The Turing Test Is a Moving Goalpost — Benjamin Harris
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So, along the lines of, you know, AGI, and again, these questions about intelligence, um, the Turing test, I used to use a version of this with students, um, long before, you know, generative AI was on the, on the horizons.
Came from my, my days in college, Philosophy 101, and, you know, basically we're asked to—I don't have a technical definition in front of me—but we're asked to consider the question, you know, if a computer can give the same answers so that if you're communicating with it through text or whatever, you can't tell if there's a computer or a person on the other end.
Um, well, then should we ascribe it the same mental life and intelligence that we ascribe to a person? Um, yeah, how do you think about that? And maybe you have a more precise, uh, computer science definition of the test.
I don't know. No, the, the, the Turing test, yeah, it was all the way back in the 1950s, Alan Turing, uh, when he was working in the early theory of computation. Um, no, you, you had a, a good working definition. You know, if you're, if you know there's two rooms behind you and you're getting text inputs from a questions you ask, how do you tell if one is a human and one's a computer? And if it's, you know, a system that is statistically indistinguishable from a human, we would say, okay, passes the Turing test. I think we are actually already there with that, with the Turing test. I think we have systems that you can, um, you can write fairly complex questions to, uh, and this is always an interesting, like, thought experiment of, like, what question would you ask that a, uh, artificial intelligence system that you know is an AI system would fail to answer well?
Right? Um, that's kind of an interest—sort of a subfield here. But I think we're, I think we already have systems that pass the Turing test. The, uh, but I think this is, it's the current application of the Turing test, I think, is a moving, um, a bit of a moving standard in that you, you have a system that seems to pass the Turing test, and then humans get used to how it communicates. Right? You begin to pick up the flavor or the nuance of, like, this sounds like it was AI generated. Right? I think we all, if we've read AI generated text, we sort of know what that feels like. It's very, it's very linear, very clear.
There's no halting, pausing. There's, it's, like, it's mechanical in a sense. And so, um, now what an AI company might say is, okay, I'll adjust my, my generation algorithm to make it a little more clunky, a little more human-like. Right? And then it, it passes the new standard of the Turing test that people can't distinguish. Um, but I, whenever you have a test that relies on human perception of something, that, uh, like, we grow, we learn. Right? That, that the benchmark for that test is going to change over time. So, you know, I think we, we have systems that at early GPTs probably passed the Turing test. Now the standard's even higher. Right? For a system to be indistinguishable from a human.
Um, and it's not because the systems have changed so much as we have changed and learned. And so. We've learned how to, how to deal with it. Yeah, that's a good perspective.