On the current paradigm in artificial intelligence

Issue title: ECAI 2012 Turing and Anniversary Track

Article type: Research Article

Authors: Cristianini, Nello

Affiliations: Intelligent Systems Laboratory, University of Bristol, Bristol, UK. E-mail: [email protected]

Abstract: The field of Artificial Intelligence (AI) has undergone many transformations, most recently the emergence of data-driven approaches centred on machine learning technology. The present article examines that paradigm shift by using the conceptual tools developed by Thomas Kuhn, and by analysing the contents of the longest running conference series in the field. A paradigm shift occurs when a new set of assumptions and values replaces the previous one within a given scientific community. These are often conveyed implicitly, by the choice of success stories that exemplify and define what a given field of research is about, demonstrating what kind of questions and answers are appropriate. The replacement of these exemplar stories corresponds to a shift in goals, methods, and expectations. We discuss the most recent such transition in the field of Artificial Intelligence, as well as commenting on some earlier ones.

Keywords: Philosophy of science, history of science, statistical artificial intelligence, data

DOI: 10.3233/AIC-130582

Journal: AI Communications, vol. 27, no. 1, pp. 37-43, 2014