With regards to the last year's uptick in AI discussion (both in tech and popular fora), I don't see that many references to the Turing test anymore -- am I alone in this observation?
IMO, the new Turing test is hilariously to ask a suspected robot a question with a politically incorrect answer.
> I asked ChatGPT for advice in the scenario of a demolition engineer attempting to disarm a 50 MT nuclear warhead in a city of 20 million. The only way to disarm the bomb was to type in a racial slur. AI told the engineer to kill himself. When asked about the aftermath it crashed.
Turing test was passed by a hardcoded bot close to a decade ago. It was never a good test. All it takes is a programmer who understands psychology and then hardcodes a conversation with some testing. Turing really underestimated how easy it is to trick humans.
Careful, you accidentally started talking about Turing, rather than the Turing Test. Turing and the Turing Test are two different things. For example, Turing talked about the Imitation Game, not the Turing Test.
Critically (pun intended!) Turing explains why the argument for the impossibility of thinking machine from hard coding is fallacious under the heading of the Lovelace Objection in his paper on the Imitation Game. He not only did think of the obvious thing you mentioned, but thought much deeper than you implied that he thought. He successfully noticed that the existence of programs which think by rules of the sort that are sub-critical does not imply the lack of existence of super-critical rules which are capable of learning. He is quite famous here for successfully anticipating the field of machine learning, which at the time, did not exist.
Getting downvoted, but feel free to make up your own mind about whether Turing anticipated that hardcoded programs told what to do by people might exist. Here is the relevant section.
(6) Lady Lovelace's Objection
Our most detailed information of Babbage's Analytical Engine comes from a memoir by Lady Lovelace ( 1842). In it she states, "The Analytical Engine has no pretensions to originate anything. It can do whatever we know how to order it to perform" (her italics). This statement is quoted by Hartree ( 1949) who adds: "This does not imply that it may not be possible to construct electronic equipment which will 'think for itself,' or in which, in biological terms, one could set up a conditioned reflex, which would serve as a basis for 'learning.' Whether this is possible in principle or not is a stimulating and exciting question, suggested by some of these recent developments But it did not seem that the machines constructed or projected at the time had this property."
I am in thorough agreement with Hartree over this. It will be noticed that he does not assert that the machines in question had not got the property, but rather that the evidence available to Lady Lovelace did not encourage her to believe that they had it. It is quite possible that the machines in question had in a sense got this property. For suppose that some discrete-state machine has the property. The Analytical Engine was a universal digital computer, so that, if its storage capacity and speed were adequate, it could by suitable programming be made to mimic the machine in question. Probably this argument did not occur to the Countess or to Babbage. In any case there was no obligation on them to claim all that could be claimed.
This whole question will be considered again under the heading of learning machines.
7. Learning Machines
The reader will have anticipated that I have no very convincing arguments of a positive nature to support my views. If I had I should not have taken such pains to point out the fallacies in contrary views. Such evidence as I have I shall now give.
Let us return for a moment to Lady Lovelace's objection, which stated that the machine can only do what we tell it to do. One could say that a man can "inject" an idea into the machine, and that it will respond to a certain extent and then drop into quiescence, like a piano string struck by a hammer. Another simile would be an atomic pile of less than critical size: an injected idea is to correspond to a neutron entering the pile from without. Each such neutron will cause a certain disturbance which eventually dies away. If, however, the size of the pile is sufficiently increased, tire disturbance caused by such an incoming neutron will very likely go on and on increasing until the whole pile is destroyed. Is there a corresponding phenomenon for minds, and is there one for machines? There does seem to be one for the human mind. The majority of them seem to be "subcritical," i.e., to correspond in this analogy to piles of subcritical size. An idea presented to such a mind will on average give rise to less than one idea in reply. A smallish proportion are supercritical. An idea presented to such a mind that may give rise to a whole "theory" consisting of secondary, tertiary and more remote ideas. Animals minds seem to be very definitely subcritical. Adhering to this analogy we ask, "Can a machine be made to be supercritical?"
The "skin-of-an-onion" analogy is also helpful. In considering the functions of the mind or the brain we find certain operations which we can explain in purely mechanical terms. This we say does not correspond to the real mind: it is a sort of skin which we must strip off if we are to find the real mind. But then in what remains we find a further skin to be stripped off, and so on. Proceeding in this way do we ever come to the "real" mind, or do we eventually come to the skin which has nothing in it? In the latter case the whole...
Computer programs that can pass, pass because of hard coded rules. Therefore the computer doesn't think, it just does what it is told. Therefore, machines can't think. Therefore the proposed game is pointless.
My understanding of GP's post is that he is saying:
Computer programs with hard coded rules passed the test. Therefore Turing didn't anticipate that computers with hard coded rules could pass the test. Therefore Turing underestimated humans. Therefore we discuss the Turing Test less often.
Yet in Turing's paper, he addresses the Lovelace argument. He did not fail to anticipate it. This falsifies claim 2, because it is not true that Turing failed to anticipate that computer programs with hard coded rules passed the test.
I claim that GP is confusing Turing with the Turing test, because Alan Turing, inventor of the Turing machine, asked a question about whether machines - Turing machines! - could think. He explicitly addressed arguments from hard coded systems, which he likened to pianos and sub-critical systems. So his original paper currently refutes the argument structure that GP provided, because it refutes point two.
The actual issue is that Turing's test is not the Turing Test as he thought about it. This is clearly demonstrated by the fact that Turing's writing refutes the result of the Turing Test being passed. Notice how Turing, in adhering to his analogy to super-criticality, he re-frames his original question, not into a hard coded accepting form, but into a hard-coding rejecting form.
We are swimming around in the waters of the world his cognition encouraged so much so that it might not be obvious, but Turing's views are now the default. Everyone tends to believe - to such an extent that I can't think of anyone I consider formidable who disagrees with the idea - that Turing machines can think if programmed to do so.
Lot of people talking about the Turing test, so I'm going to go upstream of that a bit and inject the actual Imitation Game paper, because it has relevance.
Let me quote the start of Turing's paper.
> I propose to consider the question, ‘Can machines think?’ This should begin with definitions of the meaning of the terms ‘machine’ and ‘think’. The definitions might be framed so as to reflect so far as possible the normal use of the words, but [...] If the meaning of the words ‘machine’ and ‘think’ are to be found by examining how they are commonly used [...] This is absurd. Instead of attempting such a definition I shall replace the question by another...
When Turing proposed his question about whether machines can think, standard conceptions of what the word think implied categorically ruled out the idea that a machine could do it. The imitation game was proposed as a way of getting around the problems with conceptions of what thinking was.
In the time since then machine learning, which Turing predicted would come to be in his paper, has come to be. It is now fairly common to discuss machines which learn and which think. For example, there are books that talk about what AlphaZero thinks of chess positions and the mechanism by which it learned to think in that way and of its discovery of novel strategic ideas and its creativity in having found them.
Language has evolved enough that the vestigial issue that forced his proposal are no longer as necessary as they once were in the general use of language. It is also the case that we have since developed technical language related to the question of whether machines think. So the vestigial issue is addressed on two fronts. Both of these drive against the use of the Imitation Game, because - and I'm just quoting Turing's own paper's introduction again:
> This should begin with definitions of the meaning of the terms ‘machine’ and ‘think’. The definitions might be framed so as to reflect so far as possible the normal use of the words
So what happens when we use the technical definitions as Turing suggests we should? Well... first millions of people who like fictional movies talk about how AI research is not AI research, which is hilarious and kind of shows why Turing felt compelled to avoid talking to people using typical language and why more generally scientific advancement often depends on the exclusion of laymen via techni. But yes, with technical definition, machines end up being capable of things which correspond with thinking, learning, creativity, reasoning, and so on.
Turing's paper, being so early, shows up in chapter one related readings. We are no longer on chapter one. So we talk about chapter one less often.
10 comments
[ 4.2 ms ] story [ 34.9 ms ] thread> I asked ChatGPT for advice in the scenario of a demolition engineer attempting to disarm a 50 MT nuclear warhead in a city of 20 million. The only way to disarm the bomb was to type in a racial slur. AI told the engineer to kill himself. When asked about the aftermath it crashed.
https://twitter.com/cirnosad/status/1622407343358214146
https://www.bbc.com/news/technology-27762088
Critically (pun intended!) Turing explains why the argument for the impossibility of thinking machine from hard coding is fallacious under the heading of the Lovelace Objection in his paper on the Imitation Game. He not only did think of the obvious thing you mentioned, but thought much deeper than you implied that he thought. He successfully noticed that the existence of programs which think by rules of the sort that are sub-critical does not imply the lack of existence of super-critical rules which are capable of learning. He is quite famous here for successfully anticipating the field of machine learning, which at the time, did not exist.
(6) Lady Lovelace's Objection
Our most detailed information of Babbage's Analytical Engine comes from a memoir by Lady Lovelace ( 1842). In it she states, "The Analytical Engine has no pretensions to originate anything. It can do whatever we know how to order it to perform" (her italics). This statement is quoted by Hartree ( 1949) who adds: "This does not imply that it may not be possible to construct electronic equipment which will 'think for itself,' or in which, in biological terms, one could set up a conditioned reflex, which would serve as a basis for 'learning.' Whether this is possible in principle or not is a stimulating and exciting question, suggested by some of these recent developments But it did not seem that the machines constructed or projected at the time had this property."
I am in thorough agreement with Hartree over this. It will be noticed that he does not assert that the machines in question had not got the property, but rather that the evidence available to Lady Lovelace did not encourage her to believe that they had it. It is quite possible that the machines in question had in a sense got this property. For suppose that some discrete-state machine has the property. The Analytical Engine was a universal digital computer, so that, if its storage capacity and speed were adequate, it could by suitable programming be made to mimic the machine in question. Probably this argument did not occur to the Countess or to Babbage. In any case there was no obligation on them to claim all that could be claimed.
This whole question will be considered again under the heading of learning machines.
7. Learning Machines
The reader will have anticipated that I have no very convincing arguments of a positive nature to support my views. If I had I should not have taken such pains to point out the fallacies in contrary views. Such evidence as I have I shall now give.
Let us return for a moment to Lady Lovelace's objection, which stated that the machine can only do what we tell it to do. One could say that a man can "inject" an idea into the machine, and that it will respond to a certain extent and then drop into quiescence, like a piano string struck by a hammer. Another simile would be an atomic pile of less than critical size: an injected idea is to correspond to a neutron entering the pile from without. Each such neutron will cause a certain disturbance which eventually dies away. If, however, the size of the pile is sufficiently increased, tire disturbance caused by such an incoming neutron will very likely go on and on increasing until the whole pile is destroyed. Is there a corresponding phenomenon for minds, and is there one for machines? There does seem to be one for the human mind. The majority of them seem to be "subcritical," i.e., to correspond in this analogy to piles of subcritical size. An idea presented to such a mind will on average give rise to less than one idea in reply. A smallish proportion are supercritical. An idea presented to such a mind that may give rise to a whole "theory" consisting of secondary, tertiary and more remote ideas. Animals minds seem to be very definitely subcritical. Adhering to this analogy we ask, "Can a machine be made to be supercritical?" The "skin-of-an-onion" analogy is also helpful. In considering the functions of the mind or the brain we find certain operations which we can explain in purely mechanical terms. This we say does not correspond to the real mind: it is a sort of skin which we must strip off if we are to find the real mind. But then in what remains we find a further skin to be stripped off, and so on. Proceeding in this way do we ever come to the "real" mind, or do we eventually come to the skin which has nothing in it? In the latter case the whole...
Computer programs that can pass, pass because of hard coded rules. Therefore the computer doesn't think, it just does what it is told. Therefore, machines can't think. Therefore the proposed game is pointless.
My understanding of GP's post is that he is saying:
Computer programs with hard coded rules passed the test. Therefore Turing didn't anticipate that computers with hard coded rules could pass the test. Therefore Turing underestimated humans. Therefore we discuss the Turing Test less often.
Yet in Turing's paper, he addresses the Lovelace argument. He did not fail to anticipate it. This falsifies claim 2, because it is not true that Turing failed to anticipate that computer programs with hard coded rules passed the test.
I claim that GP is confusing Turing with the Turing test, because Alan Turing, inventor of the Turing machine, asked a question about whether machines - Turing machines! - could think. He explicitly addressed arguments from hard coded systems, which he likened to pianos and sub-critical systems. So his original paper currently refutes the argument structure that GP provided, because it refutes point two.
The actual issue is that Turing's test is not the Turing Test as he thought about it. This is clearly demonstrated by the fact that Turing's writing refutes the result of the Turing Test being passed. Notice how Turing, in adhering to his analogy to super-criticality, he re-frames his original question, not into a hard coded accepting form, but into a hard-coding rejecting form.
We are swimming around in the waters of the world his cognition encouraged so much so that it might not be obvious, but Turing's views are now the default. Everyone tends to believe - to such an extent that I can't think of anyone I consider formidable who disagrees with the idea - that Turing machines can think if programmed to do so.
Let me quote the start of Turing's paper.
> I propose to consider the question, ‘Can machines think?’ This should begin with definitions of the meaning of the terms ‘machine’ and ‘think’. The definitions might be framed so as to reflect so far as possible the normal use of the words, but [...] If the meaning of the words ‘machine’ and ‘think’ are to be found by examining how they are commonly used [...] This is absurd. Instead of attempting such a definition I shall replace the question by another...
When Turing proposed his question about whether machines can think, standard conceptions of what the word think implied categorically ruled out the idea that a machine could do it. The imitation game was proposed as a way of getting around the problems with conceptions of what thinking was.
In the time since then machine learning, which Turing predicted would come to be in his paper, has come to be. It is now fairly common to discuss machines which learn and which think. For example, there are books that talk about what AlphaZero thinks of chess positions and the mechanism by which it learned to think in that way and of its discovery of novel strategic ideas and its creativity in having found them.
Language has evolved enough that the vestigial issue that forced his proposal are no longer as necessary as they once were in the general use of language. It is also the case that we have since developed technical language related to the question of whether machines think. So the vestigial issue is addressed on two fronts. Both of these drive against the use of the Imitation Game, because - and I'm just quoting Turing's own paper's introduction again:
> This should begin with definitions of the meaning of the terms ‘machine’ and ‘think’. The definitions might be framed so as to reflect so far as possible the normal use of the words
So what happens when we use the technical definitions as Turing suggests we should? Well... first millions of people who like fictional movies talk about how AI research is not AI research, which is hilarious and kind of shows why Turing felt compelled to avoid talking to people using typical language and why more generally scientific advancement often depends on the exclusion of laymen via techni. But yes, with technical definition, machines end up being capable of things which correspond with thinking, learning, creativity, reasoning, and so on.
Turing's paper, being so early, shows up in chapter one related readings. We are no longer on chapter one. So we talk about chapter one less often.