The Chinese Room Argument: An Exercise in Computational Philosophy of Mind
Ajit Narayanan
Palgrave Macmillan UK eBooks 1991 DOI: 10.1007/978-1-349-21232-3_12 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Topics | Philosophy of mind |
| Key points | Argues that Searle's criticisms of 'strong' artificial intelligence restate all five of the objections Turing himself raised to his reformulation of 'Can machines think?' - the Arguments from Informality of Behaviour, Consciousness, and Continuity in the Nervous System, the Mathematical Objection, and 'Lady Lovelace's Objection' - and proposes to evaluate Searle's views critically within the developing field the authors call 'Computational Philosophy of Mind'. |
Abstract
By ‘Computational Philosophy of Mind’ we mean the overlap area between ‘artificial intelligence’ (AI) and philosophy of mind. This overlap area is attracting increasing interest from a number of philosophers and AI researchers. The origins of the overlap area can be traced back to Turing’s seminal paper in 1950, 1 and to five of the nine objections that Turing himself raised to his own reformulation of the question, ‘Can machines think?’ The five objections are: ‘The Argument from Informality of Behaviour’, ‘The Argument from Consciousness’, ‘The Argument from Continuity in the Nervous System’, ‘The Mathematical Objection’, and ‘Lady Lovelace’s Objection’. Turing’s reformulation of the question, called the ‘Imitation Game’, and the various objections he envisages, are well documented, and we shall not deal with them here. The important point is that Searle has recently expressed criticisms of artificial intelligence (the ‘strong’ variety) which embody all five of these objections, and his criticism can therefore be regarded as modern expressions of these objections. Our aim is to evaluate critically Searle’s views and put them in the context of a developing area of philosophy. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.