Article
Version 1
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Rethinking Human and Machine Intelligence through Kant, Wittgenstein, Gödel, and Cantor
Version 1
: Received: 13 October 2023 / Approved: 13 October 2023 / Online: 13 October 2023 (11:37:25 CEST)
Version 2 : Received: 26 October 2023 / Approved: 26 October 2023 / Online: 26 October 2023 (11:30:49 CEST)
Version 3 : Received: 5 December 2023 / Approved: 6 December 2023 / Online: 6 December 2023 (09:20:28 CET)
Version 2 : Received: 26 October 2023 / Approved: 26 October 2023 / Online: 26 October 2023 (11:30:49 CEST)
Version 3 : Received: 5 December 2023 / Approved: 6 December 2023 / Online: 6 December 2023 (09:20:28 CET)
How to cite: Lee, J. J. Rethinking Human and Machine Intelligence through Kant, Wittgenstein, Gödel, and Cantor. Preprints 2023, 2023100876. https://doi.org/10.20944/preprints202310.0876.v1 Lee, J. J. Rethinking Human and Machine Intelligence through Kant, Wittgenstein, Gödel, and Cantor. Preprints 2023, 2023100876. https://doi.org/10.20944/preprints202310.0876.v1
Abstract
This paper proposes a new metaphysical framework for distinguishing between human and machine intelligence by drawing on Kant’s incongruent counterparts as an analogy. Specifically, the paper posits two deterministic worlds that are superficially identical but ultimately different. Using ideas from Wittgenstein, Gödel, and Cantor, the paper defines “deterministic knowledge” and investigates how this knowledge is processed differently in those two worlds. The paper considers computationalism and causal determinism for the new framework. Then, the paper introduces new concepts to illustrate why human and machine agents display different causal characteristics in processing verbal information. Overall, the paper’s framework provides a theoretical basis for the uniqueness of the human mind.
Keywords
ontology; AI; incongruent counterparts; computationalism; emergentism; determinism
Subject
Arts and Humanities, Philosophy
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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