Biography

Roberto Prevete (MSc in physics, PhD in Information Science) is an Assistant Professor of Computer Science at the Dept.of Electrical Engineering and Information Technologies (DIETI), University of Naples Federico II, Italy. Director of the laboratory for Computational Vision and Neural Networks (ViNe) at DIETI. His current research interests include computational models of brain mechanisms, machine learning and artificial neural networks and their applications.

Abstract

Open-ended learning robots: the interplay of epistemic and ethical issues

Distinctive ethical issues concerning learning robots arise from familiar limitations affecting our capability to predict exactly and explain their behavior. It is well-known that these epistemic limitations bear on the ethical problem of fairly ascribing retrospective responsibilities (for harmful behaviors of learning robots) as well as prospective responsibilities (for the decision to field some learning robots). By a comparative analysis of various machine learning methods – notably including non-incremental, standard on-line/incremental and open-ended learning – it is argued here that the epistemic predicaments generally affecting human observers of learning robots are significantly enhanced in open-ended learning. Indeed, in this latter case one has to develop predictive and explanatory tools without knowing a priori which categories and behaviors the robot has been continuously learning in its open-ended learning environment. Importantly, to tackle these difficulties we suggest some viable strategies in the context of neural network approaches, based on similarity measures to identify bounds on the input-output response distance. Moreover, this epistemological analysis is brought to bear on robot ethics, insofar as it enables one to identify in a principled way tasks that would be ethically problematic to let open-ended learning robots to perform.