Weaving Beyond the Mind: A Philosophical Framework for Post-Individual Intelligence

Authors

  • Jorge Rodas-Osollo *

    Electrical Engineering and Computation Department, Engineering and Technology Institute, University of Juarez City, Juarez 32310, Mexico

    Faculty of Philosophy and Literature, Autonomous University of Chihuahua, Chihuahua 31203, Mexico
  • Karla Olmos-Sanchez

    Electrical Engineering and Computation Department, Engineering and Technology Institute, University of Juarez City, Juarez 32310, Mexico

     

DOI:

https://doi.org/10.55121/prr.v3i1.848

Keywords:

Cognitive Tapestry, Distributed Cognition, Entropic Knowledge, Ethics of AI, Phantom Objectivities, Post-Individual Intelligence

Abstract

This article advances the thesis that knowledge, agency, and responsibility can be stabilised beyond the individual mind within hybrid human–AI systems. It proposes and develops the Cognitive Tapestry as a philosophical framework grounded in computational models of associative memory—Entropic Hetero Associative Memory and Alpha–Beta BAM. Methodologically, it institutes projection–protection barriers to discipline inferences from computational models to philosophical reflection and operationalises four invariants—dispersion (D), redundancy (R), mutual information (I), and revision-readiness (ρ)—that distinguish distributed cognition from mere aggregation. Epistemologically, it reconceives knowledge as resilience under bounded uncertainty, articulated through the categories of phantom objectivities, entropic networks, tacit knowledge, and group agency. Metaphysically, it treats emergence as explanatory rather than ontological and frames post-individual intelligence through controlled indeterminacy. Ethically, it introduces responsibility matrices that scale accountability across human, algorithmic, and institutional roles, illustrated through case studies in pandemic response, medical triage, DevSecOps pipelines, open-source collaboration, and swarm robotics. The article also addresses objections concerning misplaced concreteness, functionalist reductionism, emergence, and the so-called responsibility gap, and positions the framework as an open research line rather than a final doctrine. Its contribution lies in providing a disciplined vocabulary and method for analysing knowledge, agency, and responsibility across socio-technical systems, thereby offering a coherent orientation for philosophical reflection in the Cognitive Era.

References

[1] Cea, I., Signorelli, C.M., 2025. How to be an integrated information theorist without losing your body. Frontiers in Computational Neuroscience. 18, 1510066. DOI: https://doi.org/10.3389/fncom.2024.1510066

[2] Tollefsen, D., 2025. Shaping the Institutional Mind. Philosophies. 10(5), 112. DOI: https://doi.org/10.3390/philosophies10050112

[3] Parr, T., Pezzulo, G., Friston, K.J., 2022. Active Inference: The Free Energy Principle in Mind, Brain, and Behavior (Open Access edition). The MIT Press: Cambridge, MA, USA. DOI: https://doi.org/10.7551/mitpress/12441.001.0001

[4] Polanyi, M., 1966. The Tacit Dimension. Doubleday & Company: Garden City, NY, USA.

[5] Rodas-Osollo, J., 2023. An Interesting Adventure Accompanied by CMCg.I Model. Zenodo: Geneva, Switzerland. Available from: https://zenodo.org/records/10111223

[6] Morales, R., Pineda, L.A., 2025. The missing cue problem in hetero associative memory retrieval. Scientific Reports. 15, 21850. DOI: https://doi.org/10.1038/s41598-025-07963-x

[7] Acevedo-Mosqueda, E., Cruz, J.M., Cruz, A., 2007. Alpha–Beta BAM: A bidirectional associative memory model with alpha–beta learning. Neural Processing Letters. 26(1), 1–20.

[8] Floridi, L., 2011. The Philosophy of Information. Oxford University Press: Oxford, UK.

[9] Floridi, L., 2013. The Ethics of Information. Oxford University Press: Oxford, UK.

[10] Munn, L., 2023. The uselessness of AI ethics. AI and Ethics. 3, 869–877. DOI: https://doi.org/10.1007/s43681-022-00209-w

[11] Rodas-Osollo, J., Olmos-Sánchez, K., 2025. Phantom objectivity: Intersubjective knowledge in complex domains of informal structure. Philosophy and Realistic Reflection. 2(1), 1–24. DOI: https://doi.org/10.55121/prr.v2i1.366

[12] Whitehead, A.N., 1978. Process and Reality: An Essay in Cosmology. Free Press: New York, NY, USA.

[13] Kistler, M., 2025. Emergent Properties. In The Material Mind: Reduction and Emergence. University of Calgary Press: Calgary, AB, Canada. pp. 137–204.

[14] Wimsatt, W.C., 2007. Re-Engineering Philosophy for Limited Beings: Piecewise Approximations to Reality. Harvard University Press: Cambridge, MA, USA.

[15] Bailer-Jones, D., 2009. Scientific Models in Philosophy of Science. University of Pittsburgh Press: Pittsburgh, PA, USA.

[16] Santoni de Sio, F., van den Hoven, J., 2018. Meaningful human control over autonomous systems: A philosophical account. Frontiers in Robotics and AI. 5, 15. DOI: https://doi.org/10.3389/frobt.2018.00015

[17] Nyholm, S., 2023. Artificial Intelligence, Ethics of. In: Sellers, M., Kirste, S. (Eds.). Encyclopedia of the Philosophy of Law and Social Philosophy. Springer: Dordrecht, Netherlands. pp.1–8. DOI: https://doi.org/10.1007/978-94-007-6730-0_1093-1

[18] Clark, A., Chalmers, D., 1998. The extended mind. Analysis. 58(1), 7–19. DOI: https://doi.org/10.1093/analys/58.1.7

[19] Hutchins, E., 1995. Cognition in the Wild. MIT Press: Cambridge, MA, USA.

[20] Vallor, S., 2016. Technology and the Virtues: A Philosophical Guide to a Future Worth Wanting. Oxford University Press: New York, NY, USA.

[21] Anderson, P.W., 1972. More is different: Broken symmetry and the nature of the hierarchical structure of science. Science. 177(4047), 393–396. DOI: https://doi.org/10.1126/science.177.4047.393

[22] Riedl, C., Kim, Y.J., Gupta, P., et al., 2021. Quantifying collective intelligence in human groups. Proceedings of the National Academy of Sciences of the United States of America. 118(21), e2005737118. DOI: https://doi.org/10.1073/pnas.2005737118

[23] Collins, H., 2010. Tacit and Explicit Knowledge. University of Chicago Press: Chicago, IL, USA.

[24] Alston, W.P., 1989. Epistemic Justification: Essays in the Theory of Knowledge. Cornell University Press: Ithaca, NY, USA.

[25] Fodor, J.A., 1975. The Language of Thought. Thomas Y. Crowell Company, Inc.: New York, NY, USA.

[26] Putnam, H., 1960. Minds and Machines. In: Hook, S. (Ed.). Dimensions of Mind. New York University Press: New York, NY, USA. pp. 138–164.

[27] Tononi, G., 2004. An information integration theory of consciousness. BMC Neuroscience. 5(1), 42. DOI: https://doi.org/10.1186/1471-2202-5-42

[28] Topol, E., 2019. Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books: New York, NY, USA.

[29] WHO, 2021. COVID-19 Strategic Preparedness and Response Plan - Operational Planning Guideline. World Health Organization: Geneva, Switzerland. Available from: https://www.who.int/publications/i/item/WHO-WHE-2021.03

[30] Forsgren, N., Humble, J., Kim, G., 2018. Accelerate: The Science of Lean Software and DevOps: Building and Scaling High Performing Technology Organizations. IT Revolution Press: Portland, OR, USA.

[31] Liu, J., Zhang, H., Zou, Y., 2025. Understanding open source contributor profiles in popular machine learning libraries. ACM Transactions on Software Engineering and Methodology. DOI: https://doi.org/10.1145/3747347

[32] Dias, P.G.F., Silva, M.C., Rocha Filho, G.P., et al., 2021. Swarm robotics: A perspective on the latest reviewed concepts and applications. Sensors. 21(6), 2062. DOI: https://doi.org/10.3390/s21062062

[33] Cartwright, N., 1983. How the Laws of Physics Lie. Oxford University Press: Oxford, UK.

[34] Shannon, C.E., 1948. A mathematical theory of communication. Bell System Technical Journal. 27(3–4), 379–423, 623–656.

[35] Durkheim, É., 1982. The Rules of Sociological Method. Halls, W.D. (Trans.). Free Press: New York, NY, USA.

[36] Haynes, A.B., Weiser, T.G., Berry, W.R., et al., 2009. A surgical safety checklist to reduce morbidity and mortality in a global population. New England Journal of Medicine. 360(5), 491–499. DOI: https://doi.org/10.1056/NEJMsa0810119

[37] Squire, L.R., Dede, A.J.O., 2015. Conscious and unconscious memory systems. Cold Spring Harbor Perspectives in Biology. 7(3), a021667. DOI: https://doi.org/10.1101/cshperspect.a021667

[38] Bianco, K.M., Fuelscher, I., Lum, J.A.G., et al., 2024. Procedural learning is associated with microstructure of basal ganglia-cerebellar circuitry in children. Brain and Cognition. 180, 106204. DOI: https://doi.org/10.1016/j.bandc.2024.106204

[39] Cerullo, M.A., 2015. The problem with Phi: A critique of integrated information theory. PLOS Computational Biology. 11(9), e1004286. DOI: https://doi.org/10.1371/journal.pcbi.1004286

[40] Chalmers, D.J., 2006. Strong and weak emergence. In: Clayton, P., Davies, P. (Eds.). The Re-Emergence of Emergence. Oxford University Press: Oxford, UK. pp. 244–254.

[41] Zahavi, D., 2005. Subjectivity and Selfhood: Investigating the First-Person Perspective. MIT Press: Cambridge, MA, USA.

Downloads

Issue

Vol. 3 No. 1 (March 2026): In Progress

Section

Articles

License

Copyright (c) 2026 Jorge Rodas-Osollo, Dra Olmos

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.