Will Machine Learning Yield Machine Intelligence?

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Samenvatting

This paper outlines the non-behavioral Algorithmic Similarity criterion for machine intelligence, and assesses the likelihood that it will eventually be satisfied by computers programmed using Machine Learning (ML). Making this assessment requires overcoming the Black Box Problem, which makes it difficult to characterize the algorithms that are actually acquired via ML. This paper therefore considers Explainable AI’s prospects for solving the Black Box Problem, and for thereby providing a posteriori answers to questions about the possibility of machine intelligence. In addition, it suggests that the real-world nurture and situatedness of ML-programmed computers constitute a priori reasons for thinking that they will not only learn to behave like humans, but that they will also eventually acquire algorithms similar to the ones that are implemented in human brains.

Originele taal-2Engels
TitelPhilosophy and Theory of Artificial Intelligence 2017
UitgeverijSpringer
Pagina's225-227
Aantal pagina's3
Volume44
ISBN van geprinte versie978-3-319-96447-8
DOI's
StatusGepubliceerd - 2018
Extern gepubliceerdJa

Publicatie series

NaamStudies in Applied Philosophy, Epistemology and Rational Ethics
Volume44
ISSN van geprinte versie2192-6255
ISSN van elektronische versie2192-6263

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