Abstract
We propose to address the question whether the fields of machine learning and pattern recognition have achieved the level of maturity in the sense suggested by Thomas Kuhn. This is inextricably tied to the notion of a paradigm, one of the cornerstones of twentieth-century philosophy of science, which however is notoriously ambiguous, and we shall argue that the answer to our inquiry does depend on the specific interpretation chosen. Here we shall focus on a “broad” interpretation of the term, which implies a profound commitment to a set of beliefs and values. Our motivating question can in fact be seen simply as an excuse to analyze the current status of the machine learning field using Kuhn’s image of scientific progress, and to discuss the philosophical underpinnings of much of contemporary machine learning research.
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Pelillo, M., Scantamburlo, T. (2013). How Mature Is the Field of Machine Learning?. In: Baldoni, M., Baroglio, C., Boella, G., Micalizio, R. (eds) AI*IA 2013: Advances in Artificial Intelligence. AI*IA 2013. Lecture Notes in Computer Science(), vol 8249. Springer, Cham. https://doi.org/10.1007/978-3-319-03524-6_11
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