Journal article
Fair navigation planning: A resource for characterizing and designing fairness in mobile robots
- 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.
 
- Publication status:
 - Published
 
- Peer review status:
 - Peer reviewed
 
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- Files:
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                        (Preview, Accepted manuscript, 1.6MB, Terms of use)
 
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- Publisher copy:
 - 10.1016/j.artint.2020.103259
 
Authors
- Publisher:
 - Elsevier
 - Journal:
 - Artificial Intelligence More from this journal
 - Volume:
 - 282
 - Article number:
 - 103259
 - Publication date:
 - 2020-03-18
 - Acceptance date:
 - 2020-03-05
 - DOI:
 - EISSN:
 - 
                    1872-7921
 - ISSN:
 - 
                    0004-3702
 
- Language:
 - 
                    English
 - Keywords:
 - Pubs id:
 - 
                  1091447
 - Local pid:
 - 
                    pubs:1091447
 - Deposit date:
 - 
                    2020-03-06
 
Terms of use
- Copyright holder:
 - Elsevier B.V.
 - Copyright date:
 - 2020
 - Rights statement:
 - © 2020 Elsevier B.V.
 - Notes:
 - This is the accepted manuscript version of the article. The final version is available online from Elsevier at https://doi.org/10.1016/j.artint.2020.103259
 
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