Massive modularity of mind
Explanation
The hypothesis of massive modularity of mind arises in evolutionary psychology (Tooby, Cosmides, Pinker) and builds on previous ideas of Jerry Fodor (The Modularity of Mind, 1983). The thesis is that the mind is not a general-purpose device that learns anything, but a collection of specialised cognitive modules, each adapted to solve specific ecological problems faced by our ancestors during human evolution: detecting predators, recognising faces, negotiating alliances, acquiring language, choosing a mate, distinguishing kin.
Fodor distinguished modules with certain properties: domain specificity, mandatoriness, informational encapsulation (they do not share information with other modules), speed, shallow output, dedicated neural architecture. Massive modularity generalises this: most of human cognition, not just the peripheral, would be modularly organised. There would be modules for agency detection, theory of mind, intuitive psychology, intuitive physics, intuitive biology, cheater detection in social exchanges, etc.
The evidence rests on several sources: neurological dissociations (patients who lose a specific capacity but retain others), evolutionary differences (uniquely human capacities vs those shared with other primates), developmental studies (babies show specific expectations for objects, persons, numbers), cognitive experiments revealing differential processing (Wason's selection task works better with social than with abstract content, according to Cosmides).
For consciousness, massive modularity has interesting consequences. If the mind is a mosaic of mostly automatic and encapsulated modules, unified consciousness would be a useful illusion: an interface that integrates outputs of multiple underlying modules without accessing their internal workings. This fits with theories such as the global workspace (consciousness is the space where modular outputs become globally available) and with the idea that the self is a unifying narrative built upon distributed processes.
Modularity also explains why we are good at certain things intuitively (detecting faces, intentions, social cues) and bad at others (probability, formal logic, statistical thinking) despite having the same brain. Modules evolved for specific problems; when we apply them to non-ancestral domains (abstract mathematics, statistics, global economics), we fail systematically. Training System 2 is, in part, learning to correct the outputs of modules adapted to other problems.
The criticisms are serious. The human mind shows enormous general flexibility, learning of new domains, transfer between areas. Strict modularity has difficulty explaining that generality. Moreover, the specification of which modules exist is often done post hoc, without clear criteria. The current debate centres on whether there is strict massive modularity or partial modularity within a more flexible framework. Despite these debates, the evolutionary perspective has changed how human cognition is thought about.
Strengths
- Explains perceptual encapsulation and speed of automatic processes.
- Compatible with the neuroscience of specialised areas.
- Productive framework for evolutionary psychology.
- Predicts specific patterns of brain damage observed.
Main critiques
- Brain plasticity questions strict modularity.
- Evolutionary overextension generates just-so adaptationism.
- Difficult to delimit criteria of modularity.
- Tension with the holism of high-level cognition.