Behind artificial intelligence: an analysis of the epistemological bases of machine learning

Abstract

This article aims to critically analyze the epistemological foundations of artificial intelligence (AI). By examining works that explain how this technology works, it is understood that its epistemological basis is made up of the inductive method and statistics based on a mathematization of reality. It is these elements that allow machines to learn by recognizing patterns and to make predictions and provide answers. However, these foundations have limitations and problems that have been discussed by philosophers throughout history. In this article we will present how induction and mathematization function as the epistemological basis of artificial intelligence and how some of the limitations of this technology can be explained through the weaknesses of the methods that support it.