You can just say it

原始链接: https://noperator.dev/posts/you-can-just-say-it/

支持人类价值的论点往往基于一个不稳固的前提,即人类在质量或风格上优于人工智能。这种方法很危险,因为它将人类的价值锚定在一个正不断缩小的能力差距上,而随着技术进步,这个差距很可能会消失。 相反,我们应该断言人类具有无条件的价值。 除了人类价值之外,作者还区分了创作中的“形式”与“意图”。真正的创作是将意图提炼为形式的过程,而使用生成式人工智能时,这一过程往往会丧失。虽然人工智能可以用极少的意图产生大量的输出,但这通常会导致“劣质内容”——即缺乏定义人类创造力的、可辨识的思维模型。人类会费尽心思地塑造作品以符合其意图,而人工智能则可以在没有明确内在目的的情况下生成精致的形式。归根结底,由于人工智能允许形式在没有意图的情况下存在,它有稀释沟通背后意义的风险。我们珍视人类的产出,不应是因为它在竞争意义上“更好”,而因为它是一种意图的真实体现——无论自动生产如何兴起,这一过程依然至关重要。

在最近的一场 Hacker News 讨论中,开发者 Salvatore Sanfilippo (antirez) 对“AI 垃圾内容”(AI slop)提出了独到的见解。他认为问题的根源不在于人工智能本身,而在于其输出内容背后缺乏意图与理解。他将“垃圾内容”定义为在缺乏统一动机或明确规范下生成的大量信息。 Sanfilippo 指出,高质量的 AI 辅助编程需要用户提供一个意图“种子”——即为 AI 提供一套结构化且有目的的引导。相比之下,如果仅仅是在 AI 出错时要求其“重试”,只会产生低质量且缺乏方向的输出。 这一观点在讨论帖中引起了其他开发者的共鸣。一位用户表示,这种区分缓解了他们对软件开发未来的“身份危机”,并从“人类的掌控与愿景依然必不可少”这一理念中获得了慰藉。尽管讨论中也存在对作者哲学比喻的轻微质疑,但共识依然聚焦于“意图性”的重要性:当 AI 由人类策略驱动而非仅仅依赖被动、重复的指令时,它才能成为强大的工具。
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原文

There is a weird collection of arguments for appraising the value of humans and their creative artifacts. It usually goes something like this: In the age of AI, we should still prefer humans in certain roles because AI could never perform the tasks required for that role. Or, a human can at least do it better. Or, perhaps the output from a human and AI may look similar, but human output is preferable for subtle stylistic reasons that an AI cannot reproduce. Or, at least the AI cannot reproduce it consistently. Observe the scuff marks around the base of the goalpost from constant movement. Allow 28 days for the concrete to cure.

This line of thinking boils down to, “Humans are valuable if they produce high-quality output.” This argument dangerously depends on the existing-but-narrowing human-AI capability gap. The gap certainly existed in the past (2023-era ChatGPT). It may still exist now. I do not know if it will hold in the future.

Consider instead

“Humans are valuable.” You can just say it. As a human yourself, I advise you to. You do not need to qualify it. This is a robust statement that is not conditional on a point-in-time snapshot of the leading frontier model’s score on some recent benchmark.

Qualities of “quality”

As a related but importantly unnecessary aside: How do you measure the quality of a creative artifact? Is it effective? Does it accomplish the thing it is meant to do? This question implies two subcomponents of quality: intent and material form. It seems to me that many arguments for the value of creative artifacts focus too much on form at the expense of intent.

Creation is the distillation of intent into form. Intent is usually inseparably embedded into the form of the artifact. A human iteratively (sometimes painstakingly) shapes and reshapes their creation until it sufficiently matches what’s in their mind’s eye. The odd thing about generative AI is that it can produce substantial form with minimally applied intent. A human can show up to a task with an unclear mental model of what they mean to accomplish, and an AI can generate something anyway. “Write a letter of resignation for me to send to my boss.” “Hmm…I guess that looks good.”

Perhaps “AI slop” is really a way of expressing that it’s difficult to identify the intent behind the form. By that definition, humans are very capable of generating slop, too; generative AI has simply lowered the entry barrier for creating intentless form. It could be said that intent is expressed in the prompt. For prose text artifacts, a well-developed prompt is perhaps near the intended form already. In a recent conversation about (not) using LLMs to mediate human communication, my friend Tom Hudson told me, “If you’re going to use an LLM to write me an email, I’d much rather you just send me the prompt; at least then I’d have an idea of what you actually meant to say.”

The pathology of generative AI is that it too easily allows substantial form without discernible intent. That mistake is harder to make when creating by hand.

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