John Searle's Chinese Room argument raises many important questions for traditional, symbolic AI, which none of the standard replies adequately refutes. Even so, the argument does not necessarily imply that machines will never be truly able to think. Nevertheless, we must be willing to make some changes to the foundations of traditional AI in order to answer Searle's questions satisfactorily. This paper argues that if we constrain the sorts of architectures we consider as appropriate models of the mind other than the brain, such that they resemble the physical structure of the brain more closely, we gain several desirable properties. It is possible that these properties may help us solve the hard problems of inten tionality, qualia and consciousness that Computational Functionalism has so far not been able to address in satisfactory ways.

PDF, PS

Technical Report, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI94-222.

@TechReport{law:synthetic94, title={Searle, Subsymbolic Functionalism And Synthetic Intelligence}, author={Diane Law}, address={Austin, TX}, institution={Department of Computer Sciences, The University of Texas at Austin}, pages={16 pages}, note={Technical Report AI94-222}, url="http://www.cs.utexas.edu/users/ai-lab?law:synthetic", year={1994} }