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Fair navigation planning: a resource for characterizing and designing fairness in mobile robots

Research output: Contribution to journalArticle

Martim Brandao, Marina Jirotka, Helena Webb, Paul Luff

Original languageEnglish
Article number103259
Number of pages20
JournalARTIFICIAL INTELLIGENCE
Volume282
Issue numberMay 2020
Early online date20 Mar 2020
DOIs
Publication statusPublished - 1 May 2020

King's Authors

Abstract

In recent years, the development and deployment of autonomous systems such as mobile robots have been increasingly common. Investigating and implementing ethical considerations such as fairness in autonomous systems is an important problem that is receiving increased attention, both because of recent findings of their potential undesired impacts and a related surge in ethical principles and guidelines. In this paper we take a new approach to considering fairness in the design of autonomous systems: we examine fairness by obtaining formal definitions, applying them to a system, and simulating system deployment in order to anticipate challenges. We undertake this analysis in the context of the particular technical problem of robot navigation. We start by showing that there is a fairness dimension to robot navigation, and we then collect and translate several formal definitions of distributive justice into the navigation planning domain. We use a walkthrough example of a rescue robot to bring out design choices and issues that arise during the development of a fair system. We discuss indirect discrimination, fairness-efficiency trade-offs, the existence of counter-productive fairness definitions, privacy and other issues. Finally, we elaborate on important aspects of a research agenda and reflect on the adequacy of our methodology in this paper as a general approach to responsible innovation in autonomous systems.

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