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Comment by Traster | Hacker News Reader

I think what Turing is getting at here is actually less a commentary on what AI should do, than a shortcoming in the test. When you're looking for genuine intelligence you should be looking for intelligence. However, if your only sign of intelligence is human intelligence, suddenly getting a basic sum wrong is counter-intuitively a sign of intelligence.

In the end getting the sum wrong is an emergent property of human intelligence, we're good at things but we're not deterministically perfect like computers are. It's not better for a computer to start to share the shortcomings of humans, but it is more likely to pass the 'AI' test. Indicating a shortcoming in the test.

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That is, to pass for a human, the AI should imitate humans. This includes imitating their mistakes. AI's genuine mistakes would likely be different enough to help humans tell an AI from a human.

That is, the best strategy for an AI to pass the test is to be perfect, and perfectly imitate a perfect amount of human mistakes.

This definitely requires an ability to lie, to knowingly tell untrue things.

This ability is also required by much simpler circumstances: when directly asked, an AI should be able to lie and say "No, I'm a human", else it will fail the test instantly.

This likely means that a robot following the Asimov's three laws would never pass a direct Turing test.

> This likely means that a robot following the Asimov's three laws would never pass a direct Turing test.

Not necessarily true. An AI could pretend that it doesn't follow Asimov's laws while in fact following them. For example, the AI could pretend that, to execute the given order (second law), it first needs to understand the author psychology. At that point the AI can change the author's mind by using persuasive tactics. If the AI successfully changed author's mind, it successfully didn't follow the initial order by simply cancelling it with consent of the author

The first and third laws are also applicable to humans, and cannot be used to detect the AI

I tend to agree with the conclusion in the article that the Turing test wasn't really meant as a blueprint for general AI or whatever other (later) concept we're now familiar with but rather just a though experiment on whether it would even be possible to attribute intelligence to a computer. Or perhaps whether it would be possible not to attribute intelligence to it.

Or the more unnerving and less useful personality trait of lying. The Turing test is after all a game of deceit. Whether the human believes the AI to be human or the AI believes itself to be categorically human begins to blur the lines.

I'm not sure it is a a shortcoming though. It's an entirely defensible proposition that under some circumstances, accuracy and reply speed is inversely correlated with intelligence.

Consider: you ask two colleagues a deep and subtle yes/no question. One immediately replies 'nah'. The other thinks for a long time and then finally replies "I don't think so, but I'm not totally sure..." Which of your colleagues has demonstrated greater intelligence?

Accuracy is not certainty. The one that's most informative is the one that's demonstrating greater intelligence.

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