From TFA: "Eric Schwitzgebel writes that . . . There’s a huge cognitive difference between nodding along while reading something and actually productively generating a text. Two reasons: First, once the text is on the page, it’s easy to passively let the approximate word suffice, rather than thinking about word choice in the same effortful, active way we do when generating prose de novo. Second, as I suggested above, I doubt that human beings, even experts, have a good sense of all the factors that shape word choice -- everything they’re being sensitive to. You would have phrased it slightly differently, and even if you don’t know that, or why, a different signal is sent and received."
This is the best articulation I've seen of why simply reviewing and copy-editing does not provide remotely the same value as writing from scratch. I spent a considerable amount of time over the past two weeks reviewing and improving a work document that was the output of an LLM. Given the number of people involved and the final level of effort, I'm firmly convinced that writing it manually would have been faster and resulted in a higher quality product. Getting the wording right matters.
> First, once the text is on the page, it’s easy to passively let the approximate word suffice, rather than thinking about word choice in the same effortful, active way we do when generating prose de novo.
Meanwhile, me, as an English non-native speaker, ended up discussing two sentences I want send to HR for ten minutes while applying to a job.
I do believe there's generally a bias to accept something that's already written. The much bigger reason though is why you let somebody else write it to begin with.
It might just be that not thinking carefully about every sentence/wording was the exact thing that made you use AI to begin with.
> I spent a considerable amount of time over the past two weeks reviewing and improving a work document that was the output of an LLM.
I had the same experience with texts where I have a very detailed expectation of the desired result.
This is just a general limitation. For code, there's the saying "the precise description of the solution is already the code". Describing X is a simplification of X, oftentimes it's fine guess the gaps. But when it's not, it didn't help to describe X, you have to manifest X itself.
patrickmay · · focus · HN ↗
This is the best articulation I've seen of why simply reviewing and copy-editing does not provide remotely the same value as writing from scratch. I spent a considerable amount of time over the past two weeks reviewing and improving a work document that was the output of an LLM. Given the number of people involved and the final level of effort, I'm firmly convinced that writing it manually would have been faster and resulted in a higher quality product. Getting the wording right matters.
bulbar · · focus · HN ↗
Meanwhile, me, as an English non-native speaker, ended up discussing two sentences I want send to HR for ten minutes while applying to a job.
I do believe there's generally a bias to accept something that's already written. The much bigger reason though is why you let somebody else write it to begin with.
It might just be that not thinking carefully about every sentence/wording was the exact thing that made you use AI to begin with.
> I spent a considerable amount of time over the past two weeks reviewing and improving a work document that was the output of an LLM.
I had the same experience with texts where I have a very detailed expectation of the desired result. This is just a general limitation. For code, there's the saying "the precise description of the solution is already the code". Describing X is a simplification of X, oftentimes it's fine guess the gaps. But when it's not, it didn't help to describe X, you have to manifest X itself.