Reveal the informational nature of conscious self and sense of agency under the information closure theory of consciousness
Project/Area Number |
22K20679
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Research Category |
Grant-in-Aid for Research Activity Start-up
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Allocation Type | Multi-year Fund |
Review Section |
0704:Neuroscience, brain sciences, and related fields
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Research Institution | The University of Tokyo |
Principal Investigator |
チャン ユーチャン 東京大学, 大学院工学系研究科(工学部), 特任助教 (50831484)
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Project Period (FY) |
2022-08-31 – 2024-03-31
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Project Status |
Granted (Fiscal Year 2022)
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Budget Amount *help |
¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2023: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2022: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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Keywords | Consciousness / ICT / Mathematical Model / Neural Systems / Sense of Agency / Artificial Intelligence / Scale Problem / Simulation / information closure / Conscious Action |
Outline of Research at the Start |
This project investigates conscious action and the sense of agency using the framework of the Information Closure Theory of consciousness. Research aims include understanding the sense of agency via information theory and identifying conscious action and agency in neural and artificial systems.
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Outline of Annual Research Achievements |
Research Update: We have successfully navigated the first phase of our project, establishing mathematical foundations of conscious self and agency within the Information Closure Theory (ICT) framework. By hypothesizing informational closure (IC) and non-trivial informational closure (NTIC), we've begun to understand how consciousness might be scale-dependent within the neural system. The second phase, presently underway, involves small-scale simulations. Early results are promising, with artificial agents displaying potential NTIC processes post-training. We're working diligently to determine if these processes encode not only environmental data but also information about the system's partition and action states. If successful, these results will provide a critical step towards applying our refined ICT framework to leading artificial systems in phase three, thereby contributing significantly to both neuroscience and ethical discussions in AI research.
In addition to our progress in the first two phases, we've also made several significant breakthroughs in terms of the practical implications of our research. We've identified key neuroscientific insights that could have a profound impact on our understanding of the human brain and consciousness, and we've also uncovered potential ethical implications of our work with AI systems.
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Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
Our project is progressing well, following the established timeline. Phase 1, which involved the development of a mathematical model within the Information Closure Theory (ICT) framework, was completed successfully. In Phase 2, we conducted small-scale simulations and observed promising results, indicating the model's potential to capture conscious self and agency. As we transition into Phase 3, we will apply the ICT framework to leading artificial agents. Despite the complexity of the research, we've experienced no significant delays, affirming the project's smooth progression. We anticipate valuable insights in both neuroscience and AI ethics.
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Strategy for Future Research Activity |
Moving into the second half of the project, our focus shifts to Phase 3, where we'll apply the newly developed ICT framework to leading AI systems. We'll measure conscious self and agency in these systems, a critical step in validating our model. This phase involves developing empirical measures for systems with large numbers of elements, an aspect essential for both AI and neurophysiological data analysis. We anticipate potential challenges due to the complexity of advanced AI systems, but we're well-equipped to tackle them. The findings from this phase will provide key insights into consciousness in different anatomical systems, benefiting neuroscience and AI ethics.
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Report
(1 results)
Research Products
(1 results)