the place of some of the most amazing scientific transformations in history and the government has played an important role in a lot of them. If we look back and think about the Manhattan Project or Apollo, these are sort of seismic events that only the US government could bring together the ecosystem to achieve. And to be honest, I think over the last 15 or 20 years, I think science has been deeply politicized. And we no longer are asking sort of the very hard and important questions of, you know, what is a scientific method? How should we be approaching it? Should we be questioning some of these conclusions? And rather, I think it's been dominated by kind of this dogma. And I think it really crescendoed and peaked in COVID where suddenly, you know, there was a certain individual that if you didn't agree with what he said, then suddenly you were anti-science. And to me, I think that is the most anti-science conclusion you could ever make. And I really think we have to return back to the basics. And that's what we're trying to do in this administration.

是的。我的意思是，对于在座许多可能不熟悉的观众来说，你所说的科学方法的基础是，你提出问题，科学的过程就是提问和探究的过程，这种探究导致实验，收集数据，数据为你的观点提供依据，然后你继续提问。认为科学是权威的观念几乎与科学方法的基础——持续探究——相悖。这是

Yeah. I mean at the basis of what you call the scientific method for many people here who might be watching that aren't familiar it's like you ask questions the process of science is a process of asking questions and inquiry and that inquiry leads to experiments which collect data and that data is what informs your view and then you continue to ask questions. The idea that science is authority is almost antithetical to the basis of the scientific method which is constant inquiry. Is that

我完全同意，我认为我们作为政府几十年来没有付出努力或花时间去做的是，将科学方法的同样原则应用到我们政府处理科学政策的方式以及我们处理研发的方式上。现在，如果你和科学界的中位数游说者谈谈，他们唯一痴迷的就是研发预算。如果数字不增加，他们就没有做好工作，就没有所谓的支持科学。对我来说，这是一个问题。但每个科学家应该问的更重要的问题是，美国政府每年在科技资助上花费 2000 亿美元的方式，是否真的在推动美国人民最好的突破和最大的突破？有没有其他方式，你可以通过不同的时间跨度，将资金部署到不同的组织、不同的科学家？我们应该问的问题太多了，但我们没有问。这就是《科学：新黄金时代》试图提出的。

I could not agree more and I think what we as a government for many many decades have not taken the effort or the time to do is to apply those same principles of the scientific method to the way that we as a government approach science policy and the way that we approach research and development. Right now if you talk to sort of your median lobbyists for the science community, the only thing that they are fixated on is singularly the research and development budget. If the number doesn't go up, then they haven't done their job and they haven't quote unquote supported science. And to me, that's a question. But the more important question that every scientist should be asking is, is the way that the US government spends at $200 billion in S&T funding every year, is it actually driving the best breakthroughs and biggest breakthroughs of the American people? Are there other ways that you could be deploying that capital in different to different organizations to different scientists through different time horizons? There's so many questions we should be asking which we're not. And that is what Science: A New Golden Age tries to bring to the front.

所以，我从我的科学家朋友、研究人员那里听到很多，他们在学术界、私营企业和其他地方工作，有一种看法认为这届政府、这届政府在削减科学经费。听起来你说的是，资源可能从某些事情重新分配到其他事情上，这是你看待这个问题的方式。

So, I've heard this a lot from my friends who are scientists, who are researchers, who work in both the academic community, private industry, and elsewhere that there's a perception that this government, this administration is cutting science funding. And it sounds like what you're saying is that there's an allocation of resources perhaps away from some things into other things as kind of the way that you're viewing this.

是的。我认为人们首先应该摆到桌面上的最重要的事情是，拟议预算和国会拨款之间存在区别。所以国会控制着钱袋子。

Yeah. I think the most important thing that people should initially sort of table set is that there's a distinction between a proposed budget and the dollars that are appropriated by Congress. So Congress controls the purse strings.

他们决定科学资助的规模，而且在过去十多年里一直持续资助科学。但我认为更值得思考的政策问题是——我的看法是——把钱花在错误的事情上并不是正确的政策行动。

They're the ones who say how much science funding there will be, and they've consistently continued to fund science over the last decade plus. But I think the more sort of policy question to think about is—and the way I view it is—spending more money on the wrong types of things is not the right policy action.

能举个例子吗？

What's an example of that?

对我来说，我认为——

So to me I think—

抱歉，我插一句，就像 2025 年这届政府打乱、冻结或终止了 30 亿美元的活跃拨款中未使用的资金。

Sorry, cuz I'll just say like in 2025 this administration disrupted, froze, or terminated $3 billion in unspent funds on active grants.

是的。

Yeah.

所以你们终止了科学家或实验室已经获得或获批的拨款。也许你可以给我们举个例子。那 30 亿美元是什么，还有哪些其他项目你们政府会说并不是真正该投的地方？

And so you terminated grants that scientists or labs had received or gotten approval for. And so maybe you could just give us an example. What were those three billion and what were some of these other things that your administration would say are not really the right place?

说得好。对我来说，最好的例子是国家科学基金会。对有些听众来说，NSF 本质上是美国校外基础研究的首要资助机构。他们每年大约有 80 到 90 亿美元，其中大部分资金给了大学里从事各种基础科学领域研究的学者。参议员泰德·克鲁兹和参议院委员会对拜登政府期间发放的拨款做了分析，他们发现那段时间 NSF 大约四分之一，也就是 25% 的拨款流向了 DEI 相关的所谓科学。你想想看，这是天文数字。那大约是每年 20 亿美元乘以四年。那就是 80 亿美元的科学资助流向了这些 DEI 相关的倡议。那不是科学，也不应该是。那是科学政治化的纯粹表现，拜登政府站出来说：‘哦，如果你想赢得拨款，你必须确保在申请中谈到一些 DEI 相关的因素。那是我们给你钱的唯一方式。’这显然不是我们应该做的。那不是黄金标准的科学。

That's a good point. To me, I think the best example is the National Science Foundation. And for some of the listeners, the NSF is essentially the premier funder of extramural basic research in the United States. So they have about 8 to 9 billion a year, where most of that money is given to academics at universities who do research on all sorts of basic science domains. Senator Ted Cruz and the committee in the Senate did an analysis of the grants that were given during the Biden administration, and they found that roughly one quarter, or 25%, of grants at NSF during that time period went towards DEI-related quote-unquote science. And if you think about that, that's an astronomical amount. That is roughly $2 billion a year times four years. That's $8 billion of science funding that went to these DEI-related initiatives. And that isn't science, and that shouldn't be. And that's a pure manifestation of the politicization of science, where you had the Biden administration stand up and say, 'Oh, you know, if you want to win a grant, you have to make sure that you talk about some DEI-related factor in your application. That's the only way we're going to give you money.' And that obviously is not the way we should be doing it. And that is not gold standard science.

还有对气候科学研究的削减。这一点在媒体和广泛的科学界代表、期刊、协会等中受到了深刻批评。你能简要说明政府的观点吗：人为气候变化有多确定，即气候因人类行为并向大气排放碳而发生变化，以及其严重性？这是气候紧急情况吗？我们知道什么？不知道什么？为什么资金被从那些研究工作中转移走？

There was also cuts to climate science research. And this is one that's been deeply criticized in media and by broad kind of scientific community representation, journals, associations, and whatnot. Can you just frame up the administration's view on how settled is anthropogenic climate change, meaning the climate is changing because of human action and releasing carbon into the atmosphere and the criticality of that? Is it a climate emergency? And what do we know? What do we not know? And why are dollars being redirected away from those research efforts?

赖特部长在这方面非常直言不讳，在政府中算是许多这类问题的核心人物。他公开倡导并多次表示，是的，气候正在变化，是的，人类在过去一百年里燃烧了化石燃料，这导致了环境中的二氧化碳增加。不真实且数据不支持的是，这是气候紧急情况。我认为最好的例子之一就是这些 RCP 8.5 情景。这些是气候科学家试图估算所谓气候变化对世界影响的情景。这是最极端的情景，曾出现在许多国家气候评估中，也由 IPCC 运行。最终他们几个月前认定，他们无法以任何科学诚信来证实继续让这种情景上演。所以他们不得不撤下它。所以对我来说，我认为——

Secretary Wright has been very vocal on this and kind of serves as the belly button for a lot of these issues in the administration, and what he has advocated for very publicly and has said many, many times is that yes, the climate is changing, and yes, humans have burned fossil fuels over the last hundred years and that has contributed to CO2 in the environment. The thing that is not true and what the data does not support is that it is a climate emergency. And I think one of the best examples of that is what's happened with these RCP 8.5 scenarios. So these are scenarios that climate scientists try to estimate the impact of this quote-unquote climate change will have on the world. And this was the most extreme scenario that had been in numerous national climate assessments and run by the IPCC as well. And ultimately they determined a few months ago that they could not with any scientific integrity substantiate continuing to have this scenario play out. So they had to pull it down. So to me I think what—

这就是很多媒体、很多报道和很多重复报道所依据的，很多资金也基于这种未来的模拟，而这种模拟并未成真，并未发生。

And this is what a lot of media and a lot of coverage and a lot of re-reporting was based on, a lot of funding was based on this simulation of the future that did not come to bear, that did not happen.

正是如此。我认为这是一种疯狂的叙事，他们抛出了这个极端情景，大多数人认为永远不会发生，而今年证明它永远不会发生，因为他们甚至从所有预测中删除了它。然而过去 20 年每一次气候评估的每一篇媒体报道总是聚焦于极端例子。那是媒体盯住的，那是吸引所有这些人的注意力的。我认为这对科学是一种真正的伤害。

Precisely. And I think it's this crazy narrative that kind of spun around where they threw in this extreme scenario, which most people believe would never happen, and now this year proven that it will never happen because they even removed it from all their predictions. Yet every media report of every climate assessment over the last 20 years has always focused on the extreme example. That's the one that the media fixates on, and that's what sort of captivates the attention of all these folks. And I think that's kind of a real disservice to science.

所以在过去十年到二十年，大约 15 年左右，这就是为什么大量资金涌入气候研究、气候科学，而终止拨款、削减预算是一种回滚。是这么理解吗？

So over the last decade to two decades, one 15 years or so, is that why a lot of funding has rolled into climate research, climate science, and terminating grants, reducing budgets is kind of a roll back. Is that the way to think about?

我认为我们喜欢这样看：我们希望投资于最终将为美国人创造丰富能源的技术和科学，这是你大力倡导并谈论我们必须赢的。我们必须赢得这场聚变竞赛。例如，我们为此设定了 2035 年的目标。在核能方面，我们一直是这个国家历史上最前瞻的政府之一，我们正试图尽快让它加速运行，为美国人供应能源。所以对我们来说，技术将对普通美国人产生最大影响。

I think the way we like to view it is that we want to be investing in the technologies and the science which are ultimately going to create abundant energy for Americans, something that you advocate a lot for and you talk about we have to win. We have to win this fusion race. We set a target for 2035, for example, for that. We have been one of the most forward-leaning administrations in the history of this country on nuclear energy, and we're trying to get that up to speed and running and supplying energy for Americans as soon as humanly possible. So to us, I think technology is what's going to have the biggest impact for everyday Americans.

是的。我想提出两点。一是中国向大气排放的碳超过世界其他地区，所以美国加减 50% 并不会真正改变大局。那么可以说有一个问题：这值得付出经济代价吗？特别是因为它主要影响较贫困的社区，而富裕社区能负担替代品，但失去某些能源来源的较贫困社区却要付出最多。

Yeah. I mean I would make two arguments. One is China's output of carbon into the atmosphere eclipses the rest of the world, and so plus or minus 50% in the US doesn't really move the needle. So then there's arguably a question like is it worth the economic cost, particularly because it mostly impacts the poorer communities than the wealthy communities can afford alternatives, but poorer communities that lose access to certain sources of energy they have to pay the most.

绝对如此。我看到的数字是，全球大约有 20 亿人在家中使用非常肮脏的燃料做饭，比如木材、粪便或木炭。这导致——联合国报告称——每年大约 300 万人因此死亡。而这些人正是清洁化石燃料可以对其生活质量和整体状况产生巨大影响的人群。所以如果我们能加速转向替代能源，可以说并不一定需要政府来实现。在某些情况下，你需要像聚变这样的技术突破，但太阳能、电池备份——我的意思是，有如此强烈的经济激励，它更便宜、更容易、可部署，市场正在——

Absolutely. I think the numbers that I've seen, roughly two billion people around the world use this very dirty fuel for cooking in their homes, things like wood or dung or charcoal. And this leads, I mean, the UN has reported leads to roughly 3 million deaths every year because of this. And these are the people where clean fossil fuel could make a huge difference in their quality of life and overall. And so if we can accelerate through to alternative energy sources, which arguably you don't necessarily need the government to make happen. In some cases you need to have technical breakthroughs like fusion, but solar, battery backup—I mean there's such a strong economic incentive, it's cheaper, it's easier, it's deployable, that the market is kind of getting—

自行解决那个问题。

Solving that problem on its own.

关键在于解决问题——你可以相信碳排放会导致气候变化。你可以相信世界正在变暖，但你也可以认为，解决这个问题的最佳方式不一定是倒退 30 年或 40 年，而是向前发展，用新技术取代碳，而不是强制推行、让东西变得更贵，那会让人们很难适应。

That's what matters in solving — you can believe that carbon going into the atmosphere can cause climate change. You can believe that the world is getting warmer, but you can also argue that the best way to solve that problem isn't necessarily to go backwards by 30 years or 40 years, but to go forward with new technology that replaces carbon rather than forcing and making things more expensive, which makes it very hard for people to adapt.

完全同意。我不断回到你关于中国的观点。我的意思是，对这些被感知到的问题采取任何极端政策反应，都不可避免地会最伤害美国人，而且实际上解决不了问题，无论你相信它是否正在发生。

Absolutely. And I keep going back to your point about China. I mean, any of these extreme policy reactions to this perceived problem would inevitably hurt Americans the most and not actually solve the problem, whether you believe it's happening or not.

那我们来谈谈 NIH。我想稍微聊聊美国科学进步的停滞。环顾四周，很容易说：“我们有 AI，我们有基因编辑，我们了解基因组，我们有飞行汽车。”我的意思是，所有这些都来自美国。所以，很容易认为我们作为一个国家正在取得巨大进步。我们确实作为一个国家取得了巨大进步。但如果你看 NIH 的经费——1998 年 140 亿，2003 年 270 亿，2024 年 470 亿——预算自 1998 年以来增长了两倍多，但来自这些经费的突破性疗法并没有成比例增加。有人称之为 Eroom 定律——就像摩尔定律的反向。以每美元支出的产出衡量，自 1950 年以来大约下降了 80 倍。而且每 9 年减半。所以每 9 年，我们获得投资回报的效率就减半。我想这来自你的报告，或者已经发表了。那么，美国的科学停滞了吗？到底发生了什么？

So let's talk about NIH. I want to talk a little bit about the stagnation of scientific progress in the United States. It's easy to look around and say, "We've got AI, we've got gene editing, we've got an understanding of the genome, we've got flying cars." I mean, all of this stuff came from the United States. So, I think it would be easy to argue we are making great progress as a nation. We have made great progress as a nation. But if you look at NIH funding — 1998, 14 billion; 2003, 27 billion; 2024, 47 billion — so the budget has more than tripled since 1998, but there has not been a proportional rise in breakthrough treatments coming out of that funding. Arguably people call it Eroom's law — it's like Moore's law in reverse. It's fallen roughly 80-fold since 1950 in terms of outcomes per dollar spent. And it halves every 9 years. So every 9 years we get half as efficient as we were at getting a return on the investment we're making. And I think this comes from your report or it's published. So has science stagnated in America? What the heck is going on?

总的来说，我们的论点是它确实停滞了。我认为那只是一个例子。我认为许多美国人看到、感受到并明显注意到的一个例子，也是我一直喜欢谈论的，就是飞行速度。你知道，在 1990 年代你可以乘坐协和式飞机，现在不行了。我们飞得比 10 年、20 年前还慢。我认为我们可以做得更好。我认为我们总是问的问题是：为什么会这样？在政府资助的背景下。我想你可以说：好吧，所有容易的问题都已经解决了，低垂的果实已经被摘了，所以解决下一个问题更难。当然。但我认为总体而言，问题在于我们在实际进行科学的方式上没有任何创新——无论是在 NIH、NSF 还是其他任何科学机构。答案一直是：让我们继续做同样的事情，但增加更多资金，希望按比例获得更多产出，而不是问更难的问题：我们是否有其他方式进行科学，是否有其他类型的科学家可以获得资助、获得资金，是否有其他机构可以获得资助？我认为这些是我们在《新黄金时代》中开始提出的一些问题，关于我们如何真正应该照镜子问自己：我们是否在以最聪明、最好的方式花钱？

I think generally our argument is it has. And I think that's one example. I think the one that a lot of Americans see and feel and notice quite obviously that I always like to talk about is the speed of flight. You know, in the 1990s you could fly on a Concorde and now you can't. We're flying slower than we were before, you know, 10, 20 years ago. And I think we can do much better. And I think the question we always ask is like, why is this happening? In the context of government funding. I think you could say one thing: well, look, okay, all the easy problems have already kind of been solved, sort of low-hanging fruit has been picked, so it's harder to solve the next thing. Sure. But I think broadly the issue is we have not been innovative in any way on the way that we actually conduct the science — whether it's at NIH or at NSF or at any of our other science agencies. The answer has always been let's just keep doing the same thing but add more money and hope that we get more outcomes proportionally, rather than asking the harder questions about are there other ways that we could be conducting the science, are there other types of scientists that could be getting the funding, could be getting the money, are there other institutions that could be getting the funding? And I think those are some of the questions that we start to bring up in New Golden Age about how we should really be looking in the mirror and asking ourselves, are we spending money in the smartest and best ways?

为什么我们一路走来没有这样做？当你投入更多资金时，它去了哪里，导致整体产出效率更低？

Why weren't we doing that along the way? And as you pour more money in, where does it go that makes the overall outcome less efficient?

我意识到没有动力这样做。我认为国会山的动力往往是不断增加预算，最终流向特定选区或特定州。在政府方面，没有动力去检查你的作业并揭示你所做的事情实际上效果不佳。总是很容易拿一个标题说你正在增加 XYZ 领域的资金。而实际工作相当困难。要梳理 470 亿美元的资助并弄清楚哪些有效、哪些无效并不容易。我认为这就是我们试图引入的。报告中引入了元科学的概念，我们在 NSF 和 NIH 都设立元科学部门，我们将真正开始进行实验。也许我们应该以不同的方式进行资助，然后我们可以分析这些，然后调整方向，将资金引导到真正发生创新的地方。

I realize there's no incentive to do that. I think the incentive on the Hill oftentimes is to just keep increasing budgets that ultimately flow down to particular districts or particular states. On the government side, there's no incentive to sort of check your homework and reveal that what you're doing is not actually working very well. It's always easy to take a headline that you're increasing funding in XYZ domain. And the work is actually quite hard. It's not easy to go through 47 billion dollars worth of funding and figure out what's working and what isn't. And I think that's what we try to introduce. There's this concept of meta-science that's introduced in the report where we're setting up meta-science units both at NSF and at NIH where we're actually going to start running experiments. Maybe there are different ways that we should be doing funding and then we can analyze those and then course correct and direct money towards places where innovation is actually occurring.

所以你们将开始自己做实验，研究如何分配资金，看看什么回报最高。

So you're going to start doing your own experiments on how you're allocating money to see what has the highest return.

正是。

Exactly.

你如何衡量？

How do you measure that?

嗯，我认为你首先要弄清楚你想进行哪些实验。举个例子，在 NSF，几乎所有资助都采用非常标准的典型格式。有一组同行评审员进行这种基于优绩的评审。可能是来自特定领域的三四个人。他们拿到所有申请，进行评审，然后作为一个小组选出他们认为最有价值的。你知道，有人可能会说这当然是基于优绩的，但它也常常激励科学家不一定提出疯狂、大胆、创新、跳出框框的想法。他们倾向于提出那些在“好球区”内的、董事会都会支持的。所以我们在 NSF 将要测试的一件事叫做“金票”的概念，每个评审员将获得一两张或三张金票。这最初实际上在丹麦和其他一些地方测试过。理论是，评审员可以单方面、无需委员会其他成员同意，选择某个特定的资助。这样你就激励人们提出更有趣的资助。我认为这个概念还有一点很酷的是，你实际上在激励更优秀的人参与评审委员会，因为他们现在有金票，更有可能愿意参与。所以我们想进行这个实验，看看什么样的申请真正获得批准，什么样的科学得以完成。所以它创造了激励，让科学家提出疯狂的想法，因为科学家通常获得研究资助的方式——这是他们必须做的，因为那是他们的生计，字面意义上获得资助，支付你的薪水，支付你实验室人员的薪水——就是你去提交一份资助申请，看起来像是你认为会获得批准的那种。

Well, I think you start by figuring out what experiments you want to run. So I think, take for example in the National Science Foundation, almost all the grants are done in a very standard typical format. There's a set of peer reviewers that do this merit-based review. It's maybe three or four people from a particular field. They take all the applications, they review them, and they select the ones as a group they believe are most meritorious. You know, one could argue that it is merit-based, of course, but it also in many times incentivizes scientists to not necessarily propose crazy, bold, innovative, out-of-the-box ideas. They tend to want to propose ones that are in the strike zone that the board, for example, will all support. So one thing that we're going to be testing at National Science Foundation is a concept called golden tickets where each of the evaluators are going to be given one or two or three golden tickets. And this was initially actually tested in Denmark and some other places. And the theory is that the reviewer will then be able to unilaterally, without the rest of the committee agreeing, make a selection of a particular grant. So you incentivize folks to have more interesting grants. What I think is also kind of cool about this concept is that you're actually incentivizing better people to participate in the boards because they have a golden ticket now and they're more likely to want to participate. So we want to run that experiment and see what kind of applications actually get approved and what kind of science gets done. So it creates an incentive for scientists to propose wild and crazy ideas because the way scientists typically get a research grant — which is what they need to do because that's their living, literally get a grant, pay for your salary, pay for the salary of the people in your lab — is you go and submit an application for a grant that looks like the kind of thing that you think will get approved.

通常这是低风险的，因为如果某件事很可能发生，评审委员会会说：“好的，太好了。我们批准这笔资助，因为我们确信钱花得值。”但现实是，在风险投资中，你我都清楚，十件事里只有一件能成功。这是幂律分布。那件事价值 100 倍。而你想要的是十件事里有九件失败，因为那意味着你在承担大量风险。这才是真正推动边界、发现新事物、取得重大突破的方式——你必须承担风险，而风险意味着失败。

And typically that's low risk because if something is likely to happen, the review board would say, "Okay, great. We're giving that grant because we feel confident that money is well spent." But the reality is in venture capital, which you and I know well, you're going to have one out of 10 things work. It's a power law. That thing's worth 100x. And you want to have nine out of 10 failures because that means you're taking a lot of risk. That's really how you push the envelope and discover new things and make big breakthroughs is you got to take risk, which means failure.

是的。正是如此。完全正确。

Yeah. Exactly that. That's exactly right.

我认为另一个例子是，大多数 NSF 资助大约为 18 个月，这已经成为 NSF 基于学术日历而形成的自然平衡。但你知道，并非所有研究想法都需要 18 个月。有些需要 3 个月或 6 个月。有些需要 5 年。我认为我们在《新黄金时代》中提出并将要测试的另一个想法是不同期限的资助，允许人们尝试快速通道资助——如果他们有一个可以在六个月内完成的想法，如果成功了，他们可以申请更长期的资助；或者你可能有一些更长期的想法，需要三、四甚至五年来研究，我们会进行评估。所以从根本上说，几乎在每一个环节，《黄金时代》试图做的就是根据科学家的实际情况来满足他们。有些想法需要 18 个月。有些需要 6 个月，我们希望确保他们至少有机会提出自己的想法以供评估。

And I think another example of this is most NSF grants are roughly 18 months and that's just become a natural equilibrium that NSF has come to just given where the academic calendars are. But you know all research ideas don't require 18 months. Some of them require 3 months or 6 months. Some of them require 5 years. And I think another thing we're going to be testing and we proposed in New Golden Age was this idea of different durations of grants and allowing there to be opportunities for people to try fast-track grants where they have an idea that can be done in six months and if it works then they can apply for a longer grant or you may have longer-dated ideas that you would need three, four, even five years to work on that we would be evaluating. So at its core, at almost every turn, what Golden Age tries to do is meet scientists where they are. There's some ideas that require 18 months. There are other ones that require 6 months and we want to make sure that there opportunities for them to at least propose their ideas for evaluation.

嗯，除了资助想法，另一种模式是资助个人。

Well, besides funding ideas, an alternative model is to fund individuals.

正如你我所知，这在风险投资界一直被强烈提倡：你找到伟大的企业家，他们可能有一个糟糕的想法，但因为他们是谁，他们最终会做出惊人的成就。我刚又读到关于斯图尔特·巴特菲尔德的故事，他创办了 Slack，当时他在做一个完全不同的业务。他剩下三百万。他告诉投资者：“我该把钱还回去吗？但顺便说一句，我们做了一个内部工程团队使用的沟通工具。”他们说：“不，继续，转型。把它做成业务。”然后它变成了 Slack，他们以 300 亿美元卖掉了它。所以科学界的想法可能也一样：你找到伟大的人。是的。你给他们大量资金。你让他们决定如何花钱，而不是有一个监工来审查他们花的每一美元和采取的每一个行动。别挡他们的路，说：“我相信你会有所成就。这里有一大笔钱，比你要求的多得多。这里有大把时间。十年后见。你会想出惊人的东西。”

This has been strongly advocated for as you and I both know like in the venture capital world, you find great entrepreneurs and they may have a crappy idea, but because they are who they are, they eventually make something amazing work. I was just reading again about Stewart Butterfield who started Slack and he was working on a totally different business. He had three million left. He told the investors, "Should I give the money back, but by the way, we built a communication tool that we use in our engineering team." And they're like, "No, go ahead, pivot. Make that the business." And then it turned into Slack and they sold it for $30 billion. And so the idea in science may be the same, which is you find great people. Yes. You give them significant funding. You let them decide how to spend the money rather than have some overlord that scrutinizes every dollar they're spending and every action they're taking. Gets out of their way and says, "I trust that you're going to get somewhere. Here's a whole bunch of money, a lot more than you're asking for. Here's a whole lot of time. See you in 10 years. You'll figure something amazing out."

所以，我认为其中一个体现就是我们如何看待这些早期职业奖学金。GRFP 是国家科学基金会的旗舰奖学金，你知道我们大约给全国最聪明、最优秀的准博士生提供 2600 个名额。那里的想法是，我们会给你这笔钱去攻读博士学位，但它完全可携带，所以你可以带到任何你想去的地方。你可以让大学为你竞争，最终你会去一个你感到舒适、能做最好研究的地方。这再次体现了奖励科学家和个人，给他们追求学业的机会。

So, I think one sort of manifestation of that is the way that we think about some of these early career fellowships. So GRFPs are kind of the flagship fellowship you have at the National Science Foundation which you know we give roughly 2600 of these to the smartest and best sort of aspiring PhDs in the country. And the idea there is you know we will give you this money to go pursue your PhD but it's totally portable so you can take it anywhere you want. You can have universities compete for you and ultimately you'll end up in a place where you're comfortable and you can do your best research. And that's where again like rewarding the scientist and the individual and giving them an opportunity to pursue their studies.

然后另一种选择是追求大项目。人类基因组计划、曼哈顿计划、阿波罗登月任务。中国似乎非常擅长这一点。在中央计划的背景下，他们有想要实现的宏大目标，然后组织资源并分配大量资本来实现那个目标。

And then the alternative is to go after big projects. The Human Genome Project, Manhattan Project, Apollo moon mission. China seems to be exceptionally good at this. In the central planning context, they have these big objectives they want to achieve and then they organize resources and allocate significant capital to achieve that objective.

是的。

Yeah.

那是一种替代资助模式吗？如果是，在一个有小实验室、每个人都在各自为战、人们甚至可能为资助互相竞争、还有私营企业在做自己的事情的世界里，我们如何组织和执行？作为一个国家，我们是否有能力处理那些真正能为人类带来不可思议突破、但需要大量资本、时间和长期承诺的大而重要的项目？

Is that an alternative funding model? And if so, how do we organize and execute in a world where you got small labs, everyone's kind of working on their own, maybe people are even competing with each other for grants, you've got private industry doing their thing. Do we have the capacity as a nation to tackle big meaty projects that can really make incredible breakthroughs for humanity, but require significant capital and time and a long-term commitment?

我认为简短的回答是肯定的。我认为我们在《科学新黄金时代》中倡导和论证的是，我们已经在这方面迷失了方向。回想我之前提到的，我认为大多数美国人对阿波罗任务之类的事情持积极态度。它让国家团结起来。有一个明确的目标，只有联邦政府才能调动资源来实现。我们在《黄金时代》中倡导，我们必须回归这一点。并不是说这是唯一该做的事，但它应该是我刚才提到的所有事情之外，我们该做的事情之一。举几个我们在该领域正在做的例子。首先，我认为第一个是太空。总统在第一届特朗普政府中非常大胆地说我们要重返月球，我们几乎就要做到了。我的意思是，我们将在 28 年让美国人的靴子重新踏上月球。我们说要在 28 年前在太空拥有核反应堆。我们将在 2030 年前建成月球基地的第一批要素。这些都是需要十年才能完成的重大大胆赌注，我们会做到。第二个是量子计算。总统上个月刚签署了一项行政命令，启动新的国家量子计划，我们试图实现的关键目标之一是在 2028 年前创造一台具有科学相关性的量子计算机。这是给能源部的指令，我们将非常努力地确保能赶上这个相当疯狂的时间表。我的意思是，你们阵营，你知道，我们真的想在 2035 年前实现核聚变，我们正在非常努力地在能源部分配资源，并结合所有私营部门投资来实现这一目标。最后一个是整个政府的大旗舰项目，叫做“创世纪任务”。那就是我们想通过将 AI 应用于最困难的科学挑战和事业，将美国的科学产出翻倍。我们从根本上相信，AI 将成为世界历史上科学发现的最大解锁力量。

I think the short answer is yes. And I think what we advocate for and argue in Science New Golden Age is that we have lost our way on doing that. I think back to even what I mentioned earlier, I think most Americans sort of look back favorably on things like the Apollo mission. It kind of brought the country together. There was a discrete goal of something you were trying to accomplish and only the federal government could sort of marshall the resources to do that. And we advocate for in Golden Ages. We have to return to that. Not that's the only thing we should do, but that should be one of the things we do along with everything else I just mentioned. And a couple examples of what we're doing in that domain. Now, I think the first is around space. The president very boldly sort of said in the first Trump administration that we're going to go back to the moon and we're almost there. I mean, we're going to have American boots back on the moon in '28. We said we're going to have a nuclear reactor in space by '28. We're going to have the first elements of a moon base by 2030. These are like big bold bets that take a decade to accomplish and we're going to do it. I think the second is around quantum computing. So, president signed an executive order just last month launching a new national quantum initiative and one of the key goals there that we're trying to do is create a scientifically relevant quantum computer by 2028. This was a directive to the Department of Energy and we're going to be working very hard to make sure we can hit that pretty crazy timeline. I mean, your camp, you know, we really want to get the fusion by 2035 and we're trying very hard to get the resources allocated at DOE and combined with all the private sector investment to get there. And I think the last one which is kind of our big flagship project for the whole administration is called the Genesis mission. And that is where we want to essentially double the scientific output of the United States by applying AI to our hardest scientific challenges and endeavors. We fundamentally believe that AI is going to be the biggest unlock to scientific discovery in the history of the world.

无论你从事材料科学、化学、数学还是物理，将 AI 应用于你的学科将从根本上改变你从事科学的方式，并加速其进程。我们去年年底发起了一项倡议来实现这一目标，现在几乎整个政府都在为此努力。

Whether you're in material science, chemistry, math, or physics, applying AI to your discipline is going to fundamentally change the way you can do your science and accelerate the way it's done. We launched an initiative in late last year to do that, and now pretty much all of government is working towards that effort.

让我分解一下，试着理解这个选择过程，因为有些东西你可以说可以由私营企业资助，而且它们会得到资助，因为有数千亿美元的资金流入 AI。个人使用 AI 有天然的市场激励，因为它能提高生产力。当量子计算、AI 和科学等领域获得数千亿美元的私人资本时，你真的需要政府来资助这些吗？还是应该资助那些私人资本市场不会涉足的领域，比如深空研究、理解宇宙起源、纯物理学，这些更基础的科学突破，大家都挥手不管？但我们总是发现，在对宇宙的这些基本理解中，多年后会出现一些我们甚至没想到的应用。我们如何做出这些选择？

Let me break this down and try to understand the selection process, because some things you could argue can be funded by private industry and they will be, because there's hundreds of billions of dollars of capital flowing into AI. There's a natural market incentive for individuals to use AI because it makes them more productive. Do you really need the government to fund things like quantum computing and AI and science when those things are getting hundreds of billions of dollars of private capital, versus funding things that are not going to be found in the private capital markets, like deep space research, understanding the origins of the universe, pure physics, looking at these more fundamental scientific breakthroughs that everyone waves off? But we always find that in those fundamental understandings of our universe emerge some application years down the road that we weren't even thinking about. And how do we make those selections?

是的，这是一个很好的观点。我们一直积极倡导的是，我们必须将政府资助的研究的主要焦点回归到基础的早期竞争前研发。这种发现科学是私营部门没有动力参与的领域，只有政府才能做。同时，拥有这些只有政府才能做的大胆想法对我们的企业也非常重要。如果你考虑到到 2028 年创建一台科学相关的量子计算机的紧迫性，私营部门在量子领域有很多活动。但对他们来说，这是为了商业应用。我们想要创造一种可用于科学发现的工具，这将在整个生态系统中带来巨大的红利。我认为 AI for science 的细微差别在于，我们不是在花钱在私营部门围绕 AI 所做的科学上。今天投入 AI 的算力和资金比你想象的任何东西都多，政府并不试图在这个领域竞争。它试图做的是说，看，如果你正在对你提到的所有如此重要的事情进行基础研究，你应该考虑 AI 将如何影响或加速你正在做的工作，我们想帮助你踏上这段旅程。

Yeah, no, that's a great point. Something that we've advocated for quite aggressively is we have to return the primary focus of government-funded research on basic early stage pre-competitive R&D. This discovery science is an area where the private sector is not incentivized to participate in and only the government can do that. At the same time, having these big bold ideas only government can do is also very important for our enterprise. If you think about the urgency to create a scientifically relevant quantum computer by 2028, there's lots of activity in quantum going on throughout the private sector. But to them, it's for commercial applications. We want to create an instrument that can be used for scientific discovery that will pay huge dividends across all the ecosystem. And I think the AI for science, I think the nuance there is we're not spending money on the science that the private sector is doing around AI. There is more compute, more money going into AI than anything you could ever imagine today, and the government's not trying to compete in that space. What it's trying to do is say, look, if you are doing basic research on all the things that you mentioned are so important, you should be considering how AI is going to impact or accelerate the work that you're doing, and we want to help you along in that journey.

我一直觉得政府的许多挑战在于复杂性。就像随时间增加的熵。你有所有这些不同的机构，所有这些不同的团体都在争夺预算，一切都在膨胀。但是，是否有理由将我们这么多机构合并为一个单一的科技机构，更好地组织和优先排序，并将资本分配到最重要的事情上？

I always felt like so much of the challenge with government is the complication. It's like entropy over time. You have all these different agencies, all these different groups all competing for budget and everything balloons. But is there a rationale for consolidating so many of our agencies into a single science and technology agency and being better organized and prioritized and allocating capital to the most important things?

这是一个长期的争论，我认为在我多年工作中反思后，我真诚地认为这是一个特点，而不是一个缺陷。我认为极端的替代方案就是中国正在做的事情。在那里，你有一个自上而下的单一机构实体，设定优先事项并试图执行。自 2019 年我们实施出口管制以来，他们一直在试图解决 EUV 光刻技术。没有突破发生。对他们经济来说，没有比解决这个科学问题更重要的事情了，但他们一直未能做到。所以对我来说，我觉得我们系统最特殊的特点之一就是我们确实有竞争。这种自由市场的创新方法是我们生态系统的一个巨大特点，我认为这是我们拥有所有这些突破的重要原因。

It's a perennial debate and I think as I reflected on it for many years working on it, I honestly think it's a feature and not a bug. And I think the alternative to an extreme is kind of what the PRC or what China is doing. And there you have a top-down directed single agency entity that sets priorities and tries to execute. They have been trying to essentially figure out how to do EUV lithography since we put the export controls in 2019. No breakthrough has happened. There's nothing more important to their economy than solving that scientific problem and they haven't been able to do that. So to me, I feel like one of the most special features about our system is we do have people competing. This free market approach to innovation is a huge feature of our ecosystem and one that I think is an important reason why we have all these breakthroughs.

所以这对我们的成功从根本上至关重要？

So that's critical for our success fundamentally?

我认为是的。你知道，DARPA 的人和从事国家安全相关研发的人坐在国防部而不是某个科学机构，我认为这使他们的工作更好，更符合他们的使命。

I think so. I think you know the fact that the DARPA people and the people working on national security related R&D are sitting at DOD and not sitting at some science agency I think makes their work much better and more relevant to their mission.

所以在我们谈到中国并讨论正在各个领域展开的伟大竞赛之前，我没有和任何行业、政府或其他地方的人交谈过，他们目前没有敏锐地感受到与中国的这种竞争力。但我只想谈谈我们如何分配资本，因为 NIH、NSF，这么多资金流向政府机构或大学。在我看来，可能有四个渠道，你可能有自己的标准，但政府机构可以拿钱去做研究。大学可以拿钱，实验室在大学，大学管理实验室，一切都在大学校园里完成。我们可以谈谈其中的挑战，我认为这非常重要。然后是有经济激励的行业公司，它们可以做研究并取得突破，并从政府获得资金来帮助它们。然后还有像霍华德·休斯医学研究所、梅奥诊所这样的独立组织。在欧洲有马克斯·普朗克。我的意思是，有这些既不是政府也不是私营企业的机构。它们可以说是非营利组织。那么我们如何考虑在这四个渠道之间分配资本？为什么它们好，为什么它们不好，以及随着时间的推移，平衡需要如何转变，以便我们的科学资金获得更好的投资回报率。

So before we get to China and talk about the great race that's underway across every domain, I don't talk to anyone in industry, government, or elsewhere that isn't acutely experiencing this kind of competitiveness with China at the moment. But I just want to talk about how we allocate capital because NIH, NSF, so much of the money flows either to a government agency or to a university. And it seems to me that there are probably four channels and you might have your own kind of rubric for this, but a government agency can take the money and go do research. A university can take the money and the lab is at the university and the university administers the lab and it's all done on campus at a university. And we can talk about the challenges with that which I think is really important to highlight. And then there's industry companies that have an economic incentive that can do research and have breakthroughs and get money from the government to help them. And then there's these kind of like independent organizations like Howard Hughes Medical Institute, Mayo Clinic. In Europe there's like Max Planck. I mean there's these sorts of institutes that are not a government, not private industry. They're sort of like a nonprofit if you will. So how do we think about allocating capital amongst those four channels? Why they're good, why they're not good, and how the balance needs to shift over time for us to get better ROI on our science dollars.

是的。所以，你在这里提出的问题正是我们撰写黄金时代报告的主要原因之一。所以，如果你把历史倒回到 1945 年，第二次世界大战即将结束。

Yeah. So, what you're bringing up here is kind of one of the big reasons why we even wrote the golden age report. So, if you kind of rewind history back in 1945, World War II was ending.

万尼瓦尔·布什，他算是科学顾问——曾担任我如今为罗斯福总统担任的这个角色——收到了一封总统来信，问他：二战后我们该如何对待科学事业？布什写下的回信后来成为《科学：无尽的前沿》，这可以说是美国政府在如何与科学界互动方面的奠基性著作，在过去 70 年里一直是我们思考科学资助的北极星。布什提出的本质上就是我们今天所拥有的体系：政府资助基础研究，主要是在大学里进行。它建立了这样一个事业，让所有这些研究人员涌现出来，所有这项研究涌现出来，战后时代得以开展这些伟大的基础研究。与此同时，所有那些曾帮助制造二战核武器等的国家实验室也纷纷涌现，从事你刚才提到的内部研究工作。所以当时你有两块：政府和学术界。为什么这在那个时代如此重要？因为当时绝大多数科学资助来自联邦政府。大约 70% 的研发由美国政府支付，约 30% 在私营部门。过去 70 年发生的是巨大的转变。现在大约 70% 的研发由私营部门完成，30% 由联邦政府资助。正如你正确提到的，新机构涌现出来——比如资助聚焦研究组织的慈善机构，像霍华德·休斯、马克斯·普朗克研究所等等。现在的问题是：布什推动、颁布并实际带来了过去 50 年伟大发现的模式，在今天是否还像当时那样适用？我们的答案是：不再适用，我们需要更新。这就是我们写《新黄金时代》的原因。对我们来说，我们总是问自己的第一个基本问题是：政府是否在资助私营部门或慈善机构等社区其他方没有动力去做的事情？这应该是你在所有时候的第一道筛选。然后你应该问自己，对美国来说最重要的优先事项是什么。我认为这有时几乎与科学界存在张力。许多人相信，所有探索性科学都是好的，你不应该对什么重要有意见。而我认为我们会说：不，我们不同意。政府是一群民选个体——国会对我们应该在哪里花钱有非常强烈的意见，他们一直通过拨款来指导科学资助——行政部门应该对什么对国家重要有一套论点。我知道我们稍后会谈到中国，但我们必须在 AI、量子、核能、生物等领域取胜。我认为在那里，我们可以有一个叠加层，即美国政府最大的优先事项是什么，并确保在私营部门和慈善机构等无法填补需求的缺口处，政府能够介入。

Vannevar Bush, who was sort of the science adviser—had my role for FDR—received a letter from the president that asked him, you know, what do we do with the science enterprise post World War II? And Vannevar Bush wrote his response that became Science, the Endless Frontier, which is kind of the seminal work in the way that the US government should interface with the science community, and has sort of served as the north star for how we think about science funding for the last, you know, 70 years. And what Bush proposed was essentially the system that we have today, where the government funds basic research primarily at universities, and it set up this enterprise where all these researchers sprung up, all this research kind of sprung up, and kind of the post-war era was able to do this great basic research. And in parallel to that, all the national labs that had helped sort of build the nuclear weapons of World War II and so on sort of sprung up to do the intramural work that you were talking about. So there you had sort of two pieces. You had government and you had academia. And why that was so important in that era was at that time the vast majority of science funding was done by the federal government. Roughly 70% of R&D was paid for by the US government. About 30 was in the private sector. What has happened over the last 70 years was there's been this dramatic shift. Now roughly 70% of R&D is done by the private sector and 30 is funded by the federal government. And as you mentioned correctly, new institutions have sprung up—things like philanthropies that fund focused research organizations, things like Howard Hughes, Max Planck Institute and so on. And the question now is: is that model that Bush pushed forward and promulgated and actually led to the great discoveries of the last 50 years—is that still as relevant today as it was then? And our answer is it's not, and we need a refresh. And that is why we wrote New Golden Age. And for us the first basic question we always ask ourselves is: is the government spending on something that the private sector or others in the community like philanthropy are not incentivized to do? And that should be your first cut at all points. And then you should ask yourself kind of what are the most important priorities for the United States. And I think that is something that sometimes it almost is like a tension with the science community. Many sort of people believe that, you know, all discovery science is good and you should have no opinion about what's important. And I think we would say like, no, we disagree. Like the government is a set of elected individuals—Congress has a very strong opinion about where we should spend money and they direct science funding all the time through their appropriations—and the executive branch should have some sort of thesis about what's important for the country. I know we'll talk about China in a second, but we have to win on things like on AI, on quantum, on nuclear, on bio. And I think there we can—there can be an overlay of kind of what are the biggest priorities for the US government and make sure that the gaps of places where you know the private sector and where philanthropy and others aren't able to fill the need, the government can step in.

好。那么大学资助方面发生了什么？大学有一项行政收费。你们改变了这一点。也许你可以给我们讲讲。这届政府对大学从拨给科学研究的资金中抽取行政费用持什么看法？这些钱被用在了哪些可能违背、或这届政府认为违背其目标的地方？因为有些人提出，这届政府在做出改变和分配资金时带有政治动机，因为他们不喜欢大学管理者的政治立场或社会观点。

Yeah. So what is going on with university funding? There's this administrative charge that universities have. You changed that. Maybe you can tell us a little bit about that. And what is this administration's view on universities taking capital that's been allocated for scientific research, getting an administrative fee, and where does that money get used in ways that maybe counter or that this administration views being counter? Because some people have made the case that this administration is being political with the changes that they're making and how they're allocating capital because they don't like the politics or the social views of university administrators.

作为科学顾问，我的观点是：我们应该去最优秀的科学家所在的地方支持他们。如果他们在大学，我们就资助他们。如果他们在聚焦研究组织，我们就资助他们。如果他们独自在车库里做着了不起的工作，并且能通过基于绩效的评审小组，我们就资助他们在车库里做。对我来说，我认为我们愿意资助大学以外的科学家这一想法，被学术界扭曲成了我们 somehow 反学术科学家。我们是支持科学家的，不在乎他们在哪里。我认为这是我们未来几年要推动的《黄金时代》的核心原则。

My view as the science adviser is that we should meet the best scientists wherever they are. If they're at a university, we should fund them. If they're at a focused research organization, we should fund them. If they're on their own in their garage doing incredible work and can pass a merit-based review panel, we should fund them in their garage. And to me, I think the idea that we are open to funding scientists outside of universities, I think has been sort of twisted by the academic community to believe that we're somehow anti-academic scientists. We are pro-scientists and we don't care where they are. And I think that's a core tenet of Golden Age that we're going to be pushing for the next few years.

好。那么我们来谈谈与中国的伟大竞赛。2000 年，中国每年支出 330 亿美元。2021 年，6700 亿美元。所以中国增加了 19 倍。同一时期，美国增加了大约 3 倍。有一个统计数据我要引用，但很难核实，我估计大约十年前，美国在科学期刊上发表的论文数量大约是中国实验室、学者和科学家的两倍。而今天，中国在几乎所有领域发表的论文数量都多出约 50%，除了某些生命科学领域。

Okay. So, let's talk about the great race with China. In the year 2000, China was spending $33 billion a year. 2021, 670 billion. So, China increased spending by 19x. Over the same time period, the US increased spending by roughly 3x. There's a statistic I'll quote, but it's going to be hard to verify, but I've estimated it that about a decade ago, US published roughly twice as many papers in scientific journals as Chinese labs and academics and scientists did. And today, China's publishing roughly 50% more in nearly every domain with the exception of some life sciences.

中国算是跑到了前面。请为我们框定一下与中国科学竞赛的重要性。为什么这很重要？为什么人们应该关心？科学难道不是为了人类的福祉吗？当突破出现、发现诞生时，难道不是每个人都受益吗？为什么美国人应该关心？为什么世界应该关心我们与中国在这种竞争和发现方面的相对位置？

China's kind of raced ahead. Frame for us the importance of the scientific race with China. Why does it matter? Why should people care? Isn't science for the benefit of humanity? Doesn't everyone benefit when breakthroughs are made, when discoveries are made? Why should Americans care? And why should the world care about where we are with respect to this kind of competitiveness and discovery with China?

我认为中国人在几年前就意识到，技术和科学领导力是经济和国家安全的最终基础。作为一个国家，我们所做的一切，在我看来，在某种程度上都根植于科学和技术发现。我们从今天半导体的状况中看到了这一点。我们在 Transformer 和其他技术上的突破带来了今天的大语言模型。实际上，支撑我们经济的一切，其核心都是某种科学发现。对我来说——稍微谈谈之前提到的——我一直试图推动的是这样一个想法：试图集中化科学，历史上并没有带来你可能想要的那种突破。而对我来说，自由市场的方式是：我们拥有的这个极其活跃的风险投资生态系统，加上政府所做的科学资助，加上产业界有动力去做的事情，最终会带来这些伟大的发现。

I think the Chinese realized a few years ago that technological and scientific leadership is the most important foundational block to economic and national security. Everything that we do as a country is sort of at some—in some way, in my opinion, rooted in scientific and technological discovery. We see it with what's going on in semiconductors today. The breakthroughs that we had in transformers and other technology led to the large language models of today. Literally everything that's sort of powering our economy at its core was some sort of scientific discovery. I think to me—to talk a little about kind of mentioned earlier—I think what I keep trying to push is this idea that trying to centralize science has historically not led to the type of breakthroughs that you may want. And I think to me the free market approach is that this extraordinarily vibrant venture ecosystem that we have paired with the science funding that the government does, paired with what industry is incentivized to do, ultimately leads to these great discoveries.

我也非常确信，因为我们仍然是所有人都想来工作、生活和学习的地方。每个人都想在这里创业。每个人都想在我们的大学里学习。这正是让我们的生态系统如此特别、如此独特的原因，所以我们必须培育它，确保继续成功。

I'm also very assured because we continue to be the place where everyone wants to come work, live, and study. Everyone wants to build a business here. Everyone wants to learn at our universities. That is something that makes our ecosystem so special and so unique, and that's why we have to nurture it and make sure to keep succeeding.

你可以说，我们一些最大的突破是集中规划、管理和资助的——人类基因组计划、曼哈顿计划、阿波罗计划等等。但总的来说，市场中的竞争力、基于市场的体系会带来更大的风险承担、更大的突破边界，并最终带来更大的成果。这就是为什么我认为我们谈到的组合方法如此重要。这就是为什么我们在量子、太空和核聚变领域下了这些大胆的赌注。但与此同时，我们也为这种发现科学和自由市场商业化方法打开了大门。

You could argue that some of our biggest breakthroughs were centrally planned, managed, and funded — the Human Genome Project, the Manhattan Project, Apollo, and so on. But generally, the competitiveness in the market, the market-based system yields greater risk-taking, greater pushing of the envelope, and ultimately greater outcomes. That's why I think the portfolio approach we talked about is so important. That's why we set these bold bets in quantum, space, and fusion. But at the same time, we've opened the aperture for this sort of discovery science and free market approach to commercialization.

那么，你认为中国在哪些方面做得非常正确？你知道，当你为白宫、总统提供建议，谈论政策时——当我们看中国时，我们认为他们在政策方面做得非常出色的是什么？

So where do you think China's getting things really right? You know, when you advise the White House, the president, and you're talking about policy — when we look at China, what do we see as being incredibly well done with respect to their policy?

他们长期以来使用的策略基本上是复制我们的知识产权，创造该特定技术的更便宜替代品，将其倾销到美国，让我们的企业倒闭，然后挤压我们。我认为多年来你在各种技术中都看到了这一点。我认为这是我们需要非常非常警惕的事情。我认为他们采取行动或威胁采取行动的第二个领域是围绕我们的一些关键矿产，我们意识到这些矿产是我们更大的科技和科学生态系统（如果你愿意的话，供应链）中非常重要的一部分。所以这些是我们必须不断思考并准备自己能够独立的事情。

The playbook that they have used for a long time is essentially copying our IP, creating cheaper alternatives of that particular technology, dumping them in the United States, getting our businesses to go out of business, and then squeezing us. I think you've seen that with a wide variety of technologies over the years. And I think it's something that we need to be very, very cognizant of. I think the second area which they've taken action on, or threatened action on, is around some of our critical minerals, which we realize are a very important piece of our larger tech and science ecosystem, if you will, supply chain. So those are things that we have to constantly be thinking about and preparing ourselves to be able to be independent.

但考虑到他们发表的论文数量，可以说它们是可信的，是经过同行评审的。我们就说他们正在取得突破，并且在许多情况下正在领先于我们。是什么帮助了他们？所以知识产权盗窃、市场倾销，那是产业贸易政策之类的东西。但在发现这个核心基础上，他们是不是正在领先，他们在做什么？嗯，他们只是资助更多吗？因为我会说，根据一些估计，再次强调，他们的支出大致与我们相当。

But given the number of papers they're publishing, arguably they're credible, they're peer-reviewed. Let's just say they are making breakthroughs and they are getting ahead of us in many cases. What's helping them there? So the IP theft, dumping on the market, that's industrial trade policy type stuff. But on this core basis of like discovery, are they not getting ahead and what are they doing? Well, are they just funding more? Because I would argue by some estimates, so again, they're spending roughly on par with us.

嗯。

Mhm.

但根据一些估计，他们每投入一美元能获得两倍的回报。根据一些估计，四倍。根据一些估计，十倍，因为他们的劳动力成本更低。他们有更多的自动化。他们的供应链成本更低。显然，那里的标准不同。是的。在运作方式上。所以按美元对美元计算，在产生输出方面，他们相对于我们来说花费得远远更多，这体现在他们发表的论文上。这仅仅是花费更多的结果，还是我们可以做其他不同的事情？

But by some estimates, they get 2x for every dollar they put in. By some estimates, 4x. By some estimates, 10x because their labor costs are lower. They have much more automation. Their supply chain costs are lower. Obviously, the standards are different there. Yeah. In how things operate. So on a dollar-for-dollar basis, they're way overspending relative to us in terms of generating output, and it's showing up in the papers that are publishing. Is it just a function of spending more or are there other things that we could be doing differently?

看，我认为我们可以做更多的事情是鼓励更多美国人进入 STEM 领域。这是我多年来一直在思考的事情，我长期追踪的一个统计数据是，例如，美国出生的计算机科学博士获得者的百分比。如果你把时间倒回 30 年，我认为 70% 是美国人，30% 是外国人。现在情况反过来了。我认为对我们这个国家来说，我相信拥有一支具备 STEM 素养的劳动力是我们作为一个国家可以拥有的最重要的超级能力之一。我们正在尽一切努力寻找方法鼓励我们的年轻学生继续攻读这些学位。对我来说，回到这个问题上，我认为我们必须更加认真对待的另一件事是，我在我们的科学生态系统中观察到的是，我们的年轻科学家，那些刚刚完成博士学位并开始学术生涯的人，这是你能想象到的最艰难的工作之一。你几乎拿不到钱。你在大学里，辛勤工作试图做研究。对于他们为我们国家所做的事情来说，这是你能想象到的最被低估薪酬的人。对我们来说，我认为我们必须让我们的科学事业回报他们，给他们机会去研究他们最好的想法，并让他们能够脱颖而出。我认为这就是我们关注的。

Look, I think to me what we could be doing a lot more of is encouraging more Americans to enter the STEM fields. This is something that has been on my mind for many, many years, and a statistic that I've tracked for a long time is the percentage of US-born PhD recipients in computer science, for example. If you rewind the clock 30 years, I think it was 70% were American and 30% were foreign. And now it's inverted. And I think to us as a country, I believe that having a STEM-literate workforce is one of the most important superpowers we could have as a country. And we're doing everything we can to find ways to encourage our younger students to continue to pursue these degrees. And to me, back to this thing, I think another thing that we have to take a lot more seriously is, and what I've observed in our science ecosystem is, our young scientists, the ones that have just finished up their PhD and are starting their academic careers, these are one of the toughest jobs you can imagine. You're paid almost nothing. You're in a university, you're toiling away trying to do research. Here's the most underpaid people you could imagine for what they're doing for our country. And to us, I think we have to return our scientific enterprise to reward them, to give them opportunities to work on their best ideas and to allow them to excel. And I think that's what we're focused on.

所以，我们培养了很多外国学生，把他们带进来，他们在这里获得博士学位。为什么我们不多让他们留下来？那么，什么样的移民政策也能支持你之前提出的观点，即让合适的人进入该领域，让合适的人进入科学研究？我们有很多中国学生来这里获得学位、获得博士学位，然后我们没有积极留住这些人才的计划。他们回去，在中国的实验室或中国工业界工作，或者你知道，在其他国家工作。中国现在开始吸引来自印度、欧洲的科学家。为什么我们不这样做？因为我们在科学领域没有本土人才库。我们难道不应该更积极地招募人才吗？

So, we train a lot of foreign students, we bring them in, they get PhDs here. Why don't we let them stay more? And so what is the immigration policy that also bolsters the points you made earlier about getting the right people in the field, getting the right people into scientific research? We've got a lot of Chinese students that come here, get a degree, get a PhD, and then we don't have a program for actively retaining that talent. They go back and they work in the Chinese labs or Chinese industry or, you know, in other countries. And China is now starting to attract scientists from India, from Europe. Why aren't we doing that? Because we don't have the homegrown talent pool in science. Shouldn't we be more active in recruiting entertainment?

我必须——我认为对我们来说，我认为你必须做两件事。我认为第一，你必须确保我们鼓励年轻美国人进入这些 STEM 领域，对于那些确实想留下来的人，允许他们通过合法途径留在这里。

I have to — I think for us, I think you got to do two things. I think one, you got to make sure that we're encouraging young Americans to go into these STEM fields and for those who do want to stay, allow them to pursue legal pathways to stay here.

那么，这项政策被政府听到了吗？是被接受了，还是与更美国优先的政策相冲突，即首先照顾美国人，确保工作首先给美国人？

So, is that policy being heard by the administration? Is it accepted or is it in conflict with a more America First policy which is looking out for Americans first, making sure jobs are for Americans before?

嗯，我不认为这与政策冲突。我的意思是，我认为我们基本上，在开始考虑其他任何人之前，我们必须先把自己的事情处理好，关于如何让更多美国人追求这些东西。再次，这些关于计算机科学的数字应该让人们非常警觉。美国十分之七的 STEM 相关博士候选人不是美国人，这个想法，任何人都可以看到并说，鉴于我们几十年来教育美国人的方式，这看起来就是不对。我认为我们通过许多这些科学项目有一个巨大的机会，把人们带回来。

Well, I don't think any says in conflict with the policy. I mean, I think we as basics like before we even start thinking about anyone else, like we have to get our house in order about how we can get more Americans to pursue this stuff. Again, these numbers around computer science should be very alarming for people. The idea that seven out of 10 STEM-related PhD candidates in the United States are not American, like anyone can look at that and say like that just doesn't look right given the way that we've been educating Americans for so many decades. And I think we have a huge opportunity through a lot of these science programs to bring folks back in.

在写这本书和这份报告的过程中，我发现了一件事：我们曾经在国家科学基金会（National Science Foundation）设有项目，支持和鼓励美国高中和初中的天才学生。这些项目因为某些原因被停止了。鼓励成绩优异的年轻学生在美国追求 STEM，曾是政府实际决定不再资助的事情。我认为这些是令人沮丧的做法，我们想要扭转它们。

One thing I discovered while writing this book and this report was that we used to have programs at the National Science Foundation that would support and encourage gifted and talented students in American high schools and middle schools. Those were stopped for some reason. Encouraging higher-performing young students to pursue STEM in America was something the government made an actual decision to no longer fund. I think those are discouraging actions that we want to turn around.

为什么会这样？看起来挺愚蠢的。

Why is that? Seems silly.

感觉这是更大范围的 DEI 努力的一部分。你可以想象，而且你在加州应该很清楚，旧金山有所有这些举措，他们停止在高中教授高等代数。

It feels like it's part of this larger DEI effort. You can imagine, and you probably know well being in California, there were all these initiatives out in San Francisco where they stopped teaching advanced algebra to students in high school.

现在加州大学正在就 SAT 分数展开争论。教授们都说，进来的孩子不会——我们得在 UC 伯克利（我就是那里毕业的）做补救数学，教他们怎么做数学。以前你得 SAT 考到 1500 分才能进那里——那时候满分是 1600，我不知道现在还是不是——但他们停止要求 SAT 了，现在孩子来了之后表现就体现出来了。最初不想取消 SAT 的教授们现在都说，不不不，我们需要它回来，我们需要它回来。

And there's this battle right now at the University of California on SAT scores. The professors are all saying we got kids coming in and they can't—we have to do remedial math to teach them how to do math at UC Berkeley, which is where I went. And it was like you had to get like a 1500 on your SATs just to get in there back in the—this was when it was on 1600, I don't know if it still is—but they stopped taking SATs and now you're seeing it in the performance when the kids show up. And the professors who initially didn't want to remove SAT are now saying no no no we need it back we need it back.

这些政策从根本上损害了美国有才华的 STEM 孩子的进步，无法为美国下一代科学家建立人才管道。

These policies are fundamentally harming the progression of talented STEM kids in America to create that pipeline for the next scientists in America.

是的，我们应该奖励最伟大、最有才华的美国人，给他们机会去追求他们所有伟大的科学和技术梦想与事业。对我来说，最悲剧的是——有些孩子有潜力去追求这些，但我们却主动运行项目来阻止他们这样做，这必须停止。世界其他地方都在做，然后他们得到高薪、好房子，现在搬到中国去了。

Yes, we should be rewarding the greatest and most talented Americans and giving them opportunities to pursue all their great science and tech dreams and endeavors. And to me, that's what's most tragic—where you have kids that have potential to pursue this, yet we actively run programs which discourage them from doing that, and that has to stop. The rest of the world's doing it, and then they're getting paid a lot and giving nice homes and moving to China now.

是的。是的。

Yeah. Yeah.

这真是个疯狂的事实。

That is a crazy crazy fact.

我也认为，再次强调，老实说，《新黄金时代》的核心宗旨是关于思考我们如何再次提升科学家的地位——我们资助项目的方式、我们资助的项目类型、我们构建拨款和奖学金的方式，都围绕着科学家本人。不是关于你在哪个机构工作，或者你来自哪里，或者你在哪里长大。而是关于你自己。你能追求黄金标准的科学工作，我们就会支持。

And I think too, and again to keep harping on it, honestly the core tenant of New Golden Age is about thinking about how we can elevate the scientist again—how the way that we fund our programs, the types of programs we do fund, the way that we structure our grants and fellowships are all centered around the scientist himself. It's not about what institution you work at or where you came from or where you grew up. It's about you yourself. Can you pursue gold standard scientific work and we'll support it.

我的意思是，在 20 世纪，尤其是二战后，科学家是名人，是摇滚明星。他们被杂志、报纸和电视节目报道，你知道，他们因名声和知名度而获得经济回报。我们失去了这一点，还是导致了像福奇这样的时刻？

I mean in the 20th century scientists in the post World War II particularly were celebrities, were rock stars. They were kind of featured in magazines and newspapers and television shows and you know they were rewarded economically with fame and notoriety. Did we lose it or did it lead to moments where you have like Fauci?

这是个好——这是个很好的问题。我确实觉得当今时代有几个名字符合那个时刻。如果你想想像 Demis 这样的人，比如在谷歌，他获得了诺贝尔奖，那有点——

That's a good—that's a great question. I do feel like there are a few names in today's time that kind of meet that moment. If you think of someone like Demis, for example, at Google, that has won a Nobel Prize, that is sort of—

90% 的人讨厌 AI。

90% of people hate AI.

那是真的。那是真的。也许他能扭转局面。我不确定。

That is true. That is true. Maybe he can turn the tide on that one. I'm not sure.

他可能是最有资格的，但我认为在这一点上这是一场艰苦的战斗。

He's probably the best qualified but I think it's an uphill battle at this point.

是真的。我的意思是，存在这种深刻的反科学、反技术情绪，不仅在美国，在西方也是如此。你认为这是本地滋生的，因为人们感到被落下？科学家和技术专家，如果你从历史的大周期来看，他们常常是替罪羊。他们常被视为精英主义者，因为他们懂东西。他们拥有别人没有的东西。有知识，有渠道，有控制，有权力。因为当你拥有新技术时，你就拥有别人没有的权力。当你有理解时，你就拥有别人没有的东西。我们是否正处于这个时刻，这个西方民粹主义时刻，科学和技术被视为精英的工具，因此必须被打破和摧毁？

Is true. I mean, there's this deep anti-science, anti-technology sentiment, not just in the US, but in the West. Do you think it's bred locally because people feel left behind? Scientists and technologists, if you look historically through great cycles, they're often scapegoats. They're often viewed as the elitist because they know stuff. They have stuff that others don't. There's knowledge, there's access, there's control, there's power. Because when you have a new technology, you have power that others don't have. When you have understanding, you have something that others don't have. Are we in this moment, this populist moment right now in the west where science and technology is viewed as a tool of the elite and therefore it must be broken and destroyed?

我不确定，但我经常想到的是 COVID 期间发生的事情以及福奇所代表的东西。我认为他对科学的伤害比现代历史上任何人都大。当他倡导诸如学生在学校需要戴口罩的立场时，当社会、儿科协会发出信件说人们可以出去集体抗议，但不允许去医院看望垂死的祖母。任何普通的美国中产阶级听到这些后都无法再认真对待科学。所以，我认为需要做很多修复工作。这就是为什么我认为我们回归黄金标准科学根源的方法如此重要。我们必须让人们理解和信任科学是什么，看到它是一件鼓舞人心和美好的事情，可以改变我们的生活方式，而不是某种教条或规则或来自高层的法令，而是一个我们所有人都参与的过程，我们都在实验和学习我们生活的世界和宇宙。我试图更乐观，但我认为我们在 COVID 期间真的真的达到了低点，我认为我们需要——需要相当长的时间才能挖出来。

I don't know about that, but what I think about is I really do often times think about kind of what happened during COVID and what Fauci represented. And I think he did more disservice to science than anyone in modern history. When he is advocating for positions like students need to be masked in schools, when societies, the pediatric societies are putting out letters saying it's okay for people to go out and collectively protest, but they're not allowed to go see their dying grandmother in a hospital. No regular median American can listen to that and then take science seriously. So, I think there's a lot of healing that needs to be done. And that's why I think our approach to going back to the roots of gold standard science is so important. We have to allow people to understand and trust what science is about and see that it's an inspiring and a good thing and can change our way of life and it's not some sort of dogma or rule or some edict that comes from on high but it's a process that all of us are part of that we're all experimenting and learning about the world and the universe that we live in. And I try to be more optimistic but I think we really really hit a low point during COVID and I think we're going to have to take—it's going to take quite a while to dig ourselves out.

是的。我在那个时代的观察是，我总是假设如果每个人都认为某件事，那它可能是错的。

Yeah. My observation during that era is like I always assume that if everyone thinks something, it's probably wrong.

是的。

Yes.

就像——

Like—

是的。

Yes.

但如果有一部分人激烈反对，而有些人支持某事，那么其中可以找到一些客观真理。但如果每个人都以非常统一的方式支持某事，那就有些不对劲。但让我害怕的是，这么多人没有经验主义——科学的整个基础就是收集经验数据。你提出问题，你探究，然后你去收集数据，你用数据来指导你的结论。但并没有很多经验数据被用来得出结论。每个人都排队支持这些结论和假设，并且被告知要相信科学。结果，不仅破坏了人们对科学的信任，我认为它还引发了一些问题。

But if some percent of people argue viciously against it and some people argue for something, there's some objective truth to be found in that. But if everyone aligns behind something in a very kind of uniform way, there's something really off about that. But what was scary to me was how so many people without empiricism—the whole fundamental basis of science is you gather empirical data. You ask questions, you inquire, and then you go gather data and you use that data to inform your conclusion. And there wasn't a lot of empirical data that was being used to make conclusions. And everyone lined up behind these conclusions and these assumptions and it was told trust the science. And as a result, not only did it kind of destroy trust in science, but I think it brings to light questions.

科学家们怎么了？为什么他们全都这样站队？为什么大家都觉得可以贬低提出问题的人，而科学的基础本就是提问？就算有人问蠢问题、问错问题，也没关系。但这里出现了一种崩坏：科学家本应能够提出问题而不被排斥，这个科学基础被破坏了。

What happened to the scientists? Why did they all kind of line up like this? And why did everyone feel it was okay to put down people that asked questions when the basis of science is to ask questions? And it's okay if people ask dumb questions, if they ask wrong questions. But there was this breakdown on the scientific basis of scientists being capable of asking questions without being shunned.

我完全同意。任何提出问题的人都会被科学界批评为反科学。

I could not agree more. And anyone who asked questions were criticized by the scientific community as being anti-science.

这太疯狂了。

It's crazy.

反疫苗者、反这个、反那个、反科学。你问一个问题，你就是反科学。如果你质疑 IPCC 气候变化报告中的某些结论，你可以同意一些、不同意另一些，但如果你不全盘同意，你就是反科学。

Antivaxer, anti- this, anti- that, anti-science. You ask one question, you're anti-science. If you question some of the conclusions in the IPCC reports on climate change, you can agree with some things, disagree with other things, but if you don't agree with it all, you're anti-science.

嗯，不，但如果你对 RCP 8.5 提出异议，如果三四年前我公开质疑它，我会被所有人猛烈批评，被说成是反你的特朗普、反科学的 MAGA 分子，

Well, no, but the idea that you would push back on the RCPA 8.5, if I would have pushed back on that publicly three or four years ago, I would have been criticized dramatically by everyone as being anti your Trumper anti-science MAGA guy,

但 IPCC 说我们现在甚至不能再谈论那个了。所以，我认为如果你坚持到底，继续坚持那种黄金标准的科学理想——好奇、提问、遵循科学方法，我认为最终会被证明是对的。

but PCC says we can't even talk about that anymore. So, I think if you stay the course and continue to stick to sort of gold standard science ideals of being inquisitive, asking questions, following the scientific method, I think ultimately be proven right.

我的意思是，我认为你在报告中提到的关于科学家老龄化的一点值得强调。也许你可以稍微谈谈我们现状的重要性，因为今天与我们合作的科学界，以及 STEM 毕业生的流失、人才管道的流失，可能正在损害我们与中国竞争中的进展。

I mean, I think one of your points about the aging of the scientists that you make in the reports worth highlighting. Maybe you could just talk a little bit about the importance of where we are because the scientific community that we're working with today and the loss of STEM graduates, the loss of the pipeline may be hurting us in in our progress with China.

不，我的意思是我们必须继续支持年轻科学家。我认为最让我震惊的一个统计数据是 NIH 院长杰伊·巴拉查里亚与我分享的：NIH 内部研究人员的年龄中位数是 71 岁。

No, I mean we have to continue to back and support young scientists. And I think one of the statistics which was most alarming for me which Jay the Jay Baracharia the director of NIH shared with me was that the median age of an intramural researcher at NIH is 71 years old.

71 岁

71

71 岁。

71.

那是中位数年龄。

That's the median age.

中位数年龄，所以这些是在 NIH 机构工作的研究人员。

The median age of an in so these are these are researchers that work at at an NIH institution.

哇。

Wow.

退休年龄不是……你难道不是在那之前就拿到养老金了吗？你知道，我得再深入研究一下那个统计数据，但我想是的。但我认为有一个巨大的机会让年轻科学家重新回归。所以，我想说请继续关注，因为我认为 NIH 将会有很多有趣的事情发生。

Isn't the retirement age like don't you get a pension before that? you know, I gotta dig in more of that statistic, but I think so. But I think there's this huge opportunity to bring young scientists back into the fold. So, I would say stay tuned there because I think there's a lot of interesting stuff going to happen at NIH.

那么，你如何让科学和纯科学研究——物理学、数学、天文学——获得资金和所需的关注，在这个似乎每个人都如此沉迷于 AI 这个应用技术的时代？

So, how do you get science and pure science research, physics, mathematics, astronomy? How do you get these funded and get the attention that they need in an era where it seems like everyone is so consumed with AI which is an applied technology?

是的。

Yeah.

而且还有重要的工作要做。AI 可以在其他一些事情上被利用，但比如你如何考虑在 AI 上竞争？因为我参加的每次会议，我相信你也是，都是 AI 这个、AI 那个。芯片、与中国的进展、开放模型，这些主导了华盛顿的对话，主导了世界的对话。我觉得我们正在抛弃一些我们在基础研究中需要取得的真正重要的进展。

And there's important work still to do. AI can be leveraged in some of this other stuff but like how do you how do you think about competing on AI? Because every meeting I go into, I'm sure you go into it's AI this, AI that. Chips progress with China open models that's kind of dominating the conversation in DC, dominating the conversation in the world. And I feel like we're leaving behind some of these really important advances that we need to be making in fundamental research.

所以，在《新黄金时代》发布当天，实际上 Russ Vought——他是 OMB 主任、预算主任——和我写了我们的年度研发优先事项备忘录。在那份备忘录中，我们基本上列出了政府的优先事项，以及各个机构应该如何编写预算以对应那些研究优先事项。首先，在第一页，我们谈到了基础研究的重要性，我认为这些就是你提到的事情。我认为那份备忘录在某种程度上充当了美国的政策，说明像 NSF 这样的机构应该如何优先考虑这些事情。所以我很兴奋看到我们朝这个方向前进，并且正如你所说，不断提醒世界，有大量资本投入到研发，实际上是投入到私营部门的 AI。我们应该思考那些只有美国政府才能资助的事情，那就是基础研究。

So after new golden age was released on the same day actually Russ Vought who's the OMB director the budget director and myself we wrote our annual R&D priorities memo and in that memo we essentially list out kind of what are the priorities administration and how individual agencies should write their budgets to map to those research priorities and kind of first and foremost on the very first page we talk about the importance of basic fundamental research and I think those are things that that you mentioned And I think that memo kind of serves as the policy United States on how agencies like NSF should be prioritizing those things. So I'm excited to see us go in that direction and kind of as you say keep reminding the world there is an insane amount of capital going into to R&D really into AI out in the private sector. We should be thinking about the stuff that that only the US government can fund and that is that sort of basic research.

那么，在《新黄金时代》出版后，总统会发布行政命令吗？会有对国会的要求吗？我的意思是，你需要政府和国会采取什么行动来推进你提出的一些理想？

So after the publication a new golden age are there EOS executive orders coming out from the president to follow? Is there going to be asks of Congress? I mean what are the actions that you need in the admin and with Congress to try and carry forward some of the ideals that you lay out?

完全正确。所以第一份实施文件就是这份研发优先事项备忘录。这份备忘录发给白宫，发给各机构，基本上告诉他们这些是你们未来需要实施的预算优先领域和做法。嗯，排名前五的研究机构，那些研发预算超过 30 亿美元的，需要在发布后 90 天内向我们提交一份报告，说明他们将如何实施。所以，你已经开始看到各机构关于如何实施该报告的公告。国家科学基金会发布了一个 XLABS 公告，旨在资助这些聚焦研究组织。NSF 还发布了一个关于与产业合作完成的 4 年博士项目的公告，这样人们可以更快地从博士项目毕业然后进入产业界。嗯，我认为这些是我们将在各机构看到的项目。我认为第二部分将是实际上与国会合作处理拨款，确保它们与《新黄金时代》的方向一致。但我会说请继续关注。我认为我们有很多正在筹备中，我认为白宫说‘你们必须在预算中优先考虑这些事情’是第一个重大步骤。你将在明年开始看到这一点成为现实。

Totally. So the first implementation document is this R&D priorities memo. So this is a memo that goes out to the White House that is goes out to the agencies that essentially tells them these are the budget um priority areas and practices that you need to implement going forward. Um, and the top five research agencies, those with over $3 billion in in R&D, have a report due back to us 90 days after the publication on how they're going to be doing implementation. So, you've already started seeing announcements from the agencies on how they're implementing the report. You had an XLABS announcement coming out of National Science Foundation to sort of fund these focused research organizations. NSF also put out an announcement around 4-year PhDs that that are done in partnership with industry. so people can graduate out of the PhD program and then go into industry um much much more quickly. Um and and I think these are the programs we're gonna be seeing across across our agencies. I think the second piece is going to be actually working with Congress on the appropriations to make sure that sort of they're aligned with the directions of of of new golden age. But I would just stay tuned. I think we have we have a lot down in in the pipe and I think the burst first big step of the White House saying thou shalt in your budgets prioritize these things. You're going to start seeing that manifested over the next year.

有一件事让我来到华盛顿特区就抓狂，幸运的是我不必像你那样经常处理它，那就是你沿着这条路去国会，与众议院和参议院的这些人会面，他们想要的只是为他们的人争取资金。他们希望钱流向他们的选区或他们的州。你如何平衡国会的这种需求与我们刚才谈到的真正重要的事情？这是科学。这是必须完成的方式。这是人才所在。这是机构所在。这不是拿钱然后撒到各州。这是关于实现明确定义的使命。使命才是重要的。不是每个人的抢钱。

The one thing that pull I pull my hair out when I come to Washington DC and fortunately I don't have to deal with it as often as you do is you go to Congress down the road here and you go meet with these guys in the House in the Senate and all they want is funding for their people. They want money to flow to their district or to their state. How do you balance that demand from Congress against what really matters that we just talked about? This is the science. This is how it's got to get done. This is where the people are. This is where the institutions are. And it's not about taking money and just spreading it to states. It's about achieving the mission that is clearly defined. And the mission is what matters. Not about a money grab for everyone.

你知道，我认为有几种方式。

You know, I think there's a couple ways.

我认为我首先非常乐观的一点是，《黄金时代》中的大多数建议都非常非常无党派或两党共识。我认为重新思考我们部署科学资本的方法，尝试资助不同的机构，并提拔个体科学家，这些想法我认为在国会山会被一致接受，或者让人们感到兴奋。

I think the first thing which I'm very optimistic about is most of the recommendations that are in Golden Age are very, very nonpartisan or bipartisan. I think the idea of rethinking about the methods by which we deploy science capital and try to fund different institutions and promote individual scientists are all things that I think will be uniformly accepted or people excited about on the Hill.

我认为另一件可能对我们有利的事情是，这些原则中的许多将触及许多不同的州。比如，如果你出去说，看，你知道在东北部少数精选机构正在做非常出色的工作。话虽如此，全国各地都有大量研究，我们要确保最好的科学家，无论他们在哪里，都能获得资助。我认为这也能获得很多支持。所以，我很乐观，但如你所知，国会山总是艰难跋涉。

I think the other thing that could work in our favor with the Hill is that a lot of these tenets are ones that will touch lots of different states. Like if you go out and say, look, you know there is really great work being done at a few select institutions in the Northeast. That being said, there's lots of research done all over the country and we want to make sure that the best scientists, no matter where they are, are funded. I think that's something that can also gain a lot of support. So, I'm optimistic, but as you know, the Hill will always be a slog.

如果 2028 年发生，假设有一位 DSA 的人当总统，你认为一切会很快翻回原来的样子吗？你知道你的政府在这里创造的机构记忆是什么，以及这种回归科学黄金标准与由社会政治事物驱动之间的想法。

And if 2028 happens and there's, let's just say, a DSA person as president, you think everything will kind of quickly flip back to being the way it was? And you know what's kind of the institutional memory that gets created with your administration here and this idea of this return to this gold standard in science versus things being social political things driven.

我乐观地认为我们会在 28 年获胜。但我认为我之前说的这些想法也相当无党派。我的意思是，如果你只是看着科学生态系统并想要成功的人，我认为这些是可以推广的想法，你可以支持。我们的希望是，我们可以在未来两年内努力冲刺，证明它们确实有效，而从政治资本的角度来看，改变或扭转将代价高昂，因为它们会起作用。

I'm optimistic one that we'll win in 28. But I think too these ideas I said before are pretty nonpartisan. I mean if you're just someone looking at the science ecosystem and wanting to succeed, I think these are generalizable ideas that you can get behind. And our hope is that we can run really hard through the tape over the next two years and prove that they're actually working and sort of changing it or turning around is going to be costly from a political capital standpoint because they'll be working.

迈克尔·克拉齐奥斯，白宫科技政策办公室主任。感谢你今天接受采访。

Michael Kratsios, director of the Office of Science and Technology Policy here at the White House. Thank you for being with me today.

谢谢。这太有趣了。

Thank you. This was so fun.

我全力以赴。

I'm going all in.