The Waymo effect: how AI is quietly making research less collaborative
The Waymo effect: how AI is quietly making research less collaborative
Waymo 效应：人工智能如何悄无声息地削弱科研协作
The essay The Waymo effect: how AI is quietly making research less collaborative. How frictionless technologies teach us to prefer our own company – and why research leaders should worry. 本文探讨了“Waymo 效应”：人工智能如何悄无声息地削弱科研协作。无摩擦技术如何教会我们更倾向于独处，以及为什么科研领导者应该为此感到担忧。
On a recent trip to San Francisco I did the thing that every visitor to San Francisco now does: I summoned a car with no one in it. The Waymo arrived with the serene confidence of a machine that has never once worried about where to find parking, and I climbed into the back seat, glanced instinctively at the driver’s seat to say hello, and found myself nodding politely at an empty chair. The steering wheel turned itself. 在最近的一次旧金山之行中，我做了现在每位访客都会做的事：我叫了一辆无人驾驶汽车。Waymo 到达时带着一种机器特有的从容自信，它从不担心停车位的问题。我坐进后座，本能地看向驾驶座准备打招呼，却发现自己只能对着一张空椅子礼貌地点头。方向盘自动转动了起来。
I have spent a reasonable portion of my life thinking about counterintuitive aspects of physics, but that did not help me with the mild existential vertigo of watching a steering wheel moving on its own – an unseen driver responsible for my safety. 我一生中花了不少时间思考物理学中反直觉的方面，但这并没有减轻我看着方向盘自动转动时那种轻微的“存在主义眩晕感”——一个看不见的驾驶员正掌控着我的安全。
I was in San Francisco, in part, to spend time with Susan Winslow, CEO of Macmillan Learning. We are colleagues within the Holtzbrinck group, and we had come together for the most human of professional reasons: to collaborate. To sit in the same room, compare notes on how AI is reshaping our respective corners of research and education, and do the kind of thinking that is stubbornly difficult to do over video calls. 我来旧金山的部分原因是为了与麦克米伦教育（Macmillan Learning）的首席执行官苏珊·温斯洛（Susan Winslow）会面。我们同属霍尔茨布林克（Holtzbrinck）集团，我们聚在一起是为了最人性化的职业理由：协作。坐在同一个房间里，交流人工智能如何重塑我们各自的研究和教育领域，并进行那种在视频通话中难以实现的深度思考。
And yet, comparing notes on our Waymo experiences, we discovered we agreed on something else entirely: the rides were wonderful. As two self-confessed introverts, we had each found the driverless car to be a small oasis. No obligation to make conversation. No silent negotiation over the radio. A guilt-free space to be alone with one’s thoughts, finish an email, or take a call en route without the awkwardness about conducting it in front of a stranger. The car was quiet, smooth and entirely undemanding. 然而，在交流各自的 Waymo 体验时，我们发现我们在另一件事上达成了完全的一致：这种乘车体验太棒了。作为两个自认内向的人，我们都觉得无人驾驶汽车是一个小小的绿洲。没有交谈的义务，也不必在收音机频道上进行无声的博弈。这是一个可以毫无负罪感地独处、思考、处理邮件或在途中接听电话的空间，不必担心在陌生人面前通话的尴尬。车内安静、平稳，完全不需要你费心。
It took us slightly longer to name what we had lost. Two people who had crossed continents to talk to each other were quietly delighted by a technology whose central feature is that you don’t have to talk to anyone. 我们花了一点时间才意识到我们失去了什么。两个跨越洲际只为面对面交谈的人，却对一种核心功能是“让你不必与任何人交谈”的技术感到暗自窃喜。
Naming the Waymo effect
命名“Waymo 效应”
Let me attempt a definition: the Waymo effect is what happens when a technology removes the friction of dealing with another human being, and we experience that removal as pure gain – because the costs of the friction were always visible to us, while its benefits were not. 让我试着定义一下：当一项技术消除了与他人打交道的摩擦，而我们将其视为纯粹的收益时，Waymo 效应就产生了——因为摩擦带来的代价总是显而易见的，而其带来的益处却往往被忽视。
This is a familiar move for anyone who has read Tim Wu on “the tyranny of convenience” – his argument that once a frictionless option exists, we take it by default, and quietly surrender whatever the friction was doing for us, since nobody advertised it as valuable in the first place. 对于读过蒂姆·吴（Tim Wu）关于“便利的暴政”一书的人来说，这并不陌生。他的观点是：一旦存在无摩擦的选项，我们就会默认选择它，并悄悄放弃摩擦原本为我们提供的价值，因为起初并没有人宣传过这些摩擦是有价值的。
Albert Borgmann’s related idea of the device paradigm goes a step further: a device delivers a commodity – warmth, information, companionship – while concealing the practice that once had to be undertaken to earn it, so that we stop noticing the practice has gone at all. Only the commodity keeps arriving. 阿尔伯特·博格曼（Albert Borgmann）关于“设备范式”的相关理念更进一步：设备提供商品（如温暖、信息、陪伴），同时隐藏了曾经为了获得这些商品所必须付出的实践过程，以至于我们根本没注意到这些实践已经消失了。我们只看到商品源源不断地送达。
The costs of talking to a taxi driver are obvious: the small effort of politeness, the conversational roulette, the introvert’s tax of sustained small talk at 7am. The benefits are diffuse and deferred: the driver was, for many of us on many days, the last stranger we were obliged to encounter. The last person from outside our bubble – professionally, politically, socially – with whom we had an unchosen conversation. The last reliable source of a view we did not ask for. 与出租车司机交谈的代价是显而易见的：礼貌的小小努力、对话的随机性、以及早上七点被迫进行持续闲聊的“内向者税”。而其益处却是分散且滞后的：对于我们许多人来说，在很多日子里，司机是我们不得不接触的最后一个陌生人。他是我们圈子（职业、政治、社交）之外的最后一个人，我们与他进行了非自愿的交谈。他是我们未曾主动寻求却能提供观点的最后一个可靠来源。
Neither Susan nor I would design a world without those conversations. We simply enjoyed opting out of this one. And that, of course, is how such things are lost: never by decision, always by convenience. One comfortable ride at a time. 苏珊和我都不希望设计一个没有这些交谈的世界。我们只是享受这次“退出”的机会。当然，这就是事物消失的方式：从不是因为某个决定，而是因为便利。一次舒适的旅程，又一次舒适的旅程。
I should be clear that this is not an anti-Waymo article (the rides really were excellent, and I would take one again without hesitation – that is rather the point). It is an article about research. Because the same logic that removed the driver from the car is now, with equal serenity and considerably greater consequence, removing the collaborator from the research process. 我必须说明，这不是一篇反 Waymo 的文章（乘车体验确实很棒，我会毫不犹豫地再次乘坐——这正是问题的关键）。这是一篇关于科研的文章。因为将司机从车中移除的逻辑，现在正以同样的从容和更大的后果，将合作者从科研过程中移除。
The frictionless colleague
无摩擦的同事
Large language models are the Waymo of intellectual life. Consider the comparison honestly, as a researcher experiences it. A collaborator is available occasionally, between teaching commitments, grant deadlines and time zones; an LLM is available at 2am on a Sunday, which – let us not pretend otherwise – is when a worrying amount of research thinking actually happens. 大型语言模型（LLM）就是智力生活中的 Waymo。从研究人员的真实体验出发，诚实地进行比较：合作者偶尔才有空，他们忙于教学任务、经费截止日期和时区差异；而 LLM 在周日凌晨两点随时待命——别假装不知道，这正是大量科研思考真正发生的时刻。
A collaborator arrives with their own agenda, their own framing of the problem, their own inconvenient conviction that your central assumption is wrong; an LLM arrives with no agenda beyond being useful to you. A collaborator must be persuaded; an LLM must merely be prompted. 合作者带着自己的议程、对问题的框架设定，以及那种让你不悦的信念——即你的核心假设是错误的；而 LLM 除了为你提供帮助外，没有任何议程。合作者需要被说服；而 LLM 只需要被提示。
A collaborator will challenge you in ways you did not ask for and had not thought of; an LLM will challenge you precisely as robustly as you request – and not one degree more. If you ask it to critique your argument, it will do so, capably. But it will critique the argument you brought. It will not, unbidden, tell you that you are solving the wrong problem, that a rival group tried this in 2019 and abandoned it, or that your beautiful theoretical framing collapses on contact with the messy realities of someone else’s field. 合作者会以你未曾要求、未曾想到的方式挑战你；而 LLM 只会按照你要求的力度进行挑战——绝不会多出一分。如果你要求它批评你的论点，它会出色地完成。但它只会批评你提出的论点。它不会主动告诉你，你解决的问题方向错了，或者某个竞争团队在 2019 年尝试过并放弃了，又或者你那漂亮的理论框架在接触到其他领域混乱的现实时会瞬间崩塌。
The collaborator’s inconvenience, in other words, is not a bug in the collaboration; it largely is the collaboration. The value of another mind lies exactly in the ways it refuses to be an extension of your own. 换句话说，合作者带来的“不便”并不是协作中的漏洞；它在很大程度上就是协作本身。另一个大脑的价值，恰恰在于它拒绝成为你大脑的延伸。
And beyond challenge and serendipity lies something more fundamental still. Research is not merely a production function that converts ideas into papers. It is a community of practice – a social fabric maintained through argument, apprenticeship, conference-bar conversations, the shared ordeal of a difficult referee report. That fabric is woven from precisely the frictions we are now engineering away. Every conversation redirected from a colleague to a chatbot is a thread quietly withdrawn. No individual thread matters. The fabric does. 除了挑战和偶然发现之外，还有更根本的东西。科研不仅仅是将想法转化为论文的生产函数。它是一个实践社区——一个通过争论、学徒制、会议酒吧里的交谈、共同经历严苛审稿报告的磨难而维持的社会结构。这个结构正是由我们现在正通过工程手段消除的“摩擦”编织而成的。每一次从同事转向聊天机器人的对话，都是一根被悄悄抽走的丝线。单根丝线或许无关紧要，但整个结构至关重要。