Ontological challenges to cohabitation with self-taught robots

Article type: Research Article

Authors: Borgo, Stefano^{; *}

Affiliations: Laboratory for Applied Ontology, ISTC, Consiglio Nazionale delle Ricerche, Italy. E-mail: [email protected]

Correspondence: [*] Corresponding author. E-mail: [email protected].

Abstract: When you meet a delivery robot in a narrow street it stops to let you pass. It was built to give you precedence. What happens if you run into a robot that was not trained by or for humans? The existence in our environment of robots which do not abide by human behavioral rules and social systems might sound odd, but is a case we may encounter in the future. In this paper, self-taught robots are artificial embodied agents that, thanks for instance to AI learning techniques, manage to survive in the environment without embracing behavioral or judgment rules given and used by humans. The paper argues that our ontological systems are not suitable to understand and cope with artificial agents. The arguments are speculative rather than empirical, and the goal is to drive attention to new ontological challenges.

Keywords: Applied ontology, robotics, interaction, heterogeneous agents, multi-agent systems, artificial intelligence

DOI: 10.3233/SW-190385

Journal: Semantic Web, vol. 11, no. 1, pp. 161-167, 2020