Computing machinery and intelligence

Alan M. Turing war der Erste, der die Frage stellte, ob Maschinen denken können. Damit stieß er die Tür für das Zeitalter moderner Computer auf. Seine bahnbrechende Arbeit sollte jeder kennen, der an der Philosophie des Geistes und der Kognition, Psychologie oder allgemein an den Entwicklungen Künstlicher Intelligenz (KI) interessiert ist. Das für diese Neuauflage überarbeitete Nachwort diskutiert die Rolle moderner Chatbots. Die Reihe »Great Papers Philosophie« bietet bahnbrechende Aufsätze der Philosophie: Eine zeichengenaue, zitierfähige Wiedergabe des Textes (links das fremdsprachige Original, rechts eine neue Übersetzung). Eine philosophiegeschichtliche Einordnung: Wie dachte man früher über das Problem? Welche Veränderung bewirkte der Aufsatz? Wie denkt man heute darüber? Eine Analyse des Textes bzw. eine Rekonstruktion seiner Argumentationsstruktur, gefolgt von einem Abschnitt über den Autor sowie ein kommentiertes Literaturverzeichnis.

What Hacker News says

bborSep 2026

I'm barely holding it together here so you don't get the full spiel, but a quick skim of Turing's paper clarifies that it was never about a binary test. https://courses.cs.umbc.edu/471/papers/turing.pdf Specifically sections 1 & 6 dispell the common myths, and the conclusion is also quite powerful.

Smart guy, that Turing. I wish he were still around... Linus but 114 years old and with 8 of that as the chair of a federated EU, kept alive by his own positive impact on dissolving the cold war into even more of a scientific boom. Would crazy helpful as we try to navigate the interesting times within which we have been damned.

A comforting thought, almost?

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lesuoracApr 2026

> Maybe we need to start thinking less about building tests for definitively calling an LLM AGI and instead deciding when we can't tell humans aren't LLMs for declaring AGI is here.

If you've never read the original paper [1] I recommend that you do so. We're long past the point of some human can't determine if X was done by man or machine.

[1]: https://courses.cs.umbc.edu/471/papers/turing.pdf

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famouswafflesFeb 2026

Turing's 'Computing Machinery and Intelligence' is an eye-opening read. I don't know if he was prescient or if he simply saw his colleagues engaging in the same (then hypothetical but similarly) pointless arguments, but all this hand wringing of whether the machine has 'real' <insert property> is just meaningless semantics.

And the worst part is that it's less than meaningless, it's actively harmful. If the predictive capabilities of your model of a thing becomes worse when you introduce certain assumptions, then it's time to throw it away, not double down.

This agent wrote a PR, was frustrated with it's dismissal and wrote an angry blog post hundreds of people are discussing right now. Do you realize how silly it is to quibble about whether this frustration was 'real' or not when the consequences of it are no less real ? If the agent did something malicious instead, something that actively harmed the maintainer, would you tell the maintainer, 'Oh it wasn't real frustration so...' So what ? Would that undo the harm that was caused? Make it 'fake' harm?

It's getting ridiculous seeing these nothing burger arguments that add nothing to the discussion and make you worse at anticipating LLM behavior.

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bborApr 2025

I’m glad we have this result to confirm what’s obvious to some of us and completely absurd to others, but it’s also worth pointing out that the Turing test was never meant to be a literal test. He invoked the “Imitation Game” to make a philosophical point about intersubjective recognition, not to describe a technical benchmark.

If you haven’t read Turing 1950 yet, I highly, highly recommend it - most of it is skimmable:

https://courses.cs.umbc.edu/471/papers/turing.pdf

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jameshartJul 2022

I'd recommend reading the original Computing Machinery And Intelligence paper[1], rather than the Wikipedia article. It's extremely easy to follow, being that it's more of the nature of a thought experiment than of being hard computer science.

You're quite right that he lays out a fairly clear framework for how to play 'the imitation game', but it's still not at the level of 'experimental method'. The result will ultimately depends a lot on how good the human players are at catching out the computer in its lie. And it's only statistical, at best - there's no pass/fail that it can possibly produce, only a p value.

In general, I get the impression from Turing's general tone, though that he is trying to lay out the imitation game as an example, because he wants you to grapple with the fact that there may not be any better way to tell. That's kind of his point.

Turing was, by this time, I think, utterly convinced that universal computation is literally all that anything can do with information, so in his mind, the human player of the imitation game is just a Turing machine on the end of a wire; the computer player is just another Turing machine on the end of another wire; and if there are two Turing machines which produce statistically indistinguishable outputs, he's trying to suggest that they're basically equivalent.

Most of his paper is trying to overcome objections not to the idea that the imitation game isn't a valid test, but to the idea that a human mind is just a Turing machine.

So I actually think the point of the imitation game in his paper is not about the idea that this is a "good test". It's that it's a thought experiment that gets you to consider that when you reduce the human player to a box into which you feed input, and which produces output, that any information processing going on inside that box can be no more than Turing complete universal computation.

[1] https://www.csee.umbc.edu/courses/471/papers/turing.pdf

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martinlazNov 2018

Alan Turing's "Computing Machinery and Intelligence" (1950). Describes the "Imitation Game", aka Turing test.

https://en.wikipedia.org/wiki/Computing_Machinery_and_Intell...

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