Decoding Consciousness in Artificial Intelligence

Xiong, Momiao

doi:10.6339/24-JDS1117

Journal of Data Science

Decoding Consciousness in Artificial Intelligence

Volume 22, Issue 1 (2024), pp. 1–9

Momiao Xiong

https://doi.org/10.6339/24-JDS1117

Pub. online: 18 January 2024 Type: Philosophies Of Data Science

Open Access

Received
5 December 2023

Accepted
16 January 2024

Published
18 January 2024

Abstract

The exploration of whether artificial intelligence (AI) can evolve to possess consciousness is an intensely debated and researched topic within the fields of philosophy, neuroscience, and artificial intelligence. Understanding this complex phenomenon hinges on integrating two complementary perspectives of consciousness: the objective and the subjective. Objective perspectives involve quantifiable measures and observable phenomena, offering a more scientific and empirical approach. This includes the use of neuroimaging technologies such as electrocorticography (ECoG), EEG, and fMRI to study brain activities and patterns. These methods allow for the mapping and understanding of neural representations related to language, visual, acoustic, emotional, and semantic information. However, the objective approach may miss the nuances of personal experience and introspection. On the other hand, subjective perspectives focus on personal experiences, thoughts, and feelings. This introspective view provides insights into the individual nature of consciousness, which cannot be directly measured or observed by others. Yet, the subjective approach is often criticized for its lack of empirical evidence and its reliance on personal interpretation, which may not be universally applicable or reliable. Integrating these two perspectives is essential for a comprehensive understanding of consciousness. By combining objective measures with subjective reports, we can develop a more holistic understanding of the mind.

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