Acm Sigcas Computers and Society 45 (3):218-224 (2015)

Teresa Scantamburlo
University of Venice
In this paper we would like to undertake a critical examination of machine learning in the context of data revolution. Starting from the existing literature, which has in fact highlighted potential risks both at the epistemological and ethical level, we will try to suggest the main limitations of an intensive application of machine learning to decision making. Our discussion we will make direct reference to Satosi Watanabe, whose contribution springs from a genuine reflection on machine learning research and rises many philosophical questions. In addition, we will consider the difficulties of machine learning by exploiting the classical distinction between "apprehension" and "judgement" recalled even more recently by some studies dealing with the emergence of complexity in human cognition. Rather than being an exhaustive analysis, our investigation is a tentative step towards a better understanding of machine learning and its potential implications on individual and social life. Our main contribution is to try to introduce in the philosophical debate some new considerations which come from the inner core of machine learning and from the traditional notions of philosophical logic.
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Reprint years 2015, 2016
DOI 10.1145/2874239.2874270
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