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dc.contributor.authorIACCA, Giovanni
dc.contributor.authorLAGIOIA, Francesca
dc.contributor.authorLOREGGIA, Andrea
dc.contributor.authorSARTOR, Giovanni
dc.date.accessioned2024-02-28T10:25:51Z
dc.date.available2024-02-28T10:25:51Z
dc.date.issued2020
dc.identifier.citationSerena VILLATA, Jakub HARASTA and Petr KREMEN (eds), Legal knowledge and information systems : JURIX 2020 The thirty-third Annual Conference, Brno, Czech Republic, December 9-11, 2020, Amsterdam : IOS Press, 2020, Frontiers in artificial intelligence and applications ; 334, pp. 103-112en
dc.identifier.isbn9781643681504
dc.identifier.isbn9781643681511
dc.identifier.issn0922-6389
dc.identifier.issn1879-8314
dc.identifier.urihttps://hdl.handle.net/1814/76628
dc.description.abstractAs Autonomous vehicles (AVs) are entering shared roads, the challenge of designing and implementing a completely autonomous vehicle is still open. Aside from technological issues regarding how to manage the complexity of the environment, AVs raise difficult legal issues and ethical dilemmas, especially in unavoidable accident scenarios. In this context, a vast speculation depicting moral dilemmas has developed in recent years. A new perspective was proposed: an “Ethical Knob” (EK), enabling passengers to ethically customise their AVs, namely, to choose between different settings corresponding to different moral approaches or principles. In this contribution we explore how an AV can automatically learn to determine the value of its “Ethical Knob” in order to achieve a trade-off between the ethical preferences of passengers and social values, learning from experienced instances of collision. To this end, we propose a novel approach based on a genetic algorithm to optimize a population of neural networks. We report a detailed description of simulation experiments as well as possible applications.en
dc.description.sponsorshipFrancesca Lagioia, Andrea Loreggia and Giovanni Sartor have been supported by the H2020 ERC Project “CompuLaw” (G.A. 833647).en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherIOS Pressen
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/833647/EUen
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.titleA genetic approach to the Ethical Knoben
dc.typeContribution to booken
dc.identifier.doi10.3233/FAIA200854
dc.rights.licenseAttribution-NonCommercial 4.0 International*


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Except where otherwise noted, this item's license is described as Attribution-NonCommercial 4.0 International