Levels of abstraction and the Turing test

Purpose - An important lesson that philosophy can learn from the Turing test and computer science more generally concerns the careful use of the method of levels of abstraction (LoAs). The purpose of this paper is to summarize the method and apply it to the paper, modelling and analysis of phenomenological and conceptual systems showing its principal features and main advantages. Design/methodology/approach - The constituents of the method are observables, collected together and moderated by predicates restraining their behaviour. The resulting collection of sets of observables is called a gradient of abstractions (GoAs) and it formalises the minimum consistency conditions that the chosen abstractions must satisfy. Two useful kinds of GoA - disjoint and nested - are identified. It is then argued that in any discrete (as distinct from analogue) domain of discourse, a complex phenomenon may be explicated in terms of simple approximations organised together in a GoAs. Thus, the method replaces, for discrete disciplines, the differential and integral calculus, which form the basis for understanding the complex analogue phenomena of science and engineering. Findings - The result formalises an approach that is rather common in computer science hut has hitherto found little application in philosophy. So the philosophical value of the method is demonstrated by showing how making the LoA of discourse explicit can be fruitful for phenomenological and conceptual analysis. To this end, the method is applied to the Turing test, the concept of agenthood, the definition of emergence, the notion of artificial life, quantum observation and decidable observation. Originality/value - This paper applies the method of abstraction to the paper, modelling and analysis of phenomenological and conceptual systems showing its principal features and main advantages. It is hoped that this treatment will promote the use of the method in certain areas of the humanities and especially in philosophy.