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Understanding and Machine Consciousness

R. Sanz, Esther Aguado

Journal of Artificial Intelligence and Consciousness September 1, 2020 DOI: 10.1142/s2705078520500137 (opens in new tab) via Semantic Scholar

Summary

AI-generated from the abstract

Machine consciousness research combines computers, robots, neuropsychology, sociology, and philosophy. This mix creates both opportunity and risk of endless, unproductive debates that may not improve machine building. The paper analyzes this situation, advocates for an engineering approach to machine consciousness, and proposes a strategy centered on machine understanding to move beyond the current stagnation.

Study at a glance

Characteristics Theoretical or philosophical paper Peer reviewed
Keywords Computer science Psychology Philosophy Engineering
Key finding Argues that an engineering approach focused on machine understanding can advance machine consciousness research beyond unproductive interdisciplinary debates.

Abstract

The domain of machine consciousness is a melting pot of computers, robots, neuropsychology, sociology and philosophy. This is both an opportunity and a serious risk of stagnation in entertaining but never-ending discussions that may prove useless concerning the construction of better machines. This paper analyzes this situation, defends an engineering approach to machine consciousness research and proposes a strategy focused on machine understanding to get out of the current impasse.

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