Herbert Simon , the anti-philosopher
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
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Herbert Simon’s work presents a curious anomaly to the historian and philosopher trying to understand the development of classic Artiﬁcial Intelligence (AI). Simon was one of most inﬂuential ﬁgures in AI since its birth, and yet it is always with some diﬃculties that his work can be made to ﬁt within the received canon of AI’s development and goals. In fact, he diﬀered from every other ﬁgure in early AI on most counts: in terms of the recognized intellectual heritage of AI, of his own background and training, of the goals he set for his own AI work and the assessment criteria he accepted. I will argue that these diﬀerences provide important clues toward a reevaluation of the relationship between Artiﬁcial Intelligence and Herbert Simon’s work that may change our current understanding of both. On the one hand, classic Artiﬁcial Intelligence (or Complex Information Processing, as Simon preferred to call it for a number of years), provided the tool he needed to pursue a much broader research agenda that strove to encompass human beings in their cognitive, emotional, social, and political dimensions. On the other hand, AI’s curious status as the discipline that straggles the boundaries between engineering, science, and philosophy can be recast as the tool that allowed researchers to pursue philosophy’s old goals with an alternative methodology. From this perspective, Simon’s version of Artiﬁcial Intelligence becomes a full-ﬂedged form of ”anti-philosophy” as ambitious and broad-ranging as old-fashioned metaphysics and as revolutionary as the latter in the radical refashioning of its methodology. It follows that a philosophical assessment of AI, at in least in its Simonian incarnation, must be more farreaching than it is usually thought. At the methodological level, it must discuss whether AI’s invention of computer simulation as the tool that overcomes the a-priori/a-posteriori distinction by actually producing the behavior it wants to explain is really adequate to the job at hand..
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