Fodor and Pylyshyn's Systematicity Challenge Still Stands
The recent successes of neural networks producing human-like language have caused significant stir in cognitive science, with many researchers arguing that classical puzzles about human cognition and challenges to artificial intelligence are being solved by neural networks. A notable case is the argument from systematicity due to Jerry Fodor and Zenon Pylyshyn, argues that humans display systematic biconditional dependencies. For example, someone can understand the sentence "John saw Mary" just in case that they understand the sentence "Mary saw John." Symbolic systems explain this systematicity of language and thought, while neural networks offer no immediate explanation. Several recent ...
| Authors | Michael Goodale, Salvador Mascarenhas |
|---|---|
| Primary category | cs.CL |
| Published | 12 June 2026 |
| Last updated at source | 12 June 2026 |
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