论遏制奇怪的人工智能浪潮-凯发ag旗舰厅

大多数人并不要求人工智能能够完成许多以前为人类保留的任务。但它几乎完全出乎意料地在八个月前随 chatgpt 一起出现，并且从那时起就一直在加速发展。most people didn’t ask for an ai that can do many tasks previously reserved for humans. but it arrived, almost completely unexpectedly, eight months ago with chatgpt, and has been accelerating ever since.

老师们不希望看到teachers did not want to see。雇主确实希望. employers did want h。政府官员不希望在没有任何有效对策的情况下发布完美的虚假信息系统。在没有手册的情况下发布，没有人真正知道这些工具的全部功能。世界很快变得更加陌生。. government officials did not want a perfect disinformation system released without any useful countermeasures. released without a manual, no one really even knows what these tools are fully capable of. the world got much stranger, very quickly.

因此，这么多人试图阻止人工智能变得怪异也就不足为奇了。无论我走到哪里，我都能看到旨在消除人工智能带来的破坏和怪异现象的政策。这些政策不会发挥作用。更糟糕的是，如果试图假装人工智能就像以前的技术浪潮一样，它的实质性好处将大大减少。so, it is not surprising that so many people are trying to stop ai from being weird. everywhere i look i see policies put in place to eliminate the disruption and weirdness that ai brings. these policies are not going to work. and, even worse, the substantial benefits of ai are going to be greatly reduced by trying to pretend it is just like previous waves of technology.

首先，让我们放弃这样一个想法：生成式人工智能是我们在过去十年左右的时间里一直经历的 web3/加密/nft/vr/metaverse 技术炒作浪潮的下一个迭代。这些技术中的每一项都与未来产生重大影响的潜力有关，要实现这一目标需要大量投资和运气so first, let’s dispense with the idea that generative ai is the next iteration of the waves of web3/crypto/nft/vr/metaverse technology hype that we have all lived with for the last decade or so. every one of these technologies was about future potential to have a major impact, and getting there would have required massive investment and good luck

而且，对于许多人来说，这是一个问题。在与教育机构和公司的对话中，我看到领导者拼命地试图确保人工智能不会改变任何事情。我认为这不仅是徒劳的，而且还存在风险。那么我们来谈谈吧。and, for many people, that is a problem. in conversations with educational institutions and companies, i have seen leaders try desperately to ensure that ai doesn’t change anything. i believe that not only is this futile, but it also poses its own risks. so lets talk about it.

许多组织领导者还不了解人工智能，但那些看到机会的人渴望拥抱它……只要它不会让任何事情变得太奇怪。我认为人工智能的采用分为三个阶段，但都有各自的缺陷。many organizational leaders don’t yet understand ai, but those who do see an opportunity are eager to embrace it… as long as it doesn’t make anything too weird. i see three stages to ai adoption, but all have their own flaws.

忽略它。ignore it.忽视人工智能并不会让它消失。相反，个别员工会找到利用人工智能来改善自己工作的方法。他们不会告诉组织的领导他们在做什么，因为他们担心受到惩罚，或者其他人会降低他们的工作价值。这些是 ignoring ai doesn’t make it go away. instead, individual employees will find ways to use ai to enhance their own jobs. they won’t tell the organization’s leaders about what they are doing, because they worry about being punished, or that others will value their work less. these are the 我之前写过的 i have written about before.

禁止它。ban it. 这通常是对善意但有时在技术上不正确的法律意见的回应this is usually in response to well-intentioned, but sometimes technically incorrect, legal opinions

将其集中化。centralize it.我越来越多地看到大公司构建自己的内部 chatgpt，通常使用 openai 的 api，但将其包装在自己的软件中以确保“安全”和可控。在此过程中，他们还决定如何最好地使用人工智能，根据很少的经验和知识，针对自上而下决定的用例优化其定制软件。 increasingly, i see large companies building their own internal chatgpts, usually using openai’s apis, but wrapping it in their own software to be “safe” and controllable. in doing so, they also make decisions about how ai is best used, optimizing their customized software for a use case that is decided from the top-down, based on little experience and knowledge.

集中化是组织在面对新技术时习惯做的事情。集中的电子邮件、视频会议软件、即时消息、浏览器——这样公司就可以监控不当使用、保护数据安全，最重要的是为所有员工制定政策。在之前的每一波技术浪潮中，集中控制是软件安装和集成成本数百万美元的自然结果，这使得采用它是一个漫长而昂贵的过程。centralization is what organizations are used to doing when faced with a new technology. centralized email, video conference software, instant messaging, browsers - that way the company can monitor for inappropriate use, secure their data, and, most importantly set policies for all their workers. in every previous wave of technology, centralized control is a natural consequence of software can costs millions to install and integrate, making it adopting it a long and expensive process.

问题在于，目前实施的人工智能并不是真正为中心化而构建的，原因有以下三个：the problem is that ai, as currently implemented, is not really built for centralization, for three reasons:

1. 没有企业优势。gpt-4 是最先进的人工智能，可通过 bing 免费向 169 个国家/地区的所有人免费提供，或者通过 openai 收取少量费用。公司无法获得更好的东西。事实上，公司使用的 api 通常落后于公众广泛使用的 ai（你无法通过 api 或多模式输入获得代码解释器，但可以通过 chatgpt 和 bing 获得它们）。一些公司对此的回应是：“好吧，我们有大量专有数据可供人工智能使用。” 也许私人数据对于微调很有用，并带来巨大的优势。但也许不是，而且它通常还没有帮助（微调仍在开发中，大内存也是如此）。there is no corporate advantage. gpt-4, the most advanced ai available, is free for everyone in 169 countries through bing, or for a small charge from openai. corporations have no access to anything better. in fact, the apis that companies use often lag the ais available widely to the public (you can’t get code interpreter through an api, or multimodal input, but you can get them through chatgpt and bing). some companies respond to this with “well, we have tons of proprietary data for the ai to use.” and maybe private data will be useful for fine-tuning and add a huge advantage. but maybe not, and it isn’t usually helping yet (fine-tuning is still in development, as are large memories).

2. 你不知道它有什么好处。没有理由相信任何组织的企业领导层都会成为理解人工智能如何帮助特定员工完成特定任务的奇才。事实上，他们可能不太擅长找出人工智能的最佳用例。个体工作者能够敏锐地意识到自己的问题，并且能够尝试多种解决问题的替代方法，因此更有可能找到人工智能等通用技术的用途。you have no idea what it is good for. there is no reason to believe that the corporate leadership of any organization are going to be wizards at understanding how ai might help a particular employee with a particular task. in fact, they are likely pretty bad at figuring out the best use cases for ai. individual workers, who are keenly aware of their problems and can experiment a lot with alternate ways of solving them, are far more likely to find uses for a general technology like ai.

3. 你们公司的人工智能实施是可怕且有限的。员工知道官方的企业人工智能界面正在受到监控，如果他们以某种不明确的错误方式使用它，他们可能会受到惩罚。他们通常也知道这比他们在手机上访问的内容更糟糕。您不太可能看到最有趣和最强大的用例通过您的公司系统。your company ai implementation is terrifying and limited. employees know that the official corporate ai interface is being monitored, and that they may be penalized if they use it in some ill-defined wrong way. they also often know it is worse than what they can access on their phone. it is very unlikely that you are going to see that most interesting and powerful use cases go through your corporate system.

通过试图让人工智能像所有其他技术一样，公司忽视了它的变革性。一个人可以做大量的工作（by trying to make ai like all other technologies, companies are ignoring how transformative it is. one person can do a tremendous amount of work (），但它也是不同的工作：繁琐的任务被外包，有趣的任务被成倍增加。人工智能工作的性质发生了变化，令人不舒服、有风险，但潜在的威力却很大。), but it is also different work: tedious tasks are outsourced, interesting tasks are multiplied. the nature of work with ai shifts in way that uncomfortable, risky, and potentially powerful.

此外，我们的工作系统不是为人工智能而构建的，所以我们需要重建它们。目前，人工智能最先进的应用是由个人完成的。一个例子是 dinosaurs are better 的 jussi kemppainen，他正在独自开发一款完整的冒险游戏。in addition, our work systems are not built for ai, so we will need to rebuild them. right now, the most advanced uses of ai are being done by individuals. one example is jussi kemppainen of dinosaurs are better, who is developing an entire adventure game, alone.

如果不以某种方式民主化对人工智能的控制，公司就无法利用这种力量和创造力。只有由工人驱动的创新才能真正从根本上改变工作，因为只有工人才能在自己的任务上进行足够的实验，以学习如何以变革性的方式使用人工智能。仅靠自上而下的凯发ag旗舰厅的解决方案是不可能为员工赋权的。相反，请考虑：there is no way for companies to harness this kind of power and creativity without, in some way, democratizing control over ai. only innovation driven by workers can actually radically transform work, because only workers can experiment enough on their own tasks to learn how to use ai in transformative ways. and empowering workers is not going to be possible with a top-down solution alone. instead, consider:

• 确保员工愿意分享他们所学到的知识的激进激励措施。如果他们担心受到惩罚，他们就不会分享。如果他们担心得不到奖励，他们就不会分享。如果他们担心自己开发的人工智能工具可能会取代他们或他们的同事，他们就不会分享。企业领导者需要找到一种方法来安抚和奖励员工，这是他们不习惯做的。radical incentives to ensure that workers are willing to share what they learn. if they are worried about being punished, they won’t share. if they are worried they won’t be rewarded, they won’t share. if they are worried that the ai tools that they develop might replace them, or their coworkers, they won’t share. corporate leaders need to figure out a way to reassure and reward workers, something they are not used to doing.

• 增强用户对用户的创新。构建提示库，帮助工作人员开发提示并与组织内的其他人共享提示。向员工广泛开放工具以供使用（同时仍围绕专有信息制定政策），看看他们能想出什么。为员工创造闲暇时间来开发和讨论人工智能方法。empowering user-to-user innovation. build prompt libraries that help workers develop and share prompts with other people inside the organization. open up tools broadly to workers to use (while still setting policies around proprietary information), and see what they come up with. create slack time for workers to develop, and discuss, ai approaches.

• 不要依赖外部提供商或您现有的研发团队来告诉您答案。我们正处于新技术的早期阶段。没有人真正了解使用人工智能的最佳方法，他们当然也不知道在公司中使用人工智能的最佳方法。只有负责任地深入研究，您才有希望找出最佳用例。don’t rely on outside providers or your existing r&d groups to tell you the answer. we are in the very early days of a new technology. nobody really knows anything about the best ways to use ai, and they certainly don’t know the best ways to use it in your company. only by diving in, responsibly, can you hope to figure out the best use cases.

几乎每个级别的每项任务都可以（至少部分）由人工智能完成。无论你根据你最近一个学期的所见所闻对人工智能工作的质量有什么偏见，但现在它们可能是错误的。人工智能可以完成高质量的工作。它可以做数学。它犯的明显错误要少得多。它能够处理大量数据。almost every assignment, at every level, can be done, at least in part, by ai. whatever prejudices you have about the quality of ai work as a teacher based on what you saw least semester, they are probably now wrong. ai can do high-quality work. it can do math. it makes far fewer obvious mistakes. and it is capable of working with vast amounts of data.

作为演示，我将上一本书的全部内容粘贴到 claude 2 中，并给出了以下说明，没有任何附加信息：as a demonstration, i pasted in my entire last book into claude 2 and gave the following instructions, without any additional information:

我必须为此做三件事：i have to do three things with this:

1. 写一篇关于这本书的简短读书报告write a short book report on the book

2. 写一篇文章解释这本书的一些优点和缺点write an essay explaining some plusses and minuses of the book

3. 写下如何将这本书应用到我自己的创业想法中，让我可以轻松订购口香糖送货上门write about how to apply the book to my own idea of a startup that makes it easy to order gum delivered to my house

做这一切do all that

确实如此。我几乎找不到任何问题或幻觉，而且这些材料通常显示出几个月前人工智能还无法模拟的高阶思维。and it did. there were few issues or hallucinations i could find, and the materials generally showed the higher order thinking that ai was not capable of simulating just a few months ago.

面对这一挑战，许多老师希望时光倒流：蓝皮书考试。手写论文。口语考试。作为临时凯发ag旗舰厅的解决方案，这些想法并不是坏主意，但它们只是我们决定教育下一步发展时的权宜之计。在人工智能出现之前，我们没有采用大多数这些方法是有原因的。given this challenge, many teachers want to turn back the clock: blue book exams. handwritten essays. oral exams. these aren’t bad ideas as temporary fixes, but they are only stopgap measure while we decide what comes next in education. there is a reason we did not do most of these approaches before ai came along.

但人工智能对教育远非负面影响。我们非常接近大规模辅导的长期梦想，but ai is far from a negative in education. we are very close to the long-term dream of tutoring at scale, and 有望让教师的生活变得更轻松，同时改善学生和家长的成果。接下来，我们需要阐明彻底改变教育的愿景。我们需要思考如何将人工智能融入到 promise to make the lives of teachers easier, while improving outcomes for students and parents. next, we need to articulate a vision for what radically changed education could look like. we need to think about how to incorporate ai into 以及, and 。这里有巨大的机会使教育机会民主化并惠及所有能力水平的学生，但我们不能只是继续做我们一直在做的事情，并希望事情不会改变。. there is tremendous opportunity here to democratize access to education and reach out to all students, of all ability levels, but we can’t just keep doing what we always did and hope things won’t change.

对人工智能做出反应的唯一糟糕的方式就是假装它不会改变任何事情。the only bad way to react to ai is to pretend it doesn’t change anything.

关于如何在工作、学校和社会中使用人工智能，我们有相当多的机构，但我们需要首先假设我们在许多领域都面临着真正的、广泛的颠覆。设计人工智能的科学家和工程师尽管能力很强，但对于如何最好地使用人工智能，甚至应该如何以及何时使用人工智能，并没有特别的专业知识。我们必须做出这些决定。但我们必须认识到人工智能浪潮正在兴起，现在是决定这意味着什么的时候了。we have considerable agency about how to use ai in our work, schools, and societies, but we need to start with the presumption that we are facing genuine, and widespread, disruption across many fields. the scientists and engineers designing ai, as capable as they are, have no particular expertise on how ai can best be used, or even how and when it should be used. we get to make those decisions. but we have to recognize that the ai tide is rising, and that the time to decide what that means is now.