Temporal Interception and Present Reconstruction: A Cognitive-Signal Model for Human and AI Decision Making
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arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866918021196414976 |
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| author | A, Carmel Mary Esther |
| author_facet | A, Carmel Mary Esther |
| contents | This paper proposes a novel theoretical model to explain how the human mind and artificial intelligence can approach real-time awareness by reducing perceptual delays. By investigating cosmic signal delay, neurological reaction times, and the ancient cognitive state of stillness, we explore how one may shift from reactive perception to a conscious interface with the near future. This paper introduces both a physical and cognitive model for perceiving the present not as a linear timestamp, but as an interference zone where early-arriving cosmic signals and reactive human delays intersect. We propose experimental approaches to test these ideas using human neural observation and neuro-receptive extensions. Finally, we propose a mathematical framework to guide the evolution of AI systems toward temporally efficient, ethically sound, and internally conscious decision-making processes |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_09646 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Temporal Interception and Present Reconstruction: A Cognitive-Signal Model for Human and AI Decision Making A, Carmel Mary Esther Neurons and Cognition Artificial Intelligence History and Philosophy of Physics This paper proposes a novel theoretical model to explain how the human mind and artificial intelligence can approach real-time awareness by reducing perceptual delays. By investigating cosmic signal delay, neurological reaction times, and the ancient cognitive state of stillness, we explore how one may shift from reactive perception to a conscious interface with the near future. This paper introduces both a physical and cognitive model for perceiving the present not as a linear timestamp, but as an interference zone where early-arriving cosmic signals and reactive human delays intersect. We propose experimental approaches to test these ideas using human neural observation and neuro-receptive extensions. Finally, we propose a mathematical framework to guide the evolution of AI systems toward temporally efficient, ethically sound, and internally conscious decision-making processes |
| title | Temporal Interception and Present Reconstruction: A Cognitive-Signal Model for Human and AI Decision Making |
| topic | Neurons and Cognition Artificial Intelligence History and Philosophy of Physics |
| url | https://arxiv.org/abs/2505.09646 |