Basu, S. orcid.org/0000-0001-5863-854X, Omotubora, A. and Fox, C. (2024) Autonomous delivery robots: a legal framework for infliction of game-theoretic small penalties on pedestrians. Law, Innovation and Technology, 16 (2). pp. 631-662. ISSN 1757-9961
Abstract
Autonomous delivery robots (ADRs) must share and negotiate for public and private space with pedestrians. Game theory shows that this requires making credible threats of inflicting at least small harms onto members of the public, which requires new legal justification. To this end, we argue that ADRs could be considered as pedestrians under existing law. We propose ‘robot self-defence’ and right to property as the legal basis for inflicting the required ‘small penalties.’ We examine the liability framework when an ADR actually causes a collision either deliberately through actualising a credible collision threat or accidentally via errors in controlling intended non-contact threats. We explore challenges around privacy and data protection where the ADR collects and uses data to model and predict interactions. Together, this provides a framework for legal operation of ADRs, including the ability to inflict small harm onto members of the public when necessary in negotiations for space.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Autonomous delivery robots, pedestrians, game theory, small penalties |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Education, Social Sciences and Law (Leeds) > School of Law (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 15 May 2024 12:51 |
Last Modified: | 04 Dec 2024 15:40 |
Status: | Published |
Publisher: | Taylor & Francis |
Identification Number: | 10.1080/17579961.2024.2392940 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:212530 |