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Simulacrum of Knowledge Work

blog.happyfellow.dev

11–20 of 97 posts

Re: Simulacrum of Knowledge Work

#11
post #9

I don't really agree with the premise of the article. Sure proxy measures are everywhere. But for knowledge work specifically you can usually check real quality. Of course it's not as extremely easy as "oh this report contains a few spelling errors", but it is doable. If you accepted work purely based on superficial proxy measures you were not fairly evaluating work at all.

I think there’s a weaker claim that holds true: we were able to ignore lots of content based on the superficial (and pay proper attention to work that passed this test) and now we are overwhelmed because everything meets the superficial criteria and we can’t pay proper attention to all of it.

That's what I had in mind! The whole post is a claim that evaluating knowledge work got more expensive because cheaper measures stopped correlating well with quality.

If someone was already evaluating the work output using a metric closer to the underlying quality then it might not have been a big shift for them (other than having much more work to evaluate).

Re: Simulacrum of Knowledge Work

#12

The article asserts that the quality of human knowledge work was easier to judge based on proxy measures such as typos and errors, and that the lack of such "tells" in AI poses a problem. I don't know if I agree with either assertion… I've seen plenty of human-generated knowledge work that was factually correct, well-formatted, and extremely low quality on a conceptual level. And AI signatures are now easy for people…

Yes. I think the main warning here is that it is an added risk. A little glitch here and there until something breaks.

Re: Simulacrum of Knowledge Work

#13
If you have a test that fails 50% times - is that test valuable or not? A 50% failure rate alone looks like a coin toss, but by itself that does not tell us whether the test is noise or whether it is separating bad states from good ones. For a test to be useful it needs to have positive Youden’s statistic (https://en.wikipedia.org/wiki/Youden%27s_J_statistic): sensitivity + specificity - 1. A 50% failure rate alone does not let us calculate sensitivity and specificity.

I can see a similar problem with this article - the author notices that LLMs produce a lot of errors - then concludes that they are useless and produce only simulacrum of work. The author has an interesting observation about how llms disrupt the way we judge knowledge work. But when he concludes that llms do only simulacrum of work - this is where his arguments fail.

Re: Simulacrum of Knowledge Work

#14

The article asserts that the quality of human knowledge work was easier to judge based on proxy measures such as typos and errors, and that the lack of such "tells" in AI poses a problem. I don't know if I agree with either assertion… I've seen plenty of human-generated knowledge work that was factually correct, well-formatted, and extremely low quality on a conceptual level. And AI signatures are now easy for people…

It's not that pre-LLM era was a "golden age of quality", far form it. It's that LLMs have removed yet another tell-tale of rushed bullshit jobs.

Re: Simulacrum of Knowledge Work

#16
The FUD about LLM's will never get old. The way I know and trust LLM's is the same way a manager would trust their reportees to do good work.

For most tasks, the complexity/time required to verify a task is I wrote a post detailing this argument https://simianwords.bearblog.dev/the-generation-vs-verificat...

Re: Simulacrum of Knowledge Work

#17
Ultimately to understand a thing is to do the thing. And to not understand (which is ok!) is to trust others to, proxy measures or not. Agreed that the future of work is in a precarious place: doing less and trusting more only works up to a point.

`simulacrum` is a great word, gotta add that to my vocabulary.

Re: Simulacrum of Knowledge Work

#18
post #13

If you have a test that fails 50% times - is that test valuable or not? A 50% failure rate alone looks like a coin toss, but by itself that does not tell us whether the test is noise or whether it is separating bad states from good ones. For a test to be useful it needs to have positive Youden’s statistic ( https://en.wikipedia.org/wiki/Youden%27s_J_statistic ): sensitivity + specificity - 1. A 50% failure rate alone…

Gee, a thing by a guy, with a name. What are you saying exactly? So the test in question is a test the LLM is asked to carry out, right? Then your point is that if it's a load of vacuous flannel 49% of the time, but meaningful 51% of the time, on average this is genuine work so we can't complain about the 49%?

Wait, you're probably talking about the test of discarding a report based on something superficial like spelling errors. Which fails with LLMs due to their basic conman personalities and smooth talking. And therefore ..?

Re: Simulacrum of Knowledge Work

#19
post #9

I don't really agree with the premise of the article. Sure proxy measures are everywhere. But for knowledge work specifically you can usually check real quality. Of course it's not as extremely easy as "oh this report contains a few spelling errors", but it is doable. If you accepted work purely based on superficial proxy measures you were not fairly evaluating work at all.

I think there’s a weaker claim that holds true: we were able to ignore lots of content based on the superficial (and pay proper attention to work that passed this test) and now we are overwhelmed because everything meets the superficial criteria and we can’t pay proper attention to all of it.

Yes, I agree that this is true!

You could however only do that if you were fine with unfairly judging the quality of work, as you now readily discarded quality work based on superficial proxies. Which admittedly is done in a lot of cases.

Re: Simulacrum of Knowledge Work

#20
post #14

The article asserts that the quality of human knowledge work was easier to judge based on proxy measures such as typos and errors, and that the lack of such "tells" in AI poses a problem. I don't know if I agree with either assertion… I've seen plenty of human-generated knowledge work that was factually correct, well-formatted, and extremely low quality on a conceptual level. And AI signatures are now easy for people…

It's not that pre-LLM era was a "golden age of quality", far form it. It's that LLMs have removed yet another tell-tale of rushed bullshit jobs.

Have they though?
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