A Comparative Critique of Reductive Physicalism: Putnam’s Multiple Realizability vs. Dennett’s Evolutionary Functionalism

Document Type : Original Article

Author
Zeynab Arab Mistani
Ph.D. Graduate, Department of Philosoph, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran.
10.22034/zehn.2025.2062484.2121
Abstract
This study presents a comparative critique of reductive physicalism by analyzing Hilary Putnam’s multiple realizability and Daniel Dennett’s evolutionary functionalism, examining the limitations of reducing mental states to specific neural processes. Employing conceptual and textual analysis of key works by Putnam and Dennett, the research utilizes logical reasoning, textual interpretation, and critical synthesis to evaluate their critiques of type-identity theory and advocacy for functionalism. Findings demonstrate that Putnam’s multiple realizability challenges reductive physicalism by emphasizing the potential for mental states, such as pain, to be realized across diverse physical substrates, while Dennett’s multilevel framework integrates evolutionary, computational, and behavioral processes to contest reductive approaches. The study proposes an innovative framework, “multiple-realizability-evolutionary functionalism,” which combines Putnam’s semantic flexibility with Dennett’s evolutionary dynamics, redefining the mind-body relationship as an interdisciplinary model. Supported by empirical evidence, such as neural plasticity, reinforcement learning algorithms, and brain-computer interfaces, this framework offers applications in cognitive science, artificial intelligence, and technology ethics. Future research should investigate the explanatory mechanisms of mental states across diverse substrates and the ethical implications of adaptive AI systems.
Keywords
Reductive Physicalism
Multiple-Realizability-Evolutionary Functionalism
Cognitive Science
Artificial Intelligence
Neural Plasticity
Technology Ethics

Subjects

1.    اکبریان، رضا (1385). «نفس‌شناسی ابن‌سینا»، اطلاعات حکمت و فلسفه، 7 (1)، صص 190- 102.
2.    صالحی نجف‌آبادی، ملیحه (1392). «جوهریت نفس از دیدگاه ابن‌سینا و ملاصدرا»، تاریخ فلسفه، 4 (2)، صص 107- 124.
3.    صمدیه، مریم؛ فاضل‌زاده، فاطمه (1401). «تبیین ماهیت حالات ذهنی در آراء و اندیشه‌های هیلاری پاتنم، از رد فیزیکالیسم تا نقد کارکردگرایی»، فلسفه غرب، 1(3)، صص 21- 36.
4.    Bechtel, W., & Mundale, J. (1999). “Multiple realizability revisited: Linking cognitive and neural states”, Philosophy of Science, 66(2), PP. 175–207.
5.    Block, N. (1978). Troubles with functionalism. In C. W. Savage (Ed.), Perception and cognition: Issues in the foundations of psychology, University of Minnesota Press, pp. 261–325.
6.    Bostrom, N. (2014). Superintelligence: Paths, dangers, strategies, Oxford University Press.
7.    Burge, T. (2010). Origins of objectivity, Oxford University Press.
8.    Cao, R. (2022). “Multiple realizability and the spirit of functionalism”, Synthese, 200(6), Article 506.
9.    Chalmers, D. J. (1996). The conscious mind: In search of a fundamental theory, Oxford University Press.
10. Clark, A. (2013). “Whatever next? Predictive brains, situated agents, and the future of cognitive science”, Behavioral and Brain Sciences, 36(3), PP. 181-204.
11.  Crook, R. J., Hanlon, R. T., & Walters, E. T. (2021). “Pain and analgesia in cephalopods”, ILAR Journal, 62(1-2), PP. 1–11.
12.  Davidson, D. (1970). Mental events. In Essays on actions and events, Oxford University Press, pp. 207–224.
13.  Dennett, D. C. (1987). The intentional stance, MIT Press.
14.  Dennett, D. C. (1991). Consciousness explained, Little, Brown and Company.
15.  Dennett, D. C. (1995). Darwin’s dangerous idea: Evolution and the meanings of life, Simon & Schuster.
16.  Fodor, J. A. (1981). Representations: Philosophical essays on the foundations of cognitive science, MIT Press.
17.  Friston, K. J., Parr, T., & de Vries, B. (2017). The graphical brain: Belief propagation and active inference, Network Neuroscience.
18.  Fodor, J. A. (2000). The mind doesn’t work that way: The scope and limits of computational psychology, MIT Press.
19.  Hacking, I. (1999). The social construction of what?, Harvard University Press.
20.  Hyde, D. (2023). “Surgical robotics and artificial intelligence: Ethical challenges and opportunities”, Journal of Medical Ethics and Technology, 8(2), PP. 123–135.
21.  Kandel, E. R. (2001). “The molecular biology of memory storage: A dialogue between genes and synapses”. Science, 294(5544), PP. 1030–1038.
22.  Kim, J. (2005). Physicalism, or something near enough, Princeton University Press.
23.  Lebedev, M. A., & Nicolelis, M. A. L. (2017). “Brain-machine interfaces: From basic science to neuroprostheses and neurorehabilitation”, Physiological Reviews, 97(2), PP. 767–837.
24.  LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), PP. 436–444.
25.  LeDoux, J. E. (2012). “Rethinking the emotional brain”, Neuron, 73(4), PP. 653–676.
26.  Lewis, D. (1980). Mad pain and Martian pain. In N. Block (Ed.), Readings in philosophy of psychology, Vol. 1, Harvard University Press, pp. 216–222.
27.  Maiolino, P., Maggiali, M., Cannata, G., Metta, G., & Natale, L. (2013). “A flexible and robust large-scale capacitive tactile system for robots”. IEEE Sensors Journal, 13(10), PP. 3910–3917.
28.  Markram, H. (2006). “The Blue Brain Project”, Nature Reviews Neuroscience, 7(2), 153–160.
29.  Marr, D. (1982). Vision: A computational investigation into the human representation and processing of visual information. W.H. Freeman.
30.  McGrath, S. W., & Russin, J. (2024). Multiple realizability and the rise of deep learning. arXiv preprint arXiv:2405.13231.
31.  Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., ... Hassabis, D. (2015). “Human-level control through deep reinforcement learning”. Nature, 518(7540), PP. 529–533.
32.  Putnam, H. (1967). “The nature of mental states. In W. H. Capitan & D. D. errill (Eds.)”, Art, mind, and religion, University of Pittsburgh Press, PP. 37-48.
33.  Putnam, H. (1981). Reason, truth, and history, Cambridge University Press.
34.  Pandey, A. K., & Gelin, R. (2018). “A mass-produced sociable humanoid robot: Pepper, the first machine of its kind”, IEEE Robotics & Automation Magazine, 25(3), PP. 40–48.
35.  Raibert, M., Blankespoor, K., Nelson, G., & Playter, R. (2021). “BigDog, Spot, and the future of legged robots”, Annual Review of Control, Robotics, and Autonomous Systems, 4, PP. 43–67.
36.  Searle, J. R. (1992). The rediscovery of the mind, MIT Press.
37.  Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., van den Driessche, G., ... Hassabis, D. (2016). “Mastering the game of Go with deep neural networks and tree search”, Nature, 529(7587), PP. 484–489.
38.  Smart, J. J. C. (1959). “Sensations and brain processes”, The Philosophical Review, 68(2), PP. 141–156.
39.  Sutton, R. S., & Barto, A. G. (2018). Reinforcement learning: An introduction (2nd ed.), MIT Press.
40.  Yuste, R., Goering, S., Arcas, B. A. Y., Bi, G., Carmena, J. M., Carter, A., ... Wolpaw, J. (2017). “Four ethical priorities for neurotechnologies and AI”, Nature, 551(7679), 159–163.