Understanding a Robot's Guiding Ethical Principles via Automatically Generated Explanations

TL;DR

This paper explores how contrastive and non-contrastive explanations can help humans understand the ethical principles guiding robot decision-making, enhancing transparency and trust.

Contribution

It introduces a method for automatically generating explanations based on an ethical framework, improving human understanding of robot ethics.

Findings

Generated explanations aid human comprehension of robot ethics

User study shows explanations improve trust in robot decisions

Contrastive explanations are particularly effective

Abstract

The continued development of robots has enabled their wider usage in human surroundings. Robots are more trusted to make increasingly important decisions with potentially critical outcomes. Therefore, it is essential to consider the ethical principles under which robots operate. In this paper we examine how contrastive and non-contrastive explanations can be used in understanding the ethics of robot action plans. We build upon an existing ethical framework to allow users to make suggestions about plans and receive automatically generated contrastive explanations. Results of a user study indicate that the generated explanations help humans to understand the ethical principles that underlie a robot's plan.