[ninetyninenine]

>What are these "thousands of quantitative metrics" on which you base your latest claims? If you have had them on hand all this while, it seems odd that you have not made use of them so far.

Hey no offense but I don't appreciate this style of commenting where you say it's "odd." I'm not trying to hide evidence from you and I'm not intentionally lying or making things up in order to win an argument here. I thought of this as a amicable debate. Next time if you just ask for the metric rather then say it's "odd" that I don't present it that would be more appreciated.

I didn't present evidence because I thought it was obvious. How are LLMs compared with one another in terms of performance? Usually those are done with quantitative tests. You can feed any number of these tests including stuff like the SAT, BAR, ACT, IQ, SATII etc.

They also have LLM targetted tests as well:

https://assets-global.website-files.com/640f56f76d313bbe3963...

Most of these tests aren't enough though as the LLM is remarkably close to human behavior and can do comparably well and even better than most humans. I mean that last statement I made would usually make you think that those tests are enough, but they aren't because humans can still detect whether or not the thing is an LLM with a longer targetted conversation.

The final run is really giving the human with full knowledge of his task a full hour of investigating an LLM to decide whether it's human or a robot. If the LLM can deceive the human that is a hard True/False quantitative metric. That's really the only type of quantitative test left where there is a detectable difference.

[mannykannot]

I had no intention of implying any malfeasance in my use of the word "odd"; I mean it in the sense of unusual, unexpected and surprising. The thing is, you finishished your precursor post saying, about your tests and mine, that it comes down to there being a human in the loop making a judgement call, but in a follow-on you say that there are thousands of quantitative metrics. Why, I wondered, would that matter, if it comes down to a human making a judgement call? Were you switching to a different line of argument, one that (as far as I could tell) had not been raised before? That's what I found surprising about your claim.

I am still rather confused about how this fits into what you are saying more generally. At first I thought you were saying, in your latest post, that the Turing-test interrogator should be restricted to asking questions from the sets having quantitative metrics in order for it to be an objective process, but that doesn't really hold up, as far as I can see. Frankly, I suspect that the tests with objective metrics are beside the point, and the essence of your position is contained within your final paragraph: "If the LLM can deceive the human [then] that is a hard True/False quantitative metric [and the only sort we can get]."

If so, then (no surprise) I think there are some problems with it, but before I go further, I would like to check that I understand your position.

[ninetyninenine]

>I had no intention of implying any malfeasance in my use of the word "odd"; I mean it in the sense of unusual, unexpected and surprising. The thing is, you finishished your precursor post saying, about your tests and mine, that it comes down to there being a human in the loop making a judgement call, but in a follow-on you say that there are thousands of quantitative metrics. Why, I wondered, would that matter, if it comes down to a human making a judgement call? Were you switching to a different line of argument, one that (as far as I could tell) had not been raised before? That's what I found surprising about your claim.

It matters because of humans. If I gave an LLM thousands of quantitative tests and it passed them all but in an hour long conversation a human could identify it was an LLM through some flaw the human would consider all those tests useless. That's why it matters. The human making a judgement call is still a quantitative measurement btw as you can limit human output to True or False. But because every human is different in order to get good numbers you have to do measurements with multitudes of humans.

>I am still rather confused about how this fits into what you are saying more generally. At first I thought you were saying, in your latest post, that the Turing-test interrogator should be restricted to asking questions from the sets having quantitative metrics in order for it to be an objective process, but that doesn't really hold up, as far as I can see.

it can still be objective with a human in the loop assuming the human is honest. What's not objective is a human offering an opinion in the form of a paragraph with no definitive clarity on what constitutes a metric. I realize that elements of MY metric have indeterminism to it, but it is still a hard metric because the output is over a well defined set. Whenever you have indeterminism you would then turn to probability and many samples in order to produce a final quantitative result.

>If so, then (no surprise) I think there are some problems with it, but before I go further, I would like to check that I understand your position.

yes my position is that exactly. If all observable qualities indicate it's a duck, then there's nothing more you can determine beyond that, scientifically speaking. You're implying there is a better way?

[mannykannot]

At this point, I think it is worth refreshing what the issue here is, which is whether LLMs understand that the language they receive is about an external world, which operates through causes which have nothing to do with token-combination statistics of the language itself.

> It matters because of humans...

I'm still a bit puzzled here, because it seems to me that the paragraph continuing from here is making the argument that LLM performance on these tests doesn't matter, as far as the question is concerned: in this paragraph you seem to be saying (paraphrased) that despite LLMs' impressive performance on these quantitative tests, they could still fail Turing tests, so their performance on these quantitative tests is not decisive.

> yes my position is that exactly…

The impression I get from what you have written in this post is that you are not claiming that a test conforming to your requirements has actually been successfully performed, you are just assuming it could be?

Regardless, let’s assume (at least for the sake of argument) that the series of tests you propose have been performed, and the results are in: in the test environment, humans can’t distinguish current LLMs from humans any better than by chance. How do you get from that to answering the question we are actually interested in? The experiment does not explicitly address it. You might want to say something like “The Turing test has shown that the machines are as intelligent as humans so, like humans, these machines must realize that the language they receive is about an external world” but even the antecedent of that sentence is an interpretation that goes beyond what would have objectively been demonstrated by the Turing test, and the consequent is a subjective opinion that would not be entailed by the antecedent even if it were unassailable. Do you have a way to go from a successful Turing test to answering the question here, which meets your own quantitative and objective standards?

[ninetyninenine]

>I'm still a bit puzzled here, because it seems to me that the paragraph continuing from here is making the argument that LLM performance on these tests doesn't matter, as far as the question is concerned: in this paragraph you seem to be saying (paraphrased) that despite LLMs' impressive performance on these quantitative tests, they could still fail Turing tests, so their performance on these quantitative tests is not decisive.

It matters in the quantitative sense. It measures AI performance. What it won't do is matter to YOU. Because you're a human and humans will keep moving the bar to a higher standard right? When AI shot passed the turing test humans just moved the goal posts. So to convince someone like YOU we have to look at the final metric. The point where LLM I/O becomes indistinguishable/superior to humans. Of course you look at the last decade... AI is rapidly approaching that final bar.

>The impression I get from what you have written in this post is that you are not claiming that a test conforming to your requirements has actually been successfully performed, you are just assuming it could be?

Whether I assume or don't assume, the projection of the trendline currently indicates that it will. Given the trendline that is the most probable conclusion.

>The experiment does not explicitly address it.

Nothing on the face of the earth can address the question. Because nobody truly knows what "understanding" something actually is. You can't even articulate the definition in a formal way such that it can be dictated on a computer program.

So I went to the next best possibility, which is my point. The point is ALTHOUGH we don't know what understanding is, we ALL assume humans understand things. So we set that as a bar metric. Anything indistinguishable from a human must understand things. Anything that appears close to a human but is not quite human must understand things ALMOST as well as a human.

[mannykannot]

> What it won't do is matter to YOU. Because you're a human and humans will keep moving the bar to a higher standard right? When AI shot passed the turing test humans just moved the goal posts. So to convince someone like YOU we have to look at the final metric.

It is disappointing to see you descending into something of a rant here. If you knew me better, you would know that I spend more time debating in opposition to people who think they can prove that AGI/artificial consciousness is impossible than I do with people who think it is already an undeniable fact that it has already been achieved (though this discussion is shifting the balance towards the middle, if only briefly.) Just because I approach arguments in either direction with a degree of skepticism and I don't see any value in trying to call the arrival of true AGI at the very first moment it occurs, it does not mean that I'm trying (whether secretly or openly) to deny that it is possible either in the near-term or at all. FWIW, I regard the former as possible and the latter highly probable, so long as we don't self-destruct first.

> Nothing on the face of the earth can address the question. Because nobody truly knows what "understanding" something actually is. You can't even articulate the definition in a formal way such that it can be dictated on a computer program.

The anti-AI folk I mentioned above would willingly embrace this position! They would say that it shows that human-like intelligence and consciousness lies outside of the scope of the physical sciences, and that this creates the possibility of a type of p-zombie that is indistinguishable by physical science from a human and yet lacks any concept of itself as an entity within an external world.

More relevantly, your response here repeats an earlier fallacy. In practice, concepts and their definitions are revised, tightened, remixed and refined as we inquire into them and gain knowledge. I know you don't agree, but as this is not an opinion but an empirical observation, validated by many cases in the history of science and science-like disciplines, I don't see you prevailing here - and there's the knowledge-bootstrap problem if this were not the case, as well.

It occurred to me this morning that there's a variant or extension of the quantitative Turing test which goes like this:

We have two agents and a judge. The judge is a human and the agents are either a pair of humans, a pair of AIs, or one of each, chosen randomly and without the judge being unaware of the mix. One of the agents is picked, by random choice, to start a discussion with the other with the intent of exploring what the other understands about some topic, with the discussion-starter being given the freedom to choose the topic. The discussion proceeds for a reasonable length of time - let's say one hour.

The judge follows the discussion but does not participate in it. At the conclusion of the discussion, the judge is required to say, for each agent, whether it is more likely that it is a human or AI, and the accuracy of this call is used to assign a categorical variable to the result, just as in the version of the Turing test you have described.

This seems just as quantitative, and in the same way, as your version, yet there's no reason to believe it will necessarily yield the same results. More tests are better, so what's not to like?

[ninetyninenine]

>It is disappointing to see you descending into something of a rant here.

I'm going to be frank with you. I'm not ranting and uncharitable comments like this aren't appreciated. I'm going to respond to your reply later in another post, but if I see more stuff like this I'll stop stop communicating with you. Please don't say stuff like that.