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Comment by colinmorelli | Hacker News Reader

This is an interesting take. By this perspective, it's essentially impossible to ever gauge the efficacy of AI in doing anything, because the people who will know how to measure the quality of that thing are also the people who will be displaced by showing the AI can do that thing. In fact, you could probably argue that every study ever is worthless, because studies are generally performed by people who know the subject matter and it's basically impossible to be unbiased on a topic if you're also highly knowledgable about said topic.

In reality, what matters is the methodology of the study. If the study's methodology is sound, and its results can be reproduced by others, then it is generally considered to be a good study. That's the whole reason we publish methodologies and results: so others can critique and verify. If you think this study is bad, explain why. The whole document is there for you to review.

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I think you are correct, and incorrect. However: set and setting. Another of Lanier's observations, which he relates to LLMs, is the Boeing "smart" stall preventer which crashed two <strike>Dreamliners</strike> [correction:] 737 MAXes.

Who can argue with a stall preventer, right? What one can, and has been exposed / argued with, is the observation that information about the operation of the stall preventer, training, and even the ability to effectively control it depended on how much the airline was willing to pay for this necessary feature.

So in reality, what matters is studying the methodology of set and setting, not how the pieces of the crashed airship ended up where they did.

I'm not exactly sure how this relates to my comment above. An analysis of an airline crash and a study are not the same thing.

As it relates to study design, controlling for set and setting are part of the methodology. For example, most drug studies are double-blinded so that neither patients nor clinicians are aware of whether the patient is getting the drug or not, to reduce or eliminate any placebo effect (i.e. to control for the "set"/mental state of those involved in the study).

There are certainly some cases in which it's effectively impossible to control for these factors (i.e. psychedelics). That's not what's really being discussed here, though.

An airline crash is an n of 1 incident, and not the same as a designed study.

> it's essentially impossible to ever gauge the efficacy of AI in doing anything...

... compared to humans? Yes. This is a philosophical conundrum which you tie yourself up in if you choose to postulate the artificial intelligence as equivalent to, rather than a simulacrum of, human intelligence. We fly (planes): are we "smarter" than birds? We breathe underwater: are we "smarter" than fish? And so on.

How do you discern that the "other" has an internal representation and dialogue? Oh. Because a human programmed it to be so. But how do you know that another human has internal representation and dialogue? I do (I have conscious control over the verbal dialogue but that's another matter), so I choose to believe that others (humans) do (not the verbal part so much unfortunately). I could extend that to machines, but why? I need a better reason than "because". I'd rather extend the courtesy to a bird or a fish first.

This is an epistemological / religious question: a matter of faith. There are many things which we can't really know / rigorously define against objective criteria.

This, similar to your other comment, is unrelated to my comment.

This is about determining if AI can be a equivalent or better (defined as: achieving equal or better clinical outcomes) therapist than a human. That is a question that can be studied and answered.

Whether artificial intelligence accurately models human intelligence, or whether an airplane is "smarter" than a bird, are entirely separate questions that can perhaps serve to explain _why/how_ the AI can (or can't) achieve better results than the thing we're comparing against, but not whether it does or does not. Those questions are perhaps unanswerable based on today's knowledge. But they're not prerequisites.

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