Turing Machines and Intentionality: A Search for the Essence of AI

The history of artificial intelligence (AI) is characterized by the difficulty to provide a concise definition for what AI actually entails, and so at different times it has stood for different priorities and motivations. This work is predicated on the postulation that running through the history of AI is a common thread—an essence—which characterizes the different approaches taken to defining AI over the course of its history, and the main goal of this work is to elaborate on what that common thread is and why. This work is primarily based on the ideas and works of Daniel Dennett, Douglas Hofstadter, Alan Turing and John Searle, and expands upon them in an attempt to provide a cohesive picture of AI as a pursuit to create intentional systems, where “intentional system” is defined as a system whose behavior is effectively predictable by attributing intentional states to it, such as beliefs, desires, and intentions. It is argued that intentional states are necessarily attributed rather than innate, and the utility of this attribution comes across through use of intentional vocabulary in descriptions of the systems that are treated as intentional. In addition, various problems of philosophy of mind which relate to the question “can the human mind be simulated by a machine?” are discussed. These include, among other things, the implications of the Church–Turing Thesis on computability of the mind, Searle’s Chinese room argument, and the philosophical zombie argument. Discussions on these topics act as a narrative thread to help establish the main thesis of this work in a logical and cohesive manner