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Black-box artificial intelligence: an epistemological and critical analysis

  • Manuel CarabantesEmail author
Original Article

Abstract

The artificial intelligence models with machine learning that exhibit the best predictive accuracy, and therefore, the most powerful ones, are, paradoxically, those with the most opaque black-box architectures. At the same time, the unstoppable computerization of advanced industrial societies demands the use of these machines in a growing number of domains. The conjunction of both phenomena gives rise to a control problem on AI that in this paper we analyze by dividing the issue into two. First, we carry out an epistemological examination of the AI’s opacity in light of the latest techniques to remedy it. And second, we evaluate the rationality of delegating tasks in opaque agents.

Keywords

Artificial intelligence Philosophy of technology Machine learning XAI Deep neural networks GDPR Instrumental reason 

Notes

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Faculty of PhilosophyUniversidad Complutense de Madrid (Complutense University of Madrid)MadridSpain

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