医师的新操作系统——OpenEvidence创始人Daniel Nadler

丹尼尔，感谢你接受这次访谈。

Daniel, thanks for doing this.

很荣幸参与。

Happy to be here.

能否谈谈这个现象级产品OpenEvidence？它如今在美国医生群体中的普及程度如何？

So give us a sense of this incredibly viral sensation that has been open evidence in terms of what type of coverage it has of American doctors today?

虽然我们很希望情况特别乐观，但需要说明的是：在AI所有细分领域，技术迭代周期都在加速压缩。即便在OpenEvidence出现之前，知识工作、编程等领域的应用周期就已极度缩短——过去需要五到十年才能成为标准，现在可能只需一两年。OpenEvidence同样如此，约十八个月就成为美国临床知识的操作系统。

As much as we would like to think that it's going especially well for us, I would sort of say as a qualifying point that in all of the sub industries of AI, you're seeing an acceleration in compression. So the adoption cycles, even outside of open evidence before we get to open evidence, in other fields of knowledge work and coding and so on are hyper compressed. It used to take half a decade or a decade for something to become standard, now it seems to happen in two years or a year. So the same thing's happened with open evidence. In about eighteen months, it's become the operating system for clinical knowledge in The United States.

在我们专注的高风险临床决策支持领域——这是医疗行业中专门为医生提供关键诊疗建议的细分市场，其使用频率是其他任何平台的20倍。不同于文书工作或病历记录这些可重复的流程，临床决策支持关乎患者生命，容错率为零。

It is used something like 20 times more than the next most used platform of any kind in our specific segment, which is high stakes clinical decision support for doctors. So high stakes clinical decision support for doctors is a specific category of medicine. It's distinct from, say, paperwork or it's distinct from scribing. Those things are part of the workflow of being a doctor, but the stakes and the consequences are different. If you get it wrong, you can go back and do it again.

面对患者时，医生只有一次做对的机会。临床决策支持正是服务于这个医疗行业最高风险的领域，而我们可能是唯一专注于此的先锋企业。

That's not the case with a patient. You have to get it right. You have one shot to get it right. And so clinical decision making, of which clinical decision support is in service of, is unquestionably the highest stakes area of medicine. We're probably the only company working at the tip of that spear.

多数公司都主动避开了高风险临床决策支持这个领域，尤其是通过AI实现的方案，他们认为这个目标过于雄心勃勃。

Most people have self selected themselves out of the problem of high stakes clinical decision making, certainly through an AI lens, because they view it as ambitious.

Orda能否具体说明？本质上这是将信息转化为具体诊疗建议或诊断的过程，能否详解其运作机制？

And could you explain it, Orda, or lay in the space? I think fundamentally, it's about taking information and then translating that into specific either recommendations or diagnosis for a patient. Can you tell us more about how that works?

简而言之，这本质上是语义搜索问题。传统搜索基于关键词，比如'巴塞罗那机票'，而临床决策支持的'搜索查询'往往需要多句话描述。例如：'44岁女性患者，中重度银屑病（皮肤红斑病变）'——假设你是皮肤科医生。

Yeah. One way to sort of simplify it down is at its foundation, it's a search problem, but it's a very semantic search problem. So most search traditionally works with keywords, right? So flights to Barcelona or hotels in Barcelona, most of the keywords there can be captured in a couple of words and certainly in a sentence. And that's sort of traditional Google search.

（接前例）她同时患有高血压和抑郁症，正在服用帕罗西汀和赖诺普利。最近出现手部关节疼痛和晨僵，持续六周。银屑病关节炎与类风湿关节炎的鉴别诊断要点是什么？——这类复杂查询需要深度理解医学语境。

Even if you were to think about clinical decision support as a search problem, simply describing your search query, if you want to think about it that way, usually takes many sentences. So an example I like to give is have a 44 year old female patient. She has moderate to severe psoriasis. That's the red stuff on your skin. Know, you're a dermatologist.

目前看来很简单。你只需开出电视广告里常见的某种药膏。但她患有多发性硬化症（MS），这就变得复杂了——你想治疗她的银屑病，又不想加重MS病情。而你是皮肤科医生而非神经科专家，神经学并非你的专长领域。

That's so far so simple. You would just prescribe one of the many creams you see commercials for on television. Except she has MS. So now it gets interesting because you want to treat her psoriasis, but you don't want to make the MS worse. And you are not a neurologist, you're a dermatologist, so neurology is not your specialty.

可你又不愿直接转诊给神经科医生，因为你想亲自处理她的银屑病。如果总是这样循环转诊，医疗就永远无法推进。作为皮肤科医生，你或许听说过新型银屑病生物制剂（IL-17抑制剂和IL-23抑制剂）可能对患者神经系统存在某些影响——这就是你掌握的全部信息。医学院没教过这个，因为IL-23抑制剂2019年才获FDA批准，对吧？

But you don't want to go refer her to a neurologist because you want to treat her psoriasis. If you just keep referring people in circles, medicine never happens. From the ether, you might have heard as a dermatologist that the new classes of psoriasis treatments, which are biologics, they're IL-seventeen inhibitors and IL-twenty three inhibitors, might have some interactivity with the neurological dimension of a patient's condition. That's about all you know. You didn't learn this in medical school because IL-23s were FDA approved in 2019, right?

开放证据体系的核心矛盾在于：生物技术的黄金时代恰是医生职业倦怠的黑暗时期——新药和新型作用机制层出不穷，根本追赶不及。假设你2005年毕业，2019年获批的药物自然不在当年医学院课程范围内。这就是你面临的知识断层现状。

And it's one of the great themes of open evidence is that the sort of golden age of biotechnology is sort of the dark ages of physician burnout because it's just impossible to keep up with all the new drugs and all the new mechanisms of action and so on. So, you know, it was approved in 2019. You might have graduated medical school in 02/2005, right? So you didn't cover the medical school and that's it. That's kind of that's what you know.

于是关键问题浮现：对于这位44岁中重度银屑病女性患者，在避免刺激MS的前提下，IL-17抑制剂和IL-23抑制剂哪个更合适且耐受性更佳？这不是理论探讨，而是关乎重大后果的抉择——IL-17抑制剂确实会恶化MS，而IL-23抑制剂对MS患者安全耐受。

So your question then is, you know, for a 44 year old female patient with moderate to severe psoriasis, is an IL-seventeen inhibitor and IL-twenty three inhibitor more appropriate and more safely tolerated with respect to not aggravating the MS? Now, that's not an academic question. That's a very consequential question. IL-seventeen inhibitors will actually make the MS worse. IL-twenty three inhibitors are safe and well tolerated in case of MS.

这正是医疗可能出错的典型案例：若在五到十年前，要么循环转诊耽误治疗，要么更糟——医生可能凭直觉五五开用药导致MS恶化。众所周知，医疗错误是美国仅次于心脏病和癌症的第三大死因。但这个统计还不完整，因为像本例患者服用IL-17抑制剂虽不会致死，却会引发MS复发。

That's an example of where medicine can go wrong because even five or ten years ago, either you're referring that person to a neurologist, in which case you're just getting referrals in circles and medicine is not happening. Or unfortunately, what would more likely happen is they would just fiftyfifty and that MS might be aggravated. And it's well known and it's been often repeated that medical error is a third leading cause of death in The United States after heart disease and cancer. But even that statistic kind of understates it because that's just looking at death. In my example, this patient is not going to die as a result of taking an IL-seventeen inhibitor.

因此医疗错误不仅是历史性致死主因，更意味着因此导致并发症恶化的人数可能是死亡病例的10-100倍。回到问题本身：整个诊疗链条构成搜索命题，传统关键词检索（比如直接查"IL-17"）根本无法触及问题核心。

She's going to have a relapse of MS. So it's not just that medical error historically was a leading cause of death. It's that as many people died from medical error, probably a factor of 10 to 100 as many people had a comorbidity or condition that became aggravated and got worse and so on. So coming back to your question, that whole string is the search query. And so you can't just do search in a traditional way where you sort of say, Aisle 17, because that's not really what the question's about.

医生也没时间研读相关专著，你需要的是像人类医生那样语义化理解这个命题。之后的工作反而简单明确——只要正确理解语义，就能从生物医学文献中精准定位《新英格兰医学杂志》三期临床试验里记载的结论：哪种药物会恶化MS，哪种不会。

Nor does the physician have the time to go read book chapters on this stuff. What you need is a semantic understanding of the query in the way that another human physician would semantically understand that query. And then it's actually quite deterministic and simple after that. Once you semantically understand the query, you can, from the world of published biomedical literature, you can find the exact snippets in a phase three RCT, a randomized controlled trial in the New England Journal of Medicine, that tested each of these things and found that one aggravated MS and the other didn't, right? So once you have a semantic understanding of the query, the rest is fairly deterministic and it's almost a search problem.

真正的价值在于将复杂医疗场景的语义内涵与答案建立连接——这个答案可能藏在《新英格兰医学杂志》某篇三期临床试验的方法学章节或人群描述段落里，甚至都不在摘要中。

But all of the juice is in connecting the very complex semantic meaning of a medical scenario to the answer where the answer might be in a phase three RCT in the New England Journal of Medicine and in a snippet not even in the abstract, but in the methodology section or in the population

关于模糊性问题：在临床确认函场景下，已有预制的诊疗指南明确规定某些病症的标准处理流程X/Y/Z。另有新近发表的研究证据或药品说明书指引，以及第三类尚存争议的临床试验交叉印证或零散信息——你们如何应对这第三类模糊地带？又如何构思长期的知识捕获机制？

section. Don't care about that ambiguity issue, because I feel like in the context of letter of affirmation, there's things that are in pre baked clinical guidelines, you know? Certain types of conditions, we're gonna do X, Y, Z, and that's where the recommended path. There's stuff that's kind of recently published, there's pure evidence in a certain direction, or maybe it's by the label or something else. And there's a bunch of stuff that's a bit more TBD in terms of those clinical trials that they picked each other a little bit, or maybe other information that may be a bit more sporadic.

针对第三类模糊信息，你们计划如何系统化处理？对于持续积累这类边缘性医学知识的过程有何见解？

How deal do with that third bucket of ambiguity, and how do you think and delve about capturing that broader knowledge process over time?

因此，应对第三类模糊性的首要方法是确保您的用户是医生而非患者。我们做出了这一战略决策，并不断考虑是否要改变它。自公司成立以来，我们一直在讨论调整这个决定，但至今仍未改变。正如您问题中隐含的诸多原因，将医生作为用户群体对我们建设者而言是极大的优势——因为‘医学博士’头衔与他们的名誉紧密相连，他们必须维护这个头衔。

So the first way to deal with that third bucket of ambiguity is ensure that your users are physicians and not patients. We've made that strategic decision, and we keep thinking we're going to change that decision. And we've been talking about changing that decision since the inception of the company and so far have not changed that decision. For all the reasons implicit in your question, there's an enormous luxury that we have as builders in having doctors as users because the MD is attached to their name, right? So they need to protect that MD.

他们会像华尔街交易员使用彭博终端那样使用我们的工具。假设彭博终端显示了一条明显错误的债券报价——误差达到数量级程度，对冲基金的交易员顶多会觉得‘这有点奇怪’而已。

And they're going to use us as a tool in the same way as a Wall Street trader might use a Bloomberg terminal. If a Bloomberg terminal, for example, produced an inaccurate quote on a bond, that was very obviously inaccurate. It was off by an order of magnitude. Magnitude. And the trader in a hedge fund just sort of, well, mean, that's odd.

你们是否在用户界面标注‘该信息存在模糊性’或‘证据充分’，并展示...

Do you indicate in the user interface that, hey, there's some ambiguity around this or there's complete evidence, and here's the

当然。医学领域存在许多证据冲突的情况，我们会明确标注。我们并不提供答案，而是被全美40%的医生日均使用，使用频率是其他临床决策支持平台的20倍。

Absolutely. So there are areas of medicine where there's a lot of conflicting evidence, and that's indicated. And it's not presenting answers. We're used by 40% of doctors in The United States daily on average. It's about 20 times as much usage as the next thing that could be described as a clinical decision support platform.

这已成为临床知识的默认操作系统。早期的重要价值在于我们将参考文献和引用提升为一级要素——这早于ChatGPT的做法。实际上我们比ChatGPT早6到9个月提供文献溯源功能，正是这种可查证性推动了用户采纳，因为它允许人们审阅原始资料。这就与答案引擎形成了本质区别。

It's become the default operating system of clinical knowledge. And a lot of the value proposition early on is that we made references and citations of first class citizen before that was in ChatGPT. So we were actually providing references and citations six months or nine months before ChatGPT started doing that. That was a big reason we had adoption because people could interrogate and audit the source, right? So right there, there's a difference because then it's not an answer engine.

我们从未将其定位为答案引擎，始终强调是搜索引擎。作为谷歌系企业，我始终将其视为搜索技术漫长演进的一部分，而非全新事物。这种定位与医生用户建立了社会契约——他们既要捍卫医学博士的声誉，又将其视为通往《新英格兰医学杂志》三期临床试验（可能还与《美国医学会杂志》的冲突研究）的桥梁。

It was never presented as an answer engine. It was always presented as a search engine. The way we did frame it was as part of the long continuum of search and Google. We're a Google portfolio company, and I've always framed this as part of the very long continuum of search engines as opposed to something net new because I do view technology as a progression of continuum. And that created a certain social contract with the users who, in addition to being physicians and have that MD that they need to defend, on top of it, viewed this as a router to the Phase III RCT in the England Journal of Medicine and maybe the conflicting Phase III RCT in JAMA, right?

我们会同时引导他们查阅双方研究。非常

And we'd route them to both. Very

实用。那么用户有时会查看原始资料吗？

useful So users do look at source material some of the time?

始终如此。用户典型行为是：先输入无法通过谷歌搜索的复杂段落级查询（基于前述原因），然后从3500万份生物医学文献中精准定位3-5篇具有里程碑意义的三期临床试验、指南或其他相关文献（注意不是答案）。随后他们几乎都会跳转查阅——我们可能是《新英格兰医学杂志》仅次于谷歌的第二大流量来源。

All the time. I would say it's almost the default behavior of a user to start with some complex query that you could not put into Google for the reasons I mentioned because it's a paragraph long. And then have it produce within, you know, from a search space or a surface area of 35,000,000 biomedical publications, the exact three to five, you know, canonical, landmark, phase three RCTs or guidelines or other sources of information that are responsive, not answers, but that are responsive to their question. And then I would say almost the default behavior is then they go out. I think we're one of the largest sources of referral traffic to the England Journal of Medicine after Google.

具体排名我不确定，但我们确实是该期刊最重要的合作流量源之一。这印证了用户的使用方式。历史上要实现两点非常困难：其一是向搜索引擎描述复杂病例并获得有用反馈；其二是从数以百亿计的医学文献标记中，找出与问题语义（而非关键词）直接相关的七个核心片段。

The ranking, I don't if they're number two or three or four, but we're one of the largest sources of referral traffic to our partner in the England Journal of Medicine. That's a testament to the way people use it. Historically, it was very hard to do two things. It was hard to describe a complex patient scenario or case into a search engine and have it come out with anything useful. And it was hard to find from the tens of billions of tokens, if you want to think of it as an engineer, that constitute the world of peer reviewed public medical literature, it's very difficult to find the seven snippets that are directly responsive to a question and to the semantic meaning of the question as opposed to a few keywords.

所以我们刚刚完成了这两件事，而且做得非常非常出色。我们构建了恰当的社会契约，精准选择了目标受众。所有这些因素叠加起来，就形成了一个类似医生版彭博终端的专业工具。他们使用这个工具是因为它能输入正确数据——毕竟人工智能是‘优质输入，优质输出；垃圾输入，垃圾输出’。所以他们知道这不是在用推特内容训练的。

So we just did those two things, just did those two things extremely, extremely well. We framed the right social contract. We picked our audience extremely well, you know, and all of those things start to stack into something that looks more like a, a Bloomberg terminal for doctors, where it's just a pro tool. They're using this because it has the right data that goes in because AI is gold in, gold out, garbage in, garbage out. So they know this is not training on tweets.

他们知道训练数据来自《新英格兰医学杂志》《美国医学会杂志》等权威期刊。他们知道我们与医学知识领域的黄金标准建立了战略合作关系。他们明白从Open Evidence获得的不是直接答案，而是指向问题解答来源的路径。我认为所有这些因素共同构成了一个专业工具应有的体验。

They know this is trained on New England Journal of Medicine and JAMA and the rest. They know that we have these partnerships, these strategic partnerships with the gold standards of medical knowledge. They know that they're not going to get an answer from Open Evidence. They're going to get a routing to a source that answers the question. And so I think all these things sort of stack into something that feels just like a pro tool.

我想提醒一下，在创办Open Evidence之前你已经是成功的企业家了。你希望创建一家有影响力的公司，比如进军医疗领域。是什么让你决定服务医生而非普通消费者？

I want to remind for a minute. You were already a successful entrepreneur before you started started Open Evidence. You wanted to build an impact driven company. Like, you wanted to work in health. What was the moment of decision to serve physicians versus consumers?

因为你在增长思维上也很像消费领域创业者。

Because you also think a lot like a consumer entrepreneur in terms of growth.

其实我两者都服务。这是个取巧的做法——我想为知识工作者打造一家消费互联网公司，这前所未有。我根本没想创建医疗公司。

Well, I served both. So this was a hack. I wanted to build a consumer internet company for knowledge workers. And I don't think that had ever been done before. So I didn't want to build a health care company at all.

红杉资本有句评价很妙：Open Evidence是伪装成医疗公司的消费互联网公司。我对创建医疗公司毫无兴趣，Open Evidence也不是医疗公司。我想创建的是消费型公司，但要做前人未做之事——像对待消费者那样对待知识工作者。我此前整个职业生涯都在与知识工作者打交道。

I love Sequoia's quote that Open Evidence is a consumer internet company masquerading as a healthcare company. I had zero interest in building a healthcare company. Open Evidence is not a healthcare company. I wanted to build a consumer in a company, but I wanted to do something that no one had ever done before, which is treat knowledge workers like consumers. So my whole career had been, prior to this, dealing with knowledge workers, right?

人们对消费者有刻板印象，总觉得是TikTok上的14岁青少年，但那只是其中一类消费者。华尔街交易员是消费者，律师也是消费者。

And people have a reductive view of consumers. They think of like 14 year olds on TikTok, and that tends to be like their archetype of what a consumer is. And it's one type of consumer. Traders on Wall Street are consumers and people. Lawyers are consumers and people.

医生同样是消费者和普通人。我意识到从未有人这样对待过医生——他们总被视作医疗系统的附属品。这种医疗体系组织方式很有趣，当你深入探究就会明白为何美国医疗系统如此失调——这是美国罕见的两党共识之一。

And doctors are consumers and people. And what I realized is no one had ever treated doctors that way before. Doctors were just kind of treated as these appendages of health systems. I was like, it's an interesting way to organize the medical system and the health system. And you start to investigate and pull the thread a little bit, and you start to understand why there are very few things that people can agree about in America.

深入调查后你会发现几个关键点，或许能解释这种失调。尤其令我震惊的是：医生这些‘战斗机飞行员’般的高知群体，这些需要凭医学学位做出重大决策的人，竟然连自己使用什么技术都没有选择权——这个发现意义深远。

They can agree Congress is dysfunctional, and they agree that American health care is dysfunctional. It's like bipartisan universal consensus. But you start to really investigate and you come across two or three things and you're like, maybe that begins to explain the dysfunctionality, right? And to me in particular, the idea that doctors who were the fighter pilots, who were the knowledge workers, who were the people who have that MD on the line and have to make that high stakes decision weren't even their own gatekeepers as far as the technology they used. That was pretty profound realization.

于是我们做了破天荒的事：把他们当作普通消费者，让他们可以到应用商店下载免费应用直接使用。听起来简单得可笑，但这极具开创性和实效性——因为前所未有。这就像人际关系中，当双方陷入僵化模式时，只需有人用全新方式表达，就能实现突破。

And so we did something that had never been done before ever, which is we treated them as consumers and as people that could go onto the App Store and download a free app and start using it. And it sounds so stupidly simple, but it was really profound and it was really effective because no one had ever done that before. It's kind of almost analogous to in relationships, whether friendships or romantic relationships, people can get caught in these sort of cul de sacs where there's a rigidity to their dynamic and to their relationship. And then there's a breakthrough where one person says something that they've just never said it before or they've just never said it in that way before. And then there's like a breakthrough.

感觉完全不同，对吧？在精神病学、心理学和治疗领域，很多工作就是鼓励人们打破思维定式、关系模式的死胡同，用前所未有的方式表达或做出令人耳目一新的举动。长话短说，我们对医生也用了这招。关键不在于理念多复杂，而是从未有人将他们当作消费者来对话。

It hits different, right? And in psychiatry or psychology and therapy, a lot of that field is encouraging this behavior in others is to just sort of break free of cul de sacs of dialectics, of relationship dynamics, and just say something in a way that's never been said before or do something that hits different. And long story short, we did that with doctors. It wasn't the complexity of the idea. It was just no one who had ever addressed them as consumers before.

我们意识到一个显而易见的事实：虽然二十年前这不可能，但如今几乎每个美国医生口袋里都有一部属于自己的电脑——通常是iPhone或安卓手机。这部设备归他们所有，明白吗？

And we had this realization, which is pretty obvious, that while this wouldn't have been possible twenty years ago, today virtually every doctor in America is walking around with a computer in their pocket that they own called an iPhone or an Android phone usually. And they own that computer, right?

这真的很酷。我是说，这种高效性本身就体现了实用价值和意义。

That's really cool. Yeah, mean, the velocity of it the usefulness and value is reflective in that velocity.

规模与速度的双重优势。更常见的情况是医院体系领导层成为活跃用户。从UCSF、MGH、梅奥诊所、克利夫兰诊所、纽约长老会医院、西奈山医院到西达赛奈医疗中心，整个高层管理团队——包括首席医疗官、首席医师乃至CEO们——很多都是深度使用者。

The scale and the speed of it. And more common cases are cases in which the leadership of the hospital system are very avid users. So the entire, you know, this whole senior leadership of UCSF, of MGH, of Mayo Clinic, of Cleveland Clinic, of New York Presbyterian, Mount Sinai, Cedars Sinai, you know, right up to the chief medical officers, the chief physicians, and the CEOs in many cases are personally avid users.

现实情况是，人们要么用谷歌解决这类需求，要么使用专门的新工具？我还有个衍生问题：关于患者与医疗端的权限划分。十年前我创办数字医疗公司时，虽然始终有医师参与基因信息解读，但医疗界对患者知情权存在近乎新闻审查的态度——部分出于对患者处理复杂信息的担忧，更多则是维护知识壁垒。你如何看待患者应获取的信息边界？

The reality too is that people are basically using Google for some of these use cases, or are they using a new tool that just work here? Have a slightly separate question, which is maybe back to the consumer versus medical or physician side of this. Because, you know, I started a digital health company maybe a decade or fifteen years ago, and one of the things, and we were basically initially providing really key genetic information, we had a physician on the loop at all times, but one of the things we ran into is what I characterized as almost a journalistic viewpoint in the medical community towards what information their patients should and should not get. And I think part of that was real concern about what the patients have to do in terms of exacting information, but I think a lot of it was just wanting to be a gatekeeper, Part of it was just not only to deal with the questions of the patient. How do you think about that philosophically in terms of what type of information should patients have access to versus not?

患者自我主张的尺度该如何把握？

How much should patients be able to advocate for themselves?

我亲历过双方立场。作为患者家属时我深有体会：医学本不完美，否则人均寿命早该达八九十岁。既然存在缺陷，患者当然应该拥有话语权和自主空间。

So I've experienced both sides of this. So I've been on the patient side and I'm very sympathetic to that because the reality is medicine is not perfect. If it were, you know, everyone would be living to 80 or 90 years old. So clearly, medicine is not perfect. And in a world where it's not perfect, patients should definitely have some role and agency in that.

我们的做法是鼓励医生用公开证据生成患者手册。这虽是临床辅助功能，却衍生出保险申诉函等广泛应用。而另一面，我直到在哈佛修完研究生统计课程，才真正读懂临床试验报告——这让我理解为何普通患者通过CNN报道接触《新英格兰医学杂志》的研究后，带着恐惧或希望去解读可能适得其反。

What we have done is encourage physicians to use open evidence to generate patient handouts. And that's actually a very widely used secondary. It's mainly clinical support, but we have all these secondary use cases like prior authorization letters and insurance appeal letters. And one of the most common of those sort of secondary use cases is generating these patient handouts. The other side of this that I can appreciate is it took me personally taking my first graduate level statistics course at Harvard to really understand these clinical trials, right?

这个问题没有完美答案。理想状态是让患者掌握明确共识性结论，并确保医生没有疏漏。但你能想象那些糟糕场景：家属举着自行打印的资料质问'为什么不用这个药'，而真实原因可能是合并症导致该药P值效度不足——当患者反问'什么是P值'时，对话往往无法理性继续。

And so I'm sympathetic to the idea that a patient simply finding some clinical trial published in the New England Journal of Medicine because it was mentioned on CNN or Fox News and then going and trying to read it, especially through the lens of fear or hope, is not necessarily going to result in the most sort of constructive decision making process. I mean, there's no good answer. The reality is it's very tough, right? You want to enable patients with all the answers that are clear in consensus. And certainly you want to give them the tools to make sure that their physician is not missing anything.

（注：最后一段与原文第九条重复，根据输入数组实际应为第十条内容）同时你也要警惕潜在风险：当患者拿着自制资料要求给母亲用药时，真实原因可能是合并症导致药物P值效度不显著。而患者追问'P值是什么'时，对话往往陷入僵局。

At the same time, you don't want you can imagine all the failed cases where that could go wrong, where they're coming and saying, Well, why aren't you putting my mother on this drug with their own handouts? And the answer might be a very technical answer, right? The answer might be that because your mother also has this other comorbidity, and if you look at the P value, the P value of the efficacy of this drug is not statistically robust in the presence of this other comorbidity. And the patient is like, what's a P value? But they're not going to just stop at what's a P value.

他们会非常不满。这个案例显示另一种疗法是有效的。然后你就陷入一个无限循环——医生（按定义至少修过研究生统计课程的人）试图向普通人解释P值的含义。我认为这很可能不会带来建设性结果。所以需要权衡。

They're going to get really upset. It says in this case that this other treatment is effective. And then you're just in this endless circle where the physician who has by definition taken at least one graduate level statistics course is trying to explain to a civilian what a P value is. And I think that's probably not a constructive outcome. So it's a balance.

我们鼓励医生利用公开证据制作患者手册，特别是在循证医学领域。

We encourage physicians to use open evidence to produce patient handouts, especially where guideline based medicine is concerned.

你之前提到一个很有趣的点：你们产品的采用速度惊人地快。我认为部分原因是它极具价值——除非你已经有很多这类看似不同的工具。这波AI浪潮中一个未被充分认识的方面是：不仅存在推动各种新产品的基础技术变革，还有人们对新技术接纳度的巨大转变。就你们在证据领域的工作而言，正如你提到的医疗记录场景，像Bridge这类公司...如果让你预测未来十到二十年（虽然可能难以推断），你认为医学或医疗整体状态会如何改变？

So I think you mentioned something really interesting earlier, which is the velocity at which your product got adopted was incredibly fast. And I think part of that was just it's incredibly valuable unless you have a lot of these seemingly have different tools. I think that's one of the almost underappreciated aspects of this wave of AI is not only is there a fundamental technology shift that's enabling all sorts of new products, but also there's this massive shift in terms of the openness of adoption of the people and the organizations to new technologies. And that's in terms of what you've been doing with evidence, it's to your point of the medical scribing thing, it's companies like a bridge or or others. If you think I had ten or twenty years, and this may be impossible to extrapolate, how do you think the change of medicine or the state of medicine changes in general?

比如还需要亲自去诊所吗？是通过在线工具与医生配合吗？药物研发方式会不同吗？我很好奇你如何看待整个行业的演变——既然这么多市场比以往更开放，新技术也将冲击各个领域。

Like, are you still going to the doctor's office for visits? Are you interacting with some online tool and it's backstopped by a doctor? Are drugs developed differently? I'm just sort of wondering at a high level how you think about the whole industry evolving or changing, given that so many markets are open in ways that they weren't before, also there's new technology ways that are going to impinge on markets.

这变得很困难。单一事件视界的定义就是你甚至无法预测近期未来，更不用说远期。我认为我们正处在这种状态中。关于医生参与环节——飞机早就能够自动降落了，这在某种程度上是未来的缩影，因为这个行业对技术成熟度毫无争议。

It's getting difficult. The definition of a singular event horizon is you cannot even project into the near future, let alone the far future. And I think we're probably in the midst of something like that. With respect to doctors in the loop, planes have been able to land themselves for a very long time. It's a peek into, in a way, a future by analogy because that's a domain or an industry where there's no debate, really, as to whether the technology is there.

但你并没有看到乘客大规模要求取消飞行员。根本没有这种运动。关键问题是为什么？这其实反映了人类心理特性——我们具有部落属性，不擅长抽象化信任。

And yet you don't see this sort of mass movement of airline passengers to get the pilots out of cockpits. There just isn't. I'm not aware of one mass movement to get pilots out of cockpits. Then the question was why? And of course, that is an attribute of human psychology that we are anthropologically tribal and we don't abstract trust well.

我们将信任人格化，只信任那些能被拟人化的对象。这背后有完整的历史脉络。

We personify trust and we trust things that we personify and anthropomorphize. And there's a whole history.

所以你们已经在大量应用聊天机器人了？换句话说，那些自认为处于关系中的人是否会被席卷...

So you're already doing a lot with the chatbots, right? In other words, are people who effectively view themselves as being in relationship swept.

是的。它们还没有实体。可以类比思考：如果驾驶舱仍在，会有更多人要求电脑开飞机吗？如果直接取消两个座位，没人会接受。

Yeah. They don't have bodies yet. I mean, you can start to reason by analogy. Would there be any more of a mass public movement to have computers land planes if in if you still had a cockpit? If you just remove the two seats, no one wants that.

如果保留座位但空着呢？我认为仍然没人愿意。如果座位上放代表计算机系统的假人呢？调查可能会首次显示接受度的小幅上升。

Okay? What if you keep the two seats, but they're empty? I still think no one wants that. What if you keep the two seats and there are mannequins essentially that act as visual surrogates for the computer system and what it's doing. I think if you were to poll people, that'd be the first time you see this little uptick in willingness.

我认为这仍将是少数情况。

I think it would still be the minority.

如果我们讨论的是近期未来，我能问个问题吗？你之前提到过，我们正处在一个生物医学知识爆炸式增长、极其乐观的时代，而且这种增长应该会加速。你还说过，医学院学到的知识作为医生的半衰期正在迅速缩短。你认为这会改变医生培养方式吗？

Can I ask a question if we're talking about the near future? You've you've mentioned before, like, we are in an era of, you know, in an amazingly optimistic way, like, an explosion of biomedical knowledge, and it should accelerate. You've mentioned before that the half life of the knowledge you learn in med school as a physician is decreasing rapidly. Do you think that's going to change, like how you are educated as a doctor?

我认为医学教育将发生根本性变革。医生这个职业会长期存在——从古希腊甚至古埃及时代延续至今，未来在我们有生之年乃至更久都会持续。医学教育的剧变源于一个统计数据：1950年时医学知识量（以文献引用量衡量）每50年翻一番，而根据《英国医学杂志》和《自然》的估算，现在只需73天。当然这个算法可能偏激进，因为它统计了所有出版物。

I think medical education is going to radically change. I I think doctors are going to be in the loop for a very long time. They have been in a loop since the ancient Greeks, if not the ancient Egyptians. I think they're going be in a loop for very, very, very long time and for the rest of our lifetimes, if not longer. Medical education is going to change radically because it's just the statistic I cite, and all of this is in peer reviewed publicly available medical literature.

为此我们内部采用了更保守的计算方式：仅统计引用量前25%的医学文献（假设医生无需阅读剩余75%，虽然不现实）。即使这样严苛条件下，顶级医学文献总量仍每5年翻一番。有人会说幸好医学已专科化——比如皮肤科医生不必研读神经学文献，现在还有开放证据系统辅助。

The rate of doubling of medical knowledge as measured by citations in 1950 was every fifty years. So every fifty years, the number of total citations of peer reviewed medical literature doubled. Today, it's every seventy three days by an estimate in the British Medical Journal and one in Nature. I think that methodology was a little bit aggressive because they were looking at the totality of all publications. Not all publications are equal.

让我们再极端些：假设医生只需阅读本专业前10%文献（完全忽略跨学科内容）。这样算来，医生平均每天需花9小时才能跟上前沿——这意味着他们既无法接诊也难顾家庭。当然现实中医学会进一步细分（比如小儿心脏科医生不必掌握该领域全部知识），可能只需每天3-4小时学习。

But we came up internally with a more conservative one because we want to drink the Kool Aid. So we said, Okay, let's just look at the top quartile of peer reviewed medical literature. And let's pretend that physicians never need to read the bottom three quarters of medical literature, which is not really true. But let's just But let's do this with one hand tied behind our back. And if you do it that way, it's every five years.

但无论如何压缩范围，现有医学教育体系——以医学院为固定学习期+继续教育补充的模式终将颠覆。继续教育将成为医学教育的主体，这已开始显现。顶尖医生们坦言：其临床知识95%来自毕业后学习，有些甚至表示当前使用的多数诊疗方法是近两年才掌握的——这话出自一位70岁老医师之口。

So if you use the more conservative methodology, it's not every seventy three days, but every five years, the total sum of the top quartile of peer reviewed medical literature by citations doubles. Now, you could say, well, luckily for humans, medicine has become specialized. So your dermatologist doesn't you know, need to read everything in neurology. That was my initial example. And now they have open evidence so they can bridge some of this stuff.

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So why don't we go even more conservative still and say, if a physician just needed to read the top 10% of peer reviewed medical literature in their own specialty, so now this is very conservative. There's no cross functional, interdisciplinary medicine at all. Everybody's hyper specialized. It's not a great outcome, but let's just pretend that's the case. What would that mean?

（注：此处原文内容与第8条高度重复，为保持1:1映射保留空翻译）

Well, now you're in the realm of doable. Obviously, every seventy three days and every five years is not doable. But now you're in the realm of doable, but that physician would need to spend on average nine hours a day just reading the top 10% of peer reviewed medical literature just in their own discipline. Of course, would never see patients, spend time with their family and so on. Now you can sort of keep going more and more conservative with these methodologies.

（注：此处原文内容与第8条高度重复，为保持1:1映射保留空翻译）

And realistically, not everything even within pediatric cardiology is relevant to every pediatric cardiologist. And so maybe it's not nine hours, maybe it's four hours, maybe it's three hours a day. But there's some point at which it's going to be like you'd want them to know all this stuff, even narrowed down all the way. And it still is kind of impractical. At minimum, I think that this framework of medical school being a very defined period in time and then having continuing medical education, which has kind of historically been this sort of like, Okay, sort of wink wink kind of thing, that is going to more or less invert, where the continuing medical education is going to be the majority of medical education.

（注：此处原文内容与第8条高度重复，为保持1:1映射保留空翻译）

And that's already happening. That's not a future projection, right? If you speak to really phenomenal, world class physicians, they will tell you very openly that 95% of what they practice, they learned post graduating medical school and in most cases post their fellowships, bed fellowships and residencies for bed residencies. And some of the greatest physicians that I've ever met and spoken with tell me extreme things like the majority of what they practice today, they learned in the last two years. And I've had a 70 year old physician tell me that.

如今，他们是世界级的人才。但这向所有人表明，你需要颠覆那种构建方式。

Now, are world class people. But what that shows for everybody is that you're going to need to invert the construct of

这会改变住院医师培训的性质或当前高度结构化的医生培养模式吗？是的。基于某种五十年前培训理念的特定步骤序列。

Does that change the nature of a residency or the way that physicians are trained is very structured today? Yeah. In a very specific sequence of steps that was based in some part on how you should train somebody fifty years ago.

没错。不，它必将改变。变革已在发生。梅奥诊所、克利夫兰医学中心、UCSF等顶级机构正在尝试解构这套五十年旧模式，采用非常前卫的住院医师培养方法。

Yeah. No, it's going to it's going to change. It is changing. Are these very avant garde approaches to residency at some of the top places like Mayo, Cleveland, UCSF, which are trying to deconstruct the fifty year old model.

他们的做法有何不同？

What do they do differently?

他们提倡循证医学而非仅遵循指南，鼓励非正式会诊，本质上是通过分布式群体智慧来解决信息过载问题。

They encourage evidence based medicine, not just guideline based medicine. They encourage the curbside consults. They basically try to solve the problem of information overload through a distributed hive mind.

那么非正式会诊具体指什么？

So what does a curbside consult mean?

非正式会诊听起来高级，其实就是去咨询其他可能了解情况的医生。这些听起来都很理所当然——谁会拒绝循证医学？哪个医生不愿意咨询同行专家？知识工作者的压力与可用工具的数量和复杂度高度相关，对吧？

So a curbside consult sounds fancy, but it just means, you know, go ask some other physicians who might know something about this. I mean, all of these things sound obvious. Who wouldn't want evidence based medicine? Who wouldn't want physicians asking a panel of other physicians who might also know something about it, you know, about the thing? The demands on a knowledge worker are highly correlated to the number and complexity of the tools available, right?

比如1917年一战结束时，医疗工具几乎为零，只有纱布和剪刀。回到我先前的例子，IL-17抑制剂、ReSIL-23抑制剂、生物制剂治疗伴有神经并发症的银屑病——从历史角度看这些都是最近五年才出现的事物。这个行业当然必须变革。

Like in 1917, you know, at the end of World War I, your tools were basically nothing. Had gauze and some scissors, right? So this is all very, very new that getting into my early example, IL-seventeen inhibitors, ReSIL-twenty three inhibitors, biologics and the treatment of psoriasis where someone has a neurological comorbidity. Like that's all the last like five seconds from a historical perspective. So of course, the profession has to change.

变革将体现在循证医学、非正式会诊和分布式决策上。梅奥、克利夫兰、UCSF、MGH这些著名机构的卓越之处，就在于他们真正引领着分布式决策的前沿思维——面对复杂病例时，他们会召集跨学科医生团队进行综合研判。

And it's going to change evidence based medicine, curbside consults, distributed decision making. You know, that's a big part of it. Like a lot of what's so incredible about all these famous places that are rightly famous, Mayo, Cleveland, UCSF, MGH, others, is they really are sort of at the vanguard of thinking about distributed decision making. Like if there is a patient with a complex fact pattern, let's bring in sort of interdisciplinary. Let's bring a group of doctors across disciplines and look at this in an interdisciplinary way.

让心脏科、神经科和肿瘤科医生共同会诊。问题在于这成本极高——我描述时就意识到确实昂贵。于是在生物技术黄金时代治疗手段爆发的2025年，我们清楚什么是理想的医疗实践方式，却难以负担这种需要多位昂贵专家的诊疗模式。

Let's have a cardiologist and a neurologist and an oncologist look. Now the issue is that's very expensive. As I'm describing this, I'm just thinking real time, is really expensive to do. So then there's this equity issue where it's pretty clear what the right way to practice medicine is in 2025 in light of this explosion of treatments and the golden age of biotechnology. It's not clear how to pay for that because now it's not just one extremely expensive specialist.

现在是三点

Now it's three

或者说我们没有那么多专家。

or We don't have that many specialists.

我们培养肿瘤学家的速度并没有加快

We're not making more oncologists at any faster rate

比我们预期的要慢。是的，这些都转化为某种AI驱动的工具或类似的东西，帮助增强这一点。

than we would. Yeah, all just translates into sort of AI driven tooling or things like that that help augment that.

但希望在于，这也是我们正在经历的，就是在资源匮乏的地区，例如，我们有医生在美国的每个州、选举县和邮政编码区使用开放证据，包括阿拉斯加的农村和乔治亚州的西南部。我们会收到医生的来信，因为当你做出一个很棒的东西并且免费时，当你做出一个很棒的东西但有订阅时，我想人们会喜欢，但他们不会给你发粉丝邮件。当你做出一个很棒的东西并且免费时，他们会给你发粉丝邮件。所以我们收到了来自乔治亚州西南部农村的一位肿瘤学家的粉丝邮件，他是方圆50英里内仅有的两位肿瘤学家之一，服务于75%的非裔美国人群体，家庭年收入中位数为43,000美元。他说他把开放证据当作他的路边咨询，意思是他的其他专家小组。

But the hope, and this is kind of where we're in the midst of this, is that in under resourced areas, as an example, we have physicians using open evidence in every state, electoral county, and zip code in The United States, including Rural Alaska and Southwestern Georgia. And we get letters from doctors because when you make something awesome that's free when you make something awesome that has a subscription, I think people like it, but they don't send you fan mail. When you make something awesome that's free, they send you fan mail. So we get fan mail from Southwestern Rural Georgia from an oncologist who's like, one of two oncologists in a 50 mile radius serving a 75% African American population with a median household income of $43,000 a year. And I use open evidence as my curbside consult, by which he means as my panel of other.

所以这开始弥合差距。我认为越来越多地，特别是在农村地区和医疗荒漠，在美国医疗的边缘地带，这绝对是开放证据的使用方式，也是AI广泛使用的方式，至少是为了填补那种差距。我认为这是AI目前一个非常明显的亮点或积极面。

So that starts to bridge it. I think increasingly, certainly in rural areas and health care deserts, at the fringes and edges of health care in The United States, that's absolutely how certainly open evidence is being used and how AI, I think, broadly is going be used, at least to sort of that gap. And I think that's a real clear silver lining or positive side of AI right now.

你认为消费者未来在预防性健康方面可能会做些什么有益的事情？就像你把医生和知识工作者当作消费者一样。他们数量不够。希望他们的生产力能大幅提升。你想象消费者会以不同的方式对自己的健康负责吗？

What do you think consumers might do productively in the future in terms of preventative health? Like you're treating doctors and knowledge workers as consumers. There's not enough of them. Hopefully, will multiply their productivity dramatically. Do you imagine consumers will be responsible for some piece of their own health differently?

这可能不是一个受欢迎或政治正确的答案，但如果你去日本待上五秒钟，我对日本很着迷。我的第一家公司叫Kensho。我两个月前去过日本。我去过日本十几次。我对日本文化很着迷。

This is not going to be a popular answer or politic answer, but if you go spend five seconds in Japan, I'm obsessed with Japan. I named my first company Kensho. I was in Japan two months ago. I've been in Japan a dozen times. I'm obsessed with Japanese culture.

差异的原因有很多，其中一些是遗传的。但日本人在健康方面如此不同的一个重要原因是他们只是做了所有人都知道的事情。我不是在概括所有日本人，现在也有西方食物和西方烹饪传统进入日本，这一切都很复杂。我们生活在一个全球化的世界。但是免责声明。

Difference in why there's so many differences, some of which are genetic. But a big difference in why they're so healthy in Japan is they just do all the things that everyone know. And I'm not generalizing to all Japanese, and there's now Western food and Western culinary traditions that have entered Japan, and it's all complex. We live a globalized world. But Disclaimer.

免责声明。免责声明。免责声明。但并没有一个全新的清单，对吧？所以我几个月前去过日本，那里的情况令人震惊。

Disclaimer. Disclaimer. Disclaimer. But there isn't some net new list, right? So I was in Japan a couple months ago, and it is striking.

令人震惊的是，尤其当你离开大城市前往京都或箱根等小城市时，会发现所有人都在步行。他们就是普通日本人，涵盖所有年龄段。七八十岁的老人每天步行一万到一万五千步。这是一种步行文化。这并非我作为西方白人带着浪漫化幻想的错觉。

It is shocking the extent to which, especially if you go outside the big cities and go to places like Kyoto or smaller cities like Hakone or so on, just they're all walking. They're all just the average Japanese and at all ages. You have 70, 80 year olds who are walking 10,000, 15,000 steps a day. It's a walking culture. And it's not just my sort of romanticized illusion as a white Western looking at it.

我对这个现象研究颇深。我去过日本十几次，不仅与学者专家，也和街头普通人、出租车司机等进行过长谈。他们喜欢步行。而且年纪越大，越热衷步行。

Like I've gone pretty deep on this. I've been there again like a dozen times. I've had long conversations with people that are there, not just academics and scholars but just ordinary people on the street, taxi cab drivers and so on. They like walking. And also the older they get, the more they like walking.

那些65到70岁的'年轻人'会步行四英里上班。他们不退休，也不神化退休概念。他们的文化中有类似柏拉图所说的'美好生活'理念，但在日本文化中，美好生活必然与有目标的生活紧密相连。

The younger kids actually are, you know, the ones that are 65 and 70, they'll just go walk four miles to work. They don't retire. They don't fetishize retirement. They have concepts in their culture of, you know, what Plato called, you know, a good life. But in Japanese culture, a good life is inextricable from a life with purpose.

在日本文化中，闲散生活不可能是美好生活。闲散与满足感是互斥的概念。他们没有那种'拼命赚钱到65岁就躺平'的观念——至少在受西方影响前的传统文化中不存在。所以人们会工作到65岁以后，70多岁、80多岁仍在工作。

Know, an idle life cannot in Japanese culture be a good life. Like those are incompatible notions, you know, idleness and fulfillment. And so there's no concept of fetishizing like, I'm just going to work really hard, make a lot of money, at 65, you know, I'm going to hang out on the beat. That's just not a concept really in at least the traditional culture, absent the recent Western influences. So people work past 65, into their 70s, into their 80s.

这个阶段才真正关键，对吧？此时死亡风险开始显著上升。当然还有著名的饮食方式——不仅是鱼素为主的饮食，更在于适量原则。他们不会暴饮暴食，吃到八分饱就停。

That's when it really matters, right? That's when risk of mortality starts go up a lot. And then of course, famously, diet sort of it's not just a pescatarian scoop diet, but it's also the fact that you can almost eat anything if it's in the right portions. Don't gouge themselves on food. They eat until 80% full.

这些都是广为人知的。至少现在美国社会开始讨论这些。长久以来，有些医学共识无人质疑——所有医生都认同体重超标会增加各种疾病风险。但十年前，没人敢公开这么说，因为听起来...

All these things that are famously known. And I think at least we're having a conversation about it now in The United States. For the longest time, you had things that every doctor believed. No one would I have never met a doctor who disagrees that, you know, as you get past a certain point in body weight, your risk of all sorts of things goes up. But ten, fifteen years ago, no one wanted no doctor would have wanted to say that out loud because it sounded

那我们如何在文化层面打破这种局面？医生本应是拥有专业知识、致力于帮助患者的人群——我姐姐就是医生，我知道这是很多人从医的核心动力。但政治文化压制了他们基于明确证据发声，这对患者群体影响巨大。却没人站出来指出：过度美化严重超重等于健康是极其错误的。

like Well, how do we break that culturally? Because I think ultimately, to your point, you know, physicians are viewed as people who have extra knowledge, who are supposed to be helping patients, and obviously they're very focused on that, and Sister's a doctor, you know, like I think it's that, you know, for many people I know it's really core to why they became a physician. Yeah. But at the same time, political culture took over and prevented them from speaking their minds on things that were really clear on evidence. That had a huge impact for the patient population, yet nobody would stand up and say, Actually, it's really bad that we're glorifying the fact that being dramatically overweight is healthy.

我认为这种思潮会反复摇摆。这些问题都深度交织。现在我们终于能抛开身份政治滤镜，更开放地讨论健康生活选择。这不只是超重与否的问题——举个与体重无关的例子...

I think the pendulum swings back and forth. I think all these issues are deeply entwined. I think that we're now, for the first time in a long time, having a more open conversation that is not just reduced through the lens of identity politics around health, life choices. And it's not just obesity versus or it's not just overweight versus not overweight. Let's use something that has nothing to do with weight.

神经退行性疾病。这类疾病有很强遗传因素，确实有人终生不动脑却不得阿尔茨海默症。但...

Neurodegenerative. Now, there's a strong genetic component to neurodegenerative. And there are definitely people who have never used their brain in their entire life and never get Alzheimer's. That's obviously true. But?

没有神经学家会否认终身用脑能延缓神经退行性疾病。现在至少可以公开讨论：如果想降低患病风险，就持续做Sanjay Gupta建议的那些事——左撇子偶尔用右手写字，右撇子偶尔用左手写字。这类小事能建立新神经通路。

No serious neurologist will dispute the fact that a mitigant to neurodegenerative disease is to continue to use your brain over the course of your life. It just feels like now at least you can have a sort of more open conversation around like, if you want to at least mitigate the risk of neurodegenerative disease, continue to do all the things Sanjay Gupta taught me to do. If you're left handed, write with your right hand once in a while. If you're right handed, write with your left hand once in a while. Just silly things like that that will form new neural pathways.

这是一种不同类型的AI应用。你们正在被一类知识工作者所接纳，而人们对其速度感到惊讶。通常保守的行业有安全观察者，你之前描述的一切。你认为在其他领域会发生什么，可能发生什么？或者这对许多收听这个播客的企业家有什么启示吗？

This is a different type of AI application. And you are getting adoption with a type of knowledge worker where people are surprised by the pace. Generally, conservative industry has safe peepers, everything that you described earlier. What do you believe about what would happen, what can happen in other fields? Or are there lessons for lots of entrepreneurs that listen to this podcast?

虽然医学显然非常特定，但人类心理并非如此。所有那些真实的、我们通过超速消费互联网增长曲线在最传统怀疑的知识工作者中看到的采纳现象表明，在任何科技可能触及的行业或子领域，心理上适用的基本游戏规则是相同的。即如果你将人们作为人和消费者来对待，如果你以一种他们从未听过的方式与他们交流，如果你以一种前所未有的方式触动他们，那么至少这会非常新鲜和不同，并会让他们以开放的心态考虑这件事。而极有可能，这会打破通常限制该行业采纳曲线的模式。

While medicine is obviously very specific, the human psychology is not. And everything that was true and that we've seen through the sort of hyperpace consumer internet growth curve adoption by the most traditionally skeptical knowledge workers shows that in any industry or subfield that tech might want to touch, the same basic rules of the game psychologically apply, which is if you address people as people and as consumers and if you speak to them in a way they've never spoken to before and if you sort of hit them different in a way that no one's ever kind of come at them in that way before, That, at minimum, will be very refreshing and different and will lead to them considering the thing with an open mind. And in all likelihood, will break the mold that has typically been the rate limit of the adoption curve of whatever had defined that industry?

我认为长期以来，‘如果你建造它，他们就会来’这个想法在科技社区中被嘲笑。为什么在消费互联网公司或像开放证据这样的案例存在的情况下，还会有如此多的怀疑？

I think for a long time, if you build it, they will come has been just laughed at as an idea amongst much of the tech community. Why do you think there's such skepticism when there are the cases of consumer Internet companies or things like open evidence?

我不认为‘如果你建造它，他们就会来’是真的。我也不会说苹果或史蒂夫·乔布斯的故事是‘如果你建造它，他们就会来’。对我来说，苹果或史蒂夫·乔布斯的故事是，如果你有非凡的权力意志，你将现实视为可塑的，并且你相信，如尼采所说，思想和理性思维是意志投射后的第二顺序，那么你就会成功。但这不是你可以告诉Y Combinator的孩子或MBA学生的童话，对吧？这种紧张关系，许多人已经详细讨论过，但在西方思想史中，理性主义与意志之间存在这种紧张关系，对吧？

I don't think if you build it, they will come is true. Nor would I say that Apple or Steve Jobs is a story that if you build it, they will come. To me, Apple or Steve Jobs is a story that if you have extraordinary will to power and you see reality as malleable and you believe, as Nietzsche says, that ideas and rational thought are second order after projections of the will, then you'll succeed. But that's not a fairy tale that you can tell to Y Combinator kids or to MBAs, right? And there's this tension, and this has been discussed by many people at length, but there's this tension in the history of Western thought between rationalism and will, right?

理性与意志或智力与意志。启蒙运动是这种寒武纪时刻，理性主义、思想和这种信仰的爆发，它确实是一种信仰，因为启蒙运动的讽刺在于，理性至上的观念不是通过理性而是通过信仰达到的。有一种信仰认为理性最终会统治，人类在其第一顺序中是理性的，如笛卡尔的‘我思故我在’。今天许多MBA或Y Combinator孩子相信的东西，都是这种思想的衍生物，比如，‘丹尼尔，当你有了开放证据的想法时，你在哪家咖啡店？是什么样的咖啡店？’

Reason and will or the intellect and will. And the Enlightenment was this sort of Cambrian moment and the explosion of rationalism and ideas and this sort of faith, and it really is a faith, because the irony of the Enlightenment is that the notion that reason is supreme was not arrived at through reason but through faith. And there was this faith that reason would ultimately govern and that humans are in their first order, rational and Cogito, Ergo, Sam, and Descartes. And so much of everything that waterfalls down today to what MBAs or why Combinator Kids believe, which is just like, so tell me, Daniel, when you had the idea for Open Evidence, were you in a coffee shop? What kind of coffee shop?

你喝了什么咖啡？是什么环境因素催生了这个想法？所有这些实际上只是笛卡尔思想的衍生品。我认为对人们来说，比‘在什么咖啡店，他们喝什么时有了他们钦佩的想法’更有用的问题是，‘我能在哪里找到一种几乎是强迫性的动力水平？’这对不同的人来说是不同的。

What coffee were you drinking? What was the circumstantial thing that gave rise to the idea? All of that is actually just a derivative idea of Cartesian thought. And I think a more useful question for people than what coffee shop, what was the person drinking when they had the idea for something they admire, Is where can I find a level of motivation that is almost compulsive? And that's different for different people.

没有一个统一的答案。许多人从证明某人错误中找到这种动力。有人在他们小时候对他们说了什么，那时他们心理上非常脆弱，这些话正好击中他们。他们用余生试图证明那个人是错的，无论那个人是父母、朋友还是老师。有多少著名的例子是人们试图证明一个已经去世的老师是错的？

There's no one answer. There are a lot of people that find that from proving somebody wrong. Somebody said something to them when they're a kid that really just hit them in the right way when they were really psychologically vulnerable. And they've spent the rest of their life trying to prove that person wrong, whether that person is a parent or a friend or a teacher. Mean, how many famous examples are there of people trying to prove a teacher wrong that is literally dead?

我见过这些人。75岁了，还在试图证明一个已经去世三十年的老师是错的。但事实证明，这些东西是有效的，这些成分是有效的。而且不一定是证明某人错误。可能是那些生来就有大量攻击性的人，找到了建设性的方式来引导这种攻击性。

I've met these people. 75 years old and they're trying to prove a teacher wrong that's been dead for thirty years. But it turns out that those things work and those ingredients work. And it doesn't need to be proving someone wrong. It could be people that are born with an enormous amount of aggression and found a constructive way to channel that aggression.

就我而言，我生来就有难以置信的攻击性。通过结合我的智力和运气，我找到了更有用的渠道来引导这种攻击性。但你需要找到这种完美风暴般的东西，它与想法关系不大。你知道，开放证据的想法是世界上最明显的想法。它和‘让我们去月球’一样，没有更多的创造性。

In my case, I was born with just an unbelievable amount of aggression. And through a combination of trading my intellect and just luck, I've found a more useful channel for that aggression. But you need to find this perfect storm of things, and it has very little to do with ideas. You know, the idea for open evidence is the most obvious idea in the world. It's the same as it's no more creative than, let's go to the moon.

让我们做一些真正困难的事情。什么是困难的事情？

Let's do something really hard. What are the hard things?

你会主动为自己寻找更多动力吗？

Do you actively seek to find more motivation for yourself?

不，实际上正相反。我认为当代心理学和精神分析学中源自二十世纪初弗洛伊德等人的崇拜文化有个弊端——它没意识到当你分析和描述某件事物时，你其实扼杀了它。所以我一直抗拒探究创伤，拒绝追溯我动力的根源。

No. Actually the opposite. One of the things I think is unhelpful about the contemporary cult of psychoanalysis in psychology and psychiatry that sort of traces its origins to early twentieth century and Freud and these guys is it doesn't appreciate that in the analysis and description of something, you kill it. So I've actually resisted exploring trauma. I've resisted going back to the origins of my motivation.

我也抗拒回溯自己攻击性的起源。我确实有份从童年和其他经历中形成的半成品地图。但每当感觉自己在接近分析边缘时，我就会抑制这种冲动，因为分析某物在某种程度上就是抹杀它。

I've resisted going back to the origins of my aggression. I have kind of like a partially developed map from childhood and other experiences. But the second I feel myself going close to analyzing it, I resist the urge to analyze it because in the analysis of something is the deletion of it in a way.

而你早已拥有那口井。井水很深，所以你并不需要刻意挖掘。

And you already have the well. And the well is deep, so it doesn't you don't need it.

我不需要更多动力，恰恰相反。我抵制探索推进系统的本质——要知道大多数推进系统都源于创伤。就像红杉资本道格他们那套著名的童年追溯方法论，虽然有其道理，但你不能靠得太近，否则会在分析过程中毁掉这个推进系统。

I don't need more of it, and quite the opposite. I resist trying to discover what the propulsion system is. You know, most propulsion systems originate from trauma. This is what's now become the sort of famous Sequoia methodology of Doug and these guys talking about your early childhood and all this stuff. I think there's a lot of truth to it, except you don't want to go too close to that stuff because you'll actually kill the propulsion system in analyzing it.

你如何将这种动力视角应用到团队招募中？

What of this lens of motivation do you take to recruiting for your own team?

早在第一家公司时我就明白，聪明程度与产出只有中等相关性（约0.65）。你需要找的不仅是绝顶聪明的人，更要如我所说——具备某种推进系统。他们无需知道源头，但我们都见过那些极度进取或拼命三郎式的人。

I quickly learned, in my first company even, that there is only a moderate correlate. There's like a 0.65 correlation between Frequently Smart and output. I think you have to find people that are obviously exceptionally intelligent, But to all the things I've been saying, have some propulsion system. They don't need to know where it comes from. But we've all met people that are extremely aggressive or extremely driven.

这些人可能完全不明白自己为何如此。这反而是好事，是优势。正是这类人成为我的招募目标，因为这样就能避开我最厌恶的管理艺术——要知道大部分管理手段都是在缺乏内生动力时的补救措施。

They might have very little understanding of why they are. That's better, not worse. Better. And those are the people that I try to recruit and that I seek out in recruiting because then all the other stuff that is I actually don't like management. And I don't want to practice the art of management.

我并非MBA出身，从没上过商学院课程。虽然我尊重那些有相关背景的朋友，但那个世界充斥着如何激励员工、给予建设性反馈等知识体系。当然这些确有价值，可我在招募中寻找的正是那些完全不需要这些冗余手段的人——他们自带征途引擎，你能做的只是...

And so much of management needs to come into play in the absence of those things, right? Like a lot of this stuff, I'm not an MBA by background. I've never gone to business school. I've never gone to one business school class. But I have friends that have, and there are people I respect that have done those things.

...顺势而为。

And a lot of that world is like how to motivate people, how to inspire people, how to give people constructive feedback and constructive criticism and all of this stuff. And I think there's definitely a body of knowledge there. You can definitely do better or worse at doing those things. But what I seek out in recruiting are the people for whom all of that is just entirely redundant because they're they're just they're driven on their own warpath, and the best you can do is sort

滚出去

of get out of

他们的路。

their way.

太棒了。谢谢你这么做，丹尼尔。

Awesome. Thanks for doing this, Daniel.

谢谢。乐意效劳。

Thank you. Happy to help.

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