nafyi.

原始来源

The Overhang

One Useful Thing ·

A source by Ethan Mollick outlining human advantages—deep knowledge, wide knowledge, taste, and agency—for collaborating with current AI models; explaining how wide knowledge aids prompting by enabling invocation of conceptual frameworks known to LLMs; and noting that domain expertise improves both the quality and quantity of AI output, per Anthropic research.

Ethan Mollick
打开发布者 （在新标签页中打开）

一目了然

关键段落3

带明确归属与语境的原文片段。打开原始文本核查出处。

段落 9 （在新标签页中打开）
Human advantages with AI

Four personal advantages for working with AI

原始摘录

In my book, I outline four particular personal advantages that matter a lot if you want to use AI in unique and enhancing ways: deep knowledge, wide knowledge, taste, and agency.
Ethan Mollick·
上下文

That is why I think we will need to focus on the individual traits we have that remain useful even as AI abilities improve. You are not trying to compete with AI in producing outputs, that is a losing game. Instead, you want to use your human advantages as basis of working with AI to do things that neither of you could do alone.

段落 10 （在新标签页中打开）
Expertise and AI output quality

Deep knowledge improves AI results

原始摘录

And recent work from Anthropic suggests that expertise also shapes the quality of what AI gives back . Experts not only get better work out of AI, they get more work out of it.
Ethan Mollick·
上下文

The first two advantages come from what you know. Deep knowledge is the expertise that comes from understanding a field or subject so well that you build intuition around it to quickly and accurately make decisions. It is how an experienced accountant can glance at a spreadsheet and know something is wrong, or how a golf pro can watch a swing and instantly understand the mistake the golfer is making. It is also why I could tell within seconds that the first trailer was more ominous than the book actually is. Deep knowledge is the realm of the specialist, and it is the only way to truly understand the shape of the Jagged Frontier, because only experts can understand the patterns of where AI succeeds or fails, at least in their area of expertise. It also helps you adapt to change because deep knowledge makes it easier to switch from being someone who does the work to someone who manages it.

段落 11 （在新标签页中打开）
interdisciplinary literacy

Wide knowledge enables effective prompting

原始摘录

The training data for LLMs is a large swath of humanity’s vast output. The AI has learned something of design thinking and Bayesian reasoning and the Toyota Production System and Rogerian therapy and Marxist literary criticism. But AI tends not to volunteer any of these patterns unless you know to ask.
Ethan Mollick·
上下文

But you don’t just need deep knowledge, you also want wide knowledge.

来源与研究方法

这些观点均关联原始来源。转述已明确标注，不作为逐字原话展示。

打开转录或来源材料 （在新标签页中打开）报告问题