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Conceptual Limitations

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Limits of AI - theoretical, practical, ethical

Part of the book series: Technik im Fokus ((TECHNIK))

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Abstract

If the Turing test would be used as benchmark for the successful implementation of artificial intelligence, statistics-based AI is in a dilemma—at least as long as it is still operating in the in black box mode. This is because one only need to follow up on a question, which can be answered as well as possible by the AI, with the next question: “Why?”.

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Notes

  1. 1.

    It is something else that AI can, of course, “memorize” an argument if the very same question was already answered in the learning data; ChatGPT makes use of this possibility, when it recourse to its enormous learning data.

  2. 2.

    This disadvantage is accepted, on the one hand, because the program creation in the AI learning process is faster and, above all, is done by the computer itself and no longer requires a trained computer scientist. On the other hand, it is possible to tackle problems whose external complexity does not allow direct programming.

  3. 3.

    Christian Thiel [14] discusses Artin’s board as a paradigmatic example of creativity. On the notion of structure that comes into play here, see [15].

  4. 4.

    Historically, the example of the mutilated chessboard can be traced back to Max Black who posed it in 1946 as a problem in his book Critical Thinking [16, exercise 6, p. 142] (but starting off with the chess board, thus, leaving out the creative part of adding this structure as a first step). It is also reported that Emil Artin occasionally used this example in his lectures (see [15, 17]); it might well be that he took it from Black (or some other later source), but it was stressed in a obituary for Artin that he applied the idea of the solution within his mathematical activity, as he had “the very rare ability to detect, in seemingly highly complex issues, simple and transparent structures” [18, p. 39].

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Authors and Affiliations

  1. TUM Senior Excellence Faculty, Technische Universität München, München, Germany

    Klaus Mainzer

  2. Carl Friedrich von Weizsäcker-Zentrum, Universität Tübingen, Tübingen, Germany

    Reinhard Kahle

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  1. Klaus Mainzer
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  2. Reinhard Kahle
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Correspondence to Klaus Mainzer .

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Mainzer, K., Kahle, R. (2024). Conceptual Limitations. In: Limits of AI - theoretical, practical, ethical . Technik im Fokus. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-68290-6_4

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  • DOI: https://doi.org/10.1007/978-3-662-68290-6_4

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