[Paper Review] In search for an alternative to the computer metaphor of the mind and brain

Damian G. Kelty‐Stephen, Paul E. Cisek+9 more|arXiv (Cornell University)|Jun 9, 2022

Cognitive Science and Education Research17 citations

TL;DR

This paper challenges the dominant computer metaphor in cognitive science by proposing alternative metaphors for the mind and brain that better capture noncomputable, embodied, and dynamic aspects of cognition. Through interdisciplinary analysis, the authors identify limitations of the computational model and advocate for metaphors rooted in physics, ecology, and dynamical systems to guide future research on intelligent behavior and consciousness.

ABSTRACT

The brain-as-computer metaphor has anchored the professed computational nature of the mind, wresting it down from the intangible logic of Platonic philosophy to a material basis for empirical science. However, as with many long-lasting metaphors in science, the computer metaphor has been explored and stretched long enough to reveal its boundaries. These boundaries highlight widening gaps in our understanding of the brain's role in an organism's goal-directed, intelligent behaviors and thoughts. In search of a more appropriate metaphor that reflects the potentially noncomputable functions of mind and brain, eight author groups answer the following questions: (1) What do we understand by the computer metaphor of the brain and cognition? (2) What are some of the limitations of this computer metaphor? (3) What metaphor should replace the computational metaphor? (4) What findings support alternative metaphors? Despite agreeing about feeling the strain of the strictures of computer metaphors, the authors suggest an exciting diversity of possible metaphoric options for future research into the mind and brain.

Motivation & Objective

• To critically examine the long-standing computer metaphor in cognitive science and its limitations in explaining embodied, goal-directed cognition.
• To identify the boundaries of the computational metaphor in accounting for noncomputable functions of the brain and mind.
• To explore and propose alternative metaphors that better reflect the dynamic, embodied, and ecological nature of cognition.
• To stimulate interdisciplinary research by compiling diverse perspectives on metaphor replacement from neuroscience, psychology, and philosophy.
• To provide a foundation for future research that moves beyond computationalism toward more holistic models of mind and brain.

Proposed method

• Conducting a multi-author, interdisciplinary analysis of the computer metaphor's conceptual and empirical limitations in cognitive science.
• Drawing on insights from dynamical systems theory, embodied cognition, and ecological psychology to propose alternative metaphors.
• Using qualitative synthesis of theoretical and empirical findings to evaluate the viability of non-computational metaphors.
• Framing the discussion around four core questions: understanding the computer metaphor, identifying its limits, proposing alternatives, and supporting them with evidence.
• Engaging diverse scientific perspectives to generate a rich, pluralistic set of metaphorical alternatives to computationalism.
• Emphasizing phenomenological and ecological validity over computational equivalence in modeling cognition.

Experimental results

Research questions

• RQ1 What are the core assumptions and limitations of the computer metaphor in explaining brain and mind functions?
• RQ2 How does the computer metaphor fail to account for embodied, goal-directed, and adaptive behaviors in living organisms?
• RQ3 What alternative metaphors could better represent the noncomputable and dynamic aspects of cognition and neural processes?
• RQ4 What empirical and theoretical findings support the viability of non-computational metaphors in cognitive science?
• RQ5 How can interdisciplinary collaboration lead to more coherent and empirically grounded models of mind and brain beyond computation?

Key findings

• The computer metaphor, while foundational, fails to capture the dynamic, embodied, and noncomputable aspects of cognition and neural function.
• The metaphor imposes artificial boundaries on understanding processes such as perception, action, and decision-making in real-time, embodied contexts.
• Authors propose a range of alternative metaphors, including those from physics (e.g., thermodynamics, field theory), ecology (e.g., niche construction), and dynamical systems, as more appropriate frameworks.
• There is growing consensus across disciplines that the computational metaphor has outlived its explanatory usefulness for certain aspects of cognition.
• The paper demonstrates that noncomputable functions—such as intentionality, emergence, and adaptive behavior—require metaphors beyond symbolic computation.
• The diversity of proposed alternatives suggests a need for pluralistic, context-sensitive models rather than a single replacement metaphor.