Each conversation lasted a total of five minutes. According to the paper, which was published in May, the participants judged GPT-4 to be human a shocking 54 percent of the time. Because of this, the researchers claim that the large language model has indeed passed the Turing test.
That’s no better than flipping a coin and we have no idea what the questions were. This is clickbait.
On the other hand, the human participant scored 67 percent, while GPT-3.5 scored 50 percent, and ELIZA, which was pre-programmed with responses and didn’t have an LLM to power it, was judged to be human just 22 percent of the time.
Aye, I’d wager Claude would be closer to 58-60. And with the model probing Anthropic’s publishing, we could get to like ~63% on average in the next couple years? Those last few % will be difficult for an indeterminate amount of time, I imagine. But who knows. We’ve already blown by a ton of “limitations” that I thought I might not live long enough to see.
The whole point of the Turing test, is that you should be unable to tell if you’re interacting with a human or a machine. Not 54% of the time. Not 60% of the time. 100% of the time. Consistently.
They’re changing the conditions of the Turing test to promote an AI model that would get an “F” on any school test.
But you have to select if it was human or not, right? So if you can’t tell, then you’d expect 50%. That’s different than “I can tell, and I know this is a human” but you are wrong…
Now that we know the bots are so good, I’m not sure how people will decide how to answer these tests. They’re going to encounter something that seems human-like and then essentially try to guess based on minor clues… So there will be inherent randomness.
If something was a really crappy bot then it wouldn’t ever fool anyone and the result would be 0%.
Each conversation lasted a total of five minutes. According to the paper, which was published in May, the participants judged GPT-4 to be human a shocking 54 percent of the time. Because of this, the researchers claim that the large language model has indeed passed the Turing test.
That’s no better than flipping a coin and we have no idea what the questions were. This is clickbait.
On the other hand, the human participant scored 67 percent, while GPT-3.5 scored 50 percent, and ELIZA, which was pre-programmed with responses and didn’t have an LLM to power it, was judged to be human just 22 percent of the time.
54% - 67% is the current gap, not 54 to 100.
While I agree it’s a relatively low percentage, not being sure and having people pick effectively randomly is still an interesting result.
The alternative would be for them to never say that gpt-4 is a human, not 50% of the time.
Participants only said other humans were human 67% of the time.
Which makes the difference between the AIs and humans lower, likely increasing the significance of the result.
Aye, I’d wager Claude would be closer to 58-60. And with the model probing Anthropic’s publishing, we could get to like ~63% on average in the next couple years? Those last few % will be difficult for an indeterminate amount of time, I imagine. But who knows. We’ve already blown by a ton of “limitations” that I thought I might not live long enough to see.
The whole point of the Turing test, is that you should be unable to tell if you’re interacting with a human or a machine. Not 54% of the time. Not 60% of the time. 100% of the time. Consistently.
They’re changing the conditions of the Turing test to promote an AI model that would get an “F” on any school test.
But you have to select if it was human or not, right? So if you can’t tell, then you’d expect 50%. That’s different than “I can tell, and I know this is a human” but you are wrong… Now that we know the bots are so good, I’m not sure how people will decide how to answer these tests. They’re going to encounter something that seems human-like and then essentially try to guess based on minor clues… So there will be inherent randomness. If something was a really crappy bot then it wouldn’t ever fool anyone and the result would be 0%.