人工知能と科学哲学

― 因果性をめぐって ―

抄録

    Recent arguments in philosophy of science concerning artificial intelligence seem to heavily concentrate on social or ethical issues, such as ‘Singularity' problem or harmonious coexistence with AI. But the meaningful relationship between philosophy of science and AI is not limited to that of this kind. The Bayesian network (BN) is one of the central issues in the research of AI, and this has a lot to do with traditional arguments in philosophy of science, since finding the single best definition of causality has been one of main themes in philosophy of science. In this paper, I will consider possible ways for philosophers to be deeply in touch with AI regarding ‘the methodology of BN', ‘the definition of causation', and ‘the elimination of causation'.