Algorithm, Machine Learning and Artificial Intelligence

Abstract

We discuss the concepts of algorithm, machine learning and artificial intelligence. We start by noting that different definitions of algorithm may serve different epistemic purposes, and by highlighting the specificities of computer science algorithms together with a high-level overview of their different types. We continue by discussing machine learning as a discipline and commenting on its algorithms, with a focus on artificial neural networks due to their role in the deep learning revolution. We discuss the epistemic and ethical challenges arising from the widely spread use of machine learning algorithms in the applications. Then, we discuss the artifacts of the artificial intelligence domain, clarifying their relation with machine learning algorithms. Finally, we provide the reader with comments on the emergence of the “trustworthy AI” paradigm, highlighting some of the theoretical challenges affecting the discussions on trust in human-AI interactions.

Keywords: algorithm, machine learning, artificial intelligence, explainable artificial intelligence, ethics of artificial intelligence, trust