Insights for AI from the Human Mind

Artificial intelligence has recently beaten world champions in Go and poker and made extraordinary progress in domains such as machine translation, object classification, and speech recognition. However, most AI systems are extremely narrowly focused. AlphaGo, the champion Go player, does not know that the game is played by putting stones onto a board; it has no idea what a “stone” or a “board” is, and would need to be retrained from scratch if you presented it with a rectangular board rather than a square grid.” To build AIs able to comprehend open text or power general-purpose domestic robots, we need to go further. A good place to start is by looking at the human mind, which still far outstrips machines in comprehension and flexible thinking. This CACM article offers 11 clues drawn from the cognitive sciences—psychology, linguistics, and philosophy. Link

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2 Responses to Insights for AI from the Human Mind

  1. This is not about insights from the human mind, but about the architecture of the human psyche (Self, Soul, Mind), so we can safely say that this article is at least 20 years behind in the development of artificial intelligence.

    The notion of “Truly intelligent and flexible systems” is complete nonsense.

    Systems thinking does think in wholes rather than parts (the holistic principle), but does not ask the question of the being of those wholes. And thus there is no place in this thinking for an ontology (or a theory of being) and in connection with that: transcendence.

  2. With the rise of Large Language Models (LLMs), interest in ontology has only increased.

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