I've always been jealous of Winston Churchill. There's a quote, by the way. The history of innovation is the bed, the bus and the bathtub. It's always these moments when we're not really thinking about work or we're kind of doing something else that good ideas come to us.

我一直很羡慕温斯顿·丘吉尔。顺便提一句，有这样一句名言：创新的历史诞生于床笫、公交和浴缸。总是在我们没有真正思考工作，或者正在做别的事情的时候，好点子才会不期而至。

Winston Churchill, He's sitting in the bathtub, and he's dictating a national address to his assistant who's in the other room. She's saying, "distinguished ladies and gentlemen" "Don't call them distinguished" "They're not" This is the Gary Oldman version. "They're not distinguished." You know, "Dear ladies and gentlemen, we have gathered together." "Get to the point!"

温斯顿·丘吉尔坐在浴缸里，向隔壁房间的助手口述一篇国家演讲稿。助手念着：“尊敬的女士们先生们……” 丘吉尔打断：“别用‘尊敬的’这个词，他们不值得。” 这是加里·奥德曼扮演的版本。“他们不值得尊敬。” 助手又念：“亲爱的女士们先生们，我们今天齐聚于此……” 丘吉尔再次打断：“直接说重点！”

and I'm watching this going I would give anything to have an assistant who understood my context and my voice and my intent well enough that I could sit in the bath and they could write my speech. Now, the poorest villager in Palo Alto can have what only Winston Churchill used to have, which is an assistant that has my context and my voice and my intent available to me so that when I'm in the bathtub, I can be dictating my address. That is absolutely technically possible today.

我看着这一幕时心想，我愿意付出任何代价，来换取一位能够充分理解我的背景、我的语气和我意图的助手，这样我就可以坐在浴缸里，由他们来撰写我的演讲稿。而现在，即使是帕洛阿尔托（Palo Alto：美国加州城市，硅谷核心）最贫穷的村民，也能拥有温斯顿·丘吉尔曾经独享的待遇——一个掌握我的背景、语气和意图的助手，让我在浴缸里也能口述我的演讲。这在今天的技术上是完全可以实现的。

I'm Jeremy Utley, I'm an adjunct professor of creativity and AI at Stanford University. I've been teaching at Stanford for the last 15 years at the intersection of creativity, innovation, entrepreneurship, and now increasingly, artificial intelligence. The topic that I'm most focused on right now is helping non-technical professionals learn to be good collaborators to or with generative AI.

我是杰里米·乌特利，斯坦福大学创造力与人工智能方向的副教授。 [2] 过去 15 年来，我一直在斯坦福大学教授创造力、创新、创业精神的交叉学科，而现在则越来越多地涉及人工智能。目前我最关注的课题是帮助非技术背景的专业人士学习如何与生成式 AI（Generative AI：能够生成文本、图片等新内容的人工智能）进行高效协作。

And then two years ago, myself and my partner at the time, Perry Klebahn, wrote a book called Idea Flow, which was the canonical book on idea generation and prototyping. So super proud of that. It was the culmination of a dozen years of leading executive programs and the leadership program and the entrepreneurship program at Stanford. And one month after our book came out, ChatGPT came out.

两年前，我和当时的合作伙伴佩里·克莱班（Perry Klebahn）合著了一本名为《创意流》（Idea Flow）的书，这本书是关于创意生成和原型制作的权威之作。我为此感到非常自豪。它是我们十多年来在斯坦福领导高管项目、领导力项目和创业项目的结晶。然而，就在我们的书出版一个月后，ChatGPT 问世了。

To me, the fact that I wrote the canonical book on Idea generation just prior to AI is like writing the best book on retail just before the internet. AI is a tool to dramatically augment and amplify our creativity. And the truth is, I didn't know a lot about it when the book came out. So one month after my book came out, instead of going on a world book tour, I strapped myself back into the front row as a student and said, I need to be learning about this transformative new technology.

对我而言，在 AI 时代到来前夕写出了一本关于创意生成的权威书籍，就好比在互联网出现之前写出了一本关于零售业的最佳著作。AI 是一个能够极大地增强和放大我们创造力的工具。但事实是，当我的书出版时，我对 AI 还知之甚少。因此，在新书发布一个月后，我没有进行全球巡回宣传，而是重新回到学生的位置，告诉自己：我必须学习这项变革性的新技术。

So I started taking classes. I started conducting research. I started working with and studying teams inside of organizations, using the tool to understand the simple question, how does generative AI impact the individual and the team and the organization's ability to solve problems?

于是我开始上课，开始进行研究。我开始与企业内部的团队合作并研究他们，利用这个工具来理解一个简单的问题：生成式 AI 如何影响个人、团队乃至整个组织解决问题的能力？

第一章：不要问 AI，让它来问你

You can give an AI a prompt, for example. How should I answer this question? Or you could give an AI the question I want to ask how I should answer this question. What's the best way of framing that question to an AI? So you see what I did there? I asked AI for how to ask I my question, but you can use AI to use AI, which is you couldn't use Excel to use Excel. PowerPoint can't teach you how to use PowerPoint. Email can't teach you how to use email. AI strangely can teach you how to use itself if you think to ask.

例如，你可以给 AI 一个指令：“我该如何回答这个问题？” 或者，你可以换一种方式提问 AI：“我想知道，我应该如何向 AI 提问才能最好地回答这个问题？” 你看到我在这里做什么了吗？我让 AI 教我如何向 AI 提问。你可以利用 AI 来学习如何使用 AI，这是其他工具所不具备的。Excel 无法教你如何使用 Excel，PowerPoint 也无法教你如何使用 PowerPoint，邮件同样如此。但奇怪的是，只要你想到去问，AI 就能教会你如何使用它自己。

Go to your language model of choice and just say the following. Hey, you're an AI expert. I would love your help and a consultation with you to help me figure out where I can best leverage AI in my life. As an AI expert, would you please ask me questions one question at a time, until you have enough context about my workflows and responsibilities and KPIs and and objectives that you could make two obvious recommendations and two non-obvious recommendations for how AI could leverage AI in my work.

你可以打开你喜欢的语言模型，然后对它说：“你好，你是一位 AI 专家。我希望能得到你的帮助和咨询，帮我找出在我的生活中哪些地方可以最好地利用 AI。作为一名 AI 专家，请你一次只问我一个问题，直到你对我工作流程、职责、KPI（关键绩效指标）和目标有了足够了解，然后请为我提出两个显而易见和两个不那么显而易见的建议，告诉我如何在工作中使用 AI。”

you will have one of the most enlightening and illuminating conversations you've ever had, and it's all because of AI's ability to evaluate its own work. What I've seen is non-technical employees are able to do incredible things. Here's one example.

你会发现，这将是你经历过的最具启发性和启示性的对话之一，而这一切都源于 AI 评估自身工作的能力。我看到，许多非技术背景的员工正在利用 AI 完成一些不可思议的事情。这里有一个例子。

The National Park Service called me and asked me if I would conduct a training program for a bunch of backcountry rangers, so they gathered a group of about 60 backcountry rangers and facilities managers into a training session, and I spent a couple of hours over zoom teaching folks the basics of collaborating with AI. One of the people in that session was a gentleman named Adam Rymer, who works at Glen Canyon National Park.

美国国家公园管理局联系我，邀请我为一群偏远地区的护林员举办一个培训项目。他们召集了大约 60 名护林员和设施经理参加了一场线上培训会。我花了两三个小时通过 Zoom 向他们传授了与 AI 协作的基础知识。其中一位参与者是亚当·莱默（Adam Rymer），他在格伦峡谷国家公园工作。

And one of the things I say is you should focus on parts of your work that you dread. Parts of your work that you don't enjoy. "Ah, I have to do this again." And Adam said, if I have to replace the carpet tiles in the lodge. I have to fill out all this paperwork. And so to replace a carpet tile will sometimes take 2 or 3 days of paperwork. Then he thought, could AI help me write that paperwork? And in 45 minutes, he built a tool with natural language that saves him two days of work.

我当时提的一个建议是，你应该关注工作中那些你害怕、不喜欢做的部分，就是那种让你感叹“唉，又要做这个了”的任务。亚当就说，他每次要更换旅馆里的地毯砖时，都必须填写大量的文书工作，有时候光是为了换一块地毯砖，就要花上两三天的时间处理文件。然后他想，AI 能不能帮我写这些文件呢？结果，他用自然语言在 45 分钟内就构建了一个工具，为他节省了两天的工作量。

Every day he makes a statement of work and then listen to this. Someone got access to that tool and shared it across the other parks. There's about 430 parks in the service. The National Park Service is estimating that the tool that Adam built in 45 minutes is going to save the service 7000 days of human labor this year.

他每天都会用这个工具生成一份工作说明。接下来发生的事情更令人惊讶：有人获取了这个工具，并将其分享给了其他公园。国家公园管理局系统内大约有 430 个公园。据估计，亚当用 45 分钟开发的这个工具，今年将为整个国家公园系统节省 7000 个人力工作日。

That's the kind of impact that normal professionals can have, even without any technical ability, if only they're given very basic foundational training.

这就是普通专业人士，即使没有任何技术能力，只要接受了非常基础的培训，也能产生的巨大影响。

第二章：不要使用 AI，把它当作队友

People are wanting to learn AI and how it can be transformative for their business, but they don't have the basic language. And so while lots of organizations are asking me how can we work with AI to transform our business? Where I have to start with them is how do you work with AI?

人们渴望学习 AI，了解它如何为业务带来变革，但他们缺乏基础的“语言”。因此，尽管许多组织都在问我“我们如何与 AI 合作来变革业务？”，我却必须从一个更根本的问题开始：“你如何与 AI 一起工作？”

The research I'm familiar with suggests that while on the one hand, AI makes people 25% faster and 12% more work and 40% better quality, it's also true that less than 10% of working professionals are deriving meaningful productivity gains from collaboration with AI. To me, there's this enormous gap. I call it the realization gap.

我熟悉的研究表明，一方面，AI 能让人们的工作速度提高 25%，完成量增加 12%，质量提升 40%；但另一方面，只有不到 10%的职场人士能从与 AI 的协作中获得有意义的生产力提升。 [8] 在我看来，这其中存在一个巨大的鸿沟，我称之为“认知实现差距”。

We conducted studies both in Europe and in the United States. And what we found is, surprisingly, AI didn't help most people be more creative. In fact, in many cases, the people that we studied, AI made them less creative. And as we started digging into the research, we were surprised and looked at the data. We were confused because you think AI should make people more creative, not less.

我们在欧洲和美国都进行了研究，结果令人惊讶地发现，AI 并没有帮助大多数人变得更有创造力。 [8] 事实上，在许多案例中，AI 反而使我们研究的对象的创造力下降了。当我们深入研究数据时，我们感到既惊讶又困惑，因为直觉上认为 AI 应该能提升而非削弱创造力。

And we studied the underperformers and then we studied the Outperformers. And what we found is the Outperformers had a fundamentally different orientation towards AI than the underperformers did, whereas the underperformers treated AI like a tool. The outperformers treated AI like a teammate, and shifting your orientation from tool to teammate changes everything about the kinds of outcomes that you can achieve working with generative AI.

于是我们分别研究了表现不佳者和表现优异者。我们发现，表现优异者对 AI 的态度与表现不佳者有着根本的不同：表现不佳者将 AI 视为工具，而表现优异者则将 AI 视为队友。将你对 AI 的定位从“工具”转变为“队友”，会彻底改变你与生成式 AI 协作所能达成的结果。

A simple example is what do you do when it gives you mediocre results? If it's a tool, you get a mediocre result and then maybe you improve it. Or maybe you say, it's no good at doing that. If it's a teammate who's giving you a mediocre result, think about the last teammate who gave you work product that wasn't sufficient. You gave them feedback. You gave them coaching, you gave them mentorship, you helped them improve it.

一个简单的例子是：当 AI 给出平庸的结果时，你会怎么做？如果把它当成工具，你可能会自己动手修改，或者干脆认为“它做不好这个”。但如果是一个队友交出了不尽人意的工作成果，你会怎么做？你会给他反馈、指导、 mentorship（导师指导），帮助他改进。

And so what we found is that people who treat AI like a teammate, coach it and give it feedback and importantly, get it to ask them questions. The fundamental orientation a lot of people take towards AI is I'm the question asker. AI is the answer giver. But if you think about AI like a teammate, you say, hey, what are ten questions I should ask about this? Or what do you need to know from me in order to get the best response?

我们发现，那些将 AI 视为队友的人会去指导它、给予反馈，更重要的是，会引导 AI 向他们提问。许多人对 AI 的基本定位是“我是提问者，AI 是回答者”。但如果你把 AI 看作队友，你就会说：“嘿，关于这件事，我应该问哪十个问题？”或者“你需要从我这里了解什么，才能给出最好的回答？”

Did you know you could leverage a large language model to roleplay that conversation? You can get an AI to interview you about your conversation partner, and then construct a psychological profile of your conversation partner, and then play the role of your conversation partner in a roleplay, and then give you feedback from the perspective of your conversation partner on how you approach the conversation. That's something you can do today, and there are many things like that. I call them drills, but there are many things like that where if someone will just shift their consideration set of what are the things I can do with AI. They end up discovering applications that I've never even dreamed of.

你知道吗，你可以利用大语言模型来角色扮演那场对话吗？你可以让 AI 就你的谈话对象对你进行访谈，然后为对方构建一个心理档案，接着在角色扮演中扮演你的谈话对象，并从对方的角度就你的沟通方式给你反馈。这是你今天就可以做到的事情。还有很多类似的应用，我称之为“练习”，只要人们愿意改变他们对“我能用 AI 做什么”的思维定势，他们最终会发现一些我从未想象过的应用。

I've been doing this stuff for two years, and my students are regularly coming to me with use cases I've never imagined that landed them in a destination I could have never predicted, and they could never have predicted.

我研究这些已经两年了，我的学生们仍然会经常带给我一些我从未想象过的用例，这些用例将他们带到了我和他们自己都无法预见的新高度。

For me, I never thought about myself as a creative individual. Now, I fully and fundamentally believe every single human being has innate creative capacity. Every single one of us. What the D.school has helped me do is unlock others.

我以前从未认为自己是一个有创造力的人。但现在，我从根本上坚信，每一个人都拥有与生俱来的创造潜能，我们每一个人都有。斯坦福的 D.school（哈索·普拉特纳设计学院：斯坦福大学著名的设计思维与创新学院）帮助我做的，就是去释放他人的这种潜能。 [3]

Once I was teaching a class with a hip hop artist named Lecrae. He's a multi-time Grammy Award winning artist, and he and I are teaching a class to graduate students at Stanford, and we're giving them the assignment. You've got to go get inspiration in the world. And what I can see is it's like looking at myself in the mirror ten years ago, because all of the business school students in the class are going, "inspiration?"

有一次，我和一位名叫 Lecrae 的嘻哈艺术家共同授课。他是一位多次获得格莱美奖的艺术家，我们一起给斯坦福的研究生上课，并给他们布置了一个作业：去外面的世界寻找灵感。我看到班上所有商学院学生的反应都是一脸茫然地问：“灵感？”，这简直就像看到了十年前的自己。

And I just felt Lecrae is clearly the The creative legend in the room. I said, Lecrae, what do you think about inspiration? And of course, as only a hip hop artist could do, he dropped a bar. He said, inspiration is a discipline.

我感觉 Lecrae 显然是房间里最具创造力的传奇人物。我问他：“Lecrae，你怎么看待灵感？” 当然，他用一种只有嘻哈艺术家才会有的方式，说出了一句金句。他说：“灵感是一种纪律。”

And I realized in that moment, for these students, it's not even on their radar as a tool, let alone a routine part of their life. But the most wildly creative individuals I know are disciplined about cultivating the inputs to their thinking, because they know it affects the outputs of their thinking.

那一刻我意识到，对这些学生来说，灵感甚至还没有被他们视为一种工具，更不用说成为他们生活中的例行公事了。但我所认识的最具创造力的人，都非常有纪律地培养自己思想的“输入”，因为他们知道这会影响他们思想的“输出”。

And so, even in regards to AI, I push people. What is the inspiration you're bringing to the model? Everybody has the same access to the same ChatGPT. How do I get a different output than you do? It's because of what I bring to the model. And what do I bring to the model? Certainly I bring technique, but I also bring my experience. I bring my perspective. I bring all the inspiration I've gleaned from the world. That's what gets a user a differential output from a model.

所以，即便是在 AI 这个话题上，我也会督促人们去思考：你给模型带来了什么样的灵感？每个人都能访问同一个 ChatGPT，为什么我能得到和你不同的输出？这是因为我带给模型的东西不同。我带来了什么？当然有技术，但更重要的是我的经验、我的视角，以及我从世界各地收集来的所有灵感。这才是让一个用户从模型中获得差异化输出的关键。

第三章：如何超越“足够好”的创意

A seventh grader in Ohio who I don't even know what her name is, but her teacher asked, what is creativity? And she put a post-it note up on the board that says, Creativity is doing more than the first thing you think of.

俄亥俄州有一位七年级的学生，我甚至不知道她的名字，但她的老师问她“什么是创造力？” 她在白板上贴了一张便利贴，上面写着：“创造力就是做得比你最先想到的更多。”

And that's my favorite definition, because it speaks to a profound cognitive bias that we hold. It's been called functional fixedness. It's been called the Einstellung effect. But the basic premise is humans tend to fixate on an early solution and be satisfied. Herbert Simon called it satisficing, but it's the idea that if we get to good enough, it's enough.

这是我最喜欢的定义，因为它揭示了我们内心深处的一种认知偏见。这种偏见被称为“功能固着”（functional fixedness：指人们倾向于以常规方式使用物体）或“定势效应”（Einstellung effect：指思维定势阻碍找到更优解）。其基本前提是，人类倾向于固守早期的解决方案并感到满足。赫伯特·西蒙（Herbert Simon）称之为“满意即可”（satisficing），即一旦达到“足够好”的程度，我们就不再追求更好。 [8]

And that's why I love that seventh graders definition. Creativity is doing more than the first thing you think of. It's pushing past. Good enough. Is the definition of creativity changing in the age of AI? I don't think so. The reality is, with AI, it's now easier than ever to get good enough.

这就是我为什么喜欢那位七年级学生的定义。创造力是做得比你最先想到的更多，是超越“足够好”。那么，在 AI 时代，创造力的定义是否正在改变？我不这么认为。现实是，有了 AI，达到“足够好”比以往任何时候都更容易了。

If your goal is world class, if your goal is exceptional, then what you want to be prompting for is actually volume and variation, and that takes time. It takes time to not only read through it, but to sort it and to process it. But fundamentally, the definition of creativity doesn't change in the age of AI.

如果你的目标是世界级水平，是卓越，那么你应该向 AI 索要的是数量和多样性，而这需要时间。你不仅需要时间去阅读所有结果，还需要时间去筛选和处理。但从根本上说，创造力的定义在 AI 时代并未改变。

It's just that the human's ability or inability to arrive at a creative state is affected not only by the technology, but also by their stated or unstated objectives in collaborating with it. Creators don't need to be afraid of AI. Creators need to dive in. They need to lean in. Creators are about to be unleashed in a way they've never been unleashed before.

只是，人类能否达到创造性状态，不仅受技术影响，也受他们与 AI 协作时明确或隐含的目标所影响。创作者们不必害怕 AI，创作者们需要深入其中，拥抱它。创作者即将以前所未有的方式被释放。

The only correct answer to the question how do you use AI? Is I don't. I don't use AI. I work with it. When you start working with AI, it will change everything.

对于“你如何使用 AI？”这个问题，唯一正确的答案是：“我不使用 AI，我与它共事。” 当你开始与 AI 共事时，一切都将改变。