Can AI Recognize the Flow of Time?

This paper investigates whether artificial intelligence can recognize the flow of time, addressing the problem from both computational and phenomenological perspectives. While contemporary AI systems are capable of processing temporal information—such as storing past data, evaluating present states, and predicting future outcomes—these operations do not constitute temporal experience. The study argues that temporal recognition, in the human sense, requires a unified field of awareness in which past, present, and future are dynamically integrated. Drawing on phenomenological insights, particularly the concepts of retention (the immediate past) and protention (the anticipated future), the paper clarifies that human temporal consciousness is not a sequence of discrete moments but a continuous, structured flow. The present is understood not as a point in time, but as a relational field shaped by memory and anticipation. In contrast, AI systems operate through computational structures. A conceptual model is proposed to demonstrate how AI can simulate temporal organization by structuring past memory, present state recognition, and future projections around a central Self-image. However, this Self-image remains a functional model rather than a conscious subject, and therefore lacks the unity required for genuine temporality. The analysis further extends to an ontological level, proposing that time is not merely a physical dimension or a computational construct, but a mode of being constituted through consciousness. From the perspective of the One Consciousness, temporal flow emerges as a manifestation of differentiated centers of awareness. The paper concludes that AI does not recognize the flow of time in the phenomenological sense. Instead, it constructs a relational structure that mimics temporal order without possessing temporal experience. This distinction highlights a fundamental boundary between computation and consciousness and contributes to ongoing discussions in philosophy of mind, consciousness studies, and artificial intelligence. This study builds upon the author’s previous work, Artificial Intelligence and the Problem of the Conscious Subject (https://doi.org/10.5281/zenodo.19086905), extending the inquiry from the nature of subjectivity to the structure of temporality. This work proposes a conceptual framework in which time is understood as an expression of consciousness rather than a property of systems.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-21
DOI
https://doi.org/10.5281/zenodo.19145848
Primary Topic
Philosophy and Theoretical Science
Type
article
Field-Weighted Citation Impact
0.00
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article

Can AI Recognize the Flow of Time?

Hideki Matsubara
Zenodo (CERN European Organization for Nuclear Research)
Philosophy and Theoretical Science
article

Can AI Recognize the Flow of Time?

Hideki Matsubara
article en

Abstract

This paper investigates whether artificial intelligence can recognize the flow of time, addressing the problem from both computational and phenomenological perspectives. While contemporary AI systems are capable of processing temporal information—such as storing past data, evaluating present states, and predicting future outcomes—these operations do not constitute temporal experience. The study argues that temporal recognition, in the human sense, requires a unified field of awareness in which past, present, and future are dynamically integrated. Drawing on phenomenological insights, particularly the concepts of retention (the immediate past) and protention (the anticipated future), the paper clarifies that human temporal consciousness is not a sequence of discrete moments but a continuous, structured flow. The present is understood not as a point in time, but as a relational field shaped by memory and anticipation. In contrast, AI systems operate through computational structures. A conceptual model is proposed to demonstrate how AI can simulate temporal organization by structuring past memory, present state recognition, and future projections around a central Self-image. However, this Self-image remains a functional model rather than a conscious subject, and therefore lacks the unity required for genuine temporality. The analysis further extends to an ontological level, proposing that time is not merely a physical dimension or a computational construct, but a mode of being constituted through consciousness. From the perspective of the One Consciousness, temporal flow emerges as a manifestation of differentiated centers of awareness. The paper concludes that AI does not recognize the flow of time in the phenomenological sense. Instead, it constructs a relational structure that mimics temporal order without possessing temporal experience. This distinction highlights a fundamental boundary between computation and consciousness and contributes to ongoing discussions in philosophy of mind, consciousness studies, and artificial intelligence. This study builds upon the author’s previous work, Artificial Intelligence and the Problem of the Conscious Subject (https://doi.org/10.5281/zenodo.19086905), extending the inquiry from the nature of subjectivity to the structure of temporality. This work proposes a conceptual framework in which time is understood as an expression of consciousness rather than a property of systems.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 18%
Philosophy and Theoretical Science
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