@inproceedings{06209a8ac74d415e98be996dc369ad10,
title = "An Argumentation and Ontology Based Legal Support System for AI Vehicle Design",
abstract = "As AI products continue to evolve, increasingly legal problems are emerging for the engineers that design them. Current laws are often ambiguous, inconsistent or undefined when it comes to technologies that make use of AI. Engineers would benefit from decision support tools that provide engineer's with legal advice and guidance on their design decisions. This research aims at exploring a new representation of legal ontology by importing argumentation theory and constructing a trustworthy legal decision system. While the ideas are generally applicable to AI products, our initial focus has been on Autonomous Vehicles (AVs).",
keywords = "Argumentation theory, Autonomous vehicle, Explainable AI, Legal detection, Legal ontology",
author = "Yiwei Lu and Zhe Yu and Yuhui Lin and Burkhard Schafer and Andrew Ireland and Lachlan Urquhart",
note = "Funding Information: 1Work supported by UKRI Research Node on Trustworthy Autonomous Systems Governance and Regulation (EP/V026607/1, 2020-2024). 2For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission. 3Corresponding Author. Publisher Copyright: {\textcopyright} 2022 The authors and IOS Press.; 35th International Conference on Legal Knowledge and Information Systems 2022, JURIX 2022 ; Conference date: 14-12-2022 Through 16-12-2022",
year = "2022",
month = dec,
day = "5",
doi = "10.3233/FAIA220469",
language = "English",
isbn = "9781643683645",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press",
pages = "213--218",
editor = "Enrico Francesconi and Georg Borges and Christoph Sorge",
booktitle = "Legal Knowledge and Information Systems",
address = "Netherlands",
}