Lingxi Li：智能体不替代人，而是解放人

增强人类智能 当我开始做软件时，我并没有梦想着建一座工厂。 我喜爱的是，屏幕上的某个东西可以成为我思维的延伸。一个在我还没理解某个想法之前，就能把它放进去的地方。一个可以来回摆弄事物、直到新的联系浮现出来的地方。一个可以搭建小系统、让它们按我的方式运作的地方，哪怕这对别人来说毫无意义。 计算机之所以有趣，并不是因为它能在我缺席的情况下干活。它之所以有趣，是因为我能用它做些什么。 早期计算的发展脉络正是围绕这种可能性建立起来的。1962年，Engelbart 将“增强人类智能”描述为帮助一个人理解复杂情境、找到此前遥不可及的解决方案。他的出发点是具体的人，而不是自主的机器。 他描述的不是一个更快的黑箱。他关注的是人、人的工具、人的语言、人的方法，以及人能够学会用它们做什么，这整个关系。能力属于这整个系统。 在某个节点上，我们开始为一个强大得多的技术，讲述一个渺小得多的故事。 更多的自动化。更多的智能体。更多的软件生产更多的软件。更少的人产出更多的成果。更多的增长。更多的数字来证明某事正在发生。 而更少的关注，给这一切本该服务的那个人。 我不想假装计算有一个纯粹无辜的开端。取代人类劳动曾是它的野心之一。即便在1960年，Licklider 也把“人机共生”与那种让剩下的人主要服务于机器的系统区分开来。他希望计算机参与思想的形成，而不只是执行已经定义好的问题。 这种区分似乎很重要——系统是帮你发现你真正想表达什么？还是它只想让你提交一个请求，然后在外面等着它干活？ 有时候，等待恰恰是我想要的。请帮我做搜索。移动文件。把重复性的工作拿走。 但并非所有困难都是负担。 有时候，来回摆弄这些碎片，正是你理解它们的方式。有时候，动手做出来会改变你原本想做的东西。有时候，你需要看到错误的版本，触摸它，拆解它，然后发现一个更好的问题。 我想要的是能为这种关系留出空间的工具。 在1981年关于 Smalltalk 的论文中，Ingalls 描述了一个旨在支持每个人创造精神的系统。个人精通很重要：一个人应当能够理解这个系统，而不是永远依赖某种遥不可及的东西。 他还主张，计算机模型应当契合人类的心智，而不是要求人类反过来去契合它。 不是为所有人准备一套完美的工作流程。而是不同的人能够以不同方式栖居的系统。有人通过图像思考。有人需要写作。有人通过搭建模拟来理解问题。有人的生活方式组织方式完全不像一个 SaaS 仪表盘。 一个能随着你理解的变化而重塑的系统。 这就是我希望 AI 使之成为可能的东西。不只是批量产出软件，而是与软件建立一种活生生的关系。能够追问某个东西为什么这样运作。改动其中一部分而不必放弃其余部分。看看发生了什么。撤销它。学到足够多，以便自己做出下一次改动。 机器可以变得更有能力，而不必让人变得更渺小。 但这不会仅仅因为我们把模型做得更好就发生。我们必须在意它。为它而设计。留意到我们何时在让人更加依赖，却称之为赋能。 我不想只用“有多少工作在没有我们的情况下完成”来衡量未来。 我想知道，对于那些以前无法参与的人来说，什么变得可能了。 他们现在能理解什么？能表达什么？能在不请求许可的情况下改变什么？ 当我说“增强人类智能”时，我指的就是这个。 不是一个不再需要我们这个世界。 而是一个我们有更多能力去塑造的世界。

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augmenting human intellect when i started making software, i wasn’t dreaming of a factory. i loved that something on a screen could become an extension of my mind. a place to put a thought before i understood it. to move things around until new connections appeared. to make little systems that worked the way i worked, even if it made no sense to anyone else. the computer wasn’t interesting because it could do work without me. it was interesting because of what i could do with it. the early lineage of computing was built around this possibility. in 1962, Engelbart described augmenting human intellect as helping a person understand complex situations and find solutions that were previously out of reach. his starting point was the human being, not the autonomous machine. he wasn’t describing a faster black box. he was looking at the whole relationship between a person, their tools, their language, their methods, and what they could learn to do with them. the capability belonged to that whole system. somewhere along the way, we started telling a much smaller story about a much more powerful technology. more automation. more agents. more software producing more software. more output from fewer people. more growth. more numbers to prove that something is happening. and less attention to the person any of this is supposed to be for. i don’t want to pretend computing had a pure innocent beginning. replacing human labor was one of its ambitions. even in 1960, Licklider distinguished human-computer symbiosis from systems where the remaining people mainly served the machine. he wanted computers to participate in the formation of ideas, not only execute problems already defined. that distinction feels important – does the system help you discover what you mean? or does it only want you to submit a request, and wait outside while it works? sometimes waiting is exactly what i want. please do the search. move the files. take away the repetitive work. but not everything difficult is overhead. sometimes moving the pieces around is how you understand them. sometimes making the thing changes what you wanted to make. sometimes you need to see the wrong version, touch it, take it apart, and discover a better question. i want tools that leave room for that relationship. in his 1981 paper on Smalltalk, Ingalls described a system meant to support everyone’s creative spirit. personal mastery mattered: an individual should be able to comprehend the system, rather than remain dependent on something permanently beyond their reach. he also argued that computer models should fit the human mind, rather than demand the reverse. not one perfect workflow for everyone. systems that different people can inhabit differently. someone who thinks through pictures. someone who needs to write. someone who understands a problem by building a simulation. someone whose way of organizing their life doesn’t resemble a SaaS dashboard. a system you can reshape as your understanding changes. this is what i want AI to make possible. not just pumping out software, but having a living relationship with it. being able to ask why something works this way. change one part without surrendering the rest. see what happened. undo it. learn enough to make the next change yourself. the machine can become more capable without making the person smaller. but that won’t happen just because we make the models better. we have to care about it. design for it. notice when we are making someone more dependent while calling it empowerment. i don’t want to measure the future only by how much work happens without us. i want to know what becomes possible for the person who couldn’t participate before. what can they understand now? what can they express? what can they change without asking permission? when i say augmenting human intellect, that is what i mean. not a world that no longer needs us. a world we have more ability to shape.