I think you may think passing the Turing test is more difficult and meaningful than it is. Computers have been able to pass the Turing test for longer than genAI has been around. Even Turing thought it wasn't a useful test in reality. He meant it as a thought experiment.
It would be a bit more difficult if you were dealing with an LLM agent tasked with faking a turing test as opposed to a naieve LLM just responding as usual, but even there the LLM will reveal itself by the things that it plain can't do.
The intent (it was just a thought experiment) of a Turing test, was that if you can't tell it's not AGI, then it is AGI, which is semi-reasonable, as long as it's not the village idiot administering the test! It was never intended to be "if it can fool some people, some of the time, then it's AGI".
Obviously as time goes on, and chatbots/AI progress then it'll become harder and harder to distinguish. Eventually we'll have AGI and AGI+ - capable of everything that we can do, including things such as emotional responses, but it'll still be detectable as an alien unless we get to the point of actually emulating a human being in considerable detail as opposed to building an artificial brain with most or all of the same functionality (if not the flavor).
I often interact with the web all day and don't write any text a human could evaluate.
However, I'd have to guess that given a reasonable amount of data an LLM vs human interacting with websites would be fairly easy to spot since the LLM would be more purposeful - it'd be trying to fulfill a task, while a human may be curious, distracted by ads, put off by slow response times, etc, etc.
I don't think it's a very interesting question whether LLMs can sometimes generate output indistinguishable from humans, since that is exactly what they were trained to do - to mimic human-generated training samples. Apropos a Turing test, the question would be can I tell this is not a human, even given a reasonable amount of time to probe it in any way I care ... but I think there is an unspoken assumption that the person administering the test is qualified to do so (else the result isn't about AGI-ability, but rather test administrator ability).
Even before modern LLMs, some scrape-detectors would look for instant clicks, no random mouse moves, etc., and some scrapers would incorporate random delays, random mouse movements, etc.
The original Turing test is a social game, like the Mafia party game. It's not a game people try to play very often. It's unclear if any bot could win competing against skilled human opponents who have actually practiced and know some tricks for detecting bots.
The game is much harder if the human player is trying to pretend to be a machine.
Even if they lie, you could ask them 20 times and they d reply the lie, without feeling annoyed: FAIL.
LLMs cannot pass the Turing test, it's easy to see they're not human. They always enjoy questions ! And they never ask any !
The turning test wasn't meant to be bulletproof, or even quantifiable. It was a thought experiment.
I do agree (and I think there is a general consensus) that passing the Turing test is less meaningful than it may seem, it used to be considered an AGI-complete task and this is now clearly not the case.
But I think it’s important to get the attribution right, LLMs were the tech that unexpectedly passed the Turing test.
From my experience, AI has significantly improved since, and I expect that ChatGPT o3 or Claude 4 Opus would pass a 30 minute test.
> In the test, a human evaluator judges a text transcript of a natural-language conversation between a human and a machine. The evaluator tries to identify the machine, and the machine passes if the evaluator cannot reliably tell them apart. The results would not depend on the machine's ability to answer questions correctly, only on how closely its answers resembled those of a human.
Based on this, I would agree with the OP in many contexts. So, yeah, 'basically', is a load bearing word here but seems reasonably correct in the context of distinguishing human vs bot in any scalable and automated way.
Didn’t realize plexiglass existed in the 1930s!
I'm certainly not a monetization expert. But don't most consumers recoil in horror at subscriptions? At least enough to offset the idea they can be used for everything?
Not sure why this isn’t getting more attention - super helpful and way better than I expected!
The third has also been written by many a bot for at least fifteen years.