Psychology Dictionary of Arguments

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Brockman I 115
Imitation/Deutsch: (…) our ancestors were barely people. This was not due to any inadequacy in their brains. On the contrary, even before the emergence of our anatomically modern human sub-species, they were making things like clothes and campfires, using knowledge that was not in their genes. It was created in their brains by thinking, and preserved by individuals in each generation imitating their elders. Moreover, this must have been knowledge in the sense of understanding, because it is impossible to imitate novel complex behaviors like those without understanding what the component behaviors are for.(1)
Such knowledgeable imitation depends on successfully guessing explanations, whether verbal or not, of what the other person is trying to achieve and how each of his actions contributes to that (…)
No nonhuman ape today has this ability to imitate novel complex behaviors. Nor does any present-day artificial intelligence. But our pre-sapiens ancestors did. >Learning/Deutsch.


1. “Aping” (imitating certain behaviors without understanding) uses inborn hacks such
as the mirror-neuron system. But behaviors imitated that way are drastically limited in complexity. See Richard Byrne, “Imitation as Behaviour Parsing,” Philosophical Transactions of the Royal Society B 358, no. 1431 (2003): 529—36.


Deutsch, D. “Beyond Reward and Punishment” in: Brockman, John (ed.) 2019. Twenty-Five Ways of Looking at AI. New York: Penguin Press.


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Explanation of symbols: Roman numerals indicate the source, arabic numerals indicate the page number. The corresponding books are indicated on the right hand side. ((s)…): Comment by the sender of the contribution.
The note [Author1]Vs[Author2] or [Author]Vs[term] is an addition from the Dictionary of Arguments. If a German edition is specified, the page numbers refer to this edition.

Deutsch I
D. Deutsch
Fabric of Reality, Harmondsworth 1997
German Edition:
Die Physik der Welterkenntnis München 2000

Brockman I
John Brockman
Possible Minds: Twenty-Five Ways of Looking at AI New York 2019


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