Legal Detection of AI Products Based on Formal Argumentation and Legal Ontology

• URL: http://arxiv.org/abs/2209.03070v1
• Date: Wed, 7 Sep 2022 11:08:08 GMT
• Title: Legal Detection of AI Products Based on Formal Argumentation and Legal Ontology
• Authors: Zhe Yu and Yiwei Lu
• Abstract summary: Current paper presents a structured argumentation framework for reasoning in legal contexts. We show that using this combined theory of formal argumentation and DL-based legal logic, acceptable assertions can be obtained.
• Score: 4.286330841427189
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Ontology is a popular method for knowledge representation in different domains, including the legal domain, and description logics (DL) is commonly used as its description language. To handle reasoning based on inconsistent DL-based legal ontologies, the current paper presents a structured argumentation framework particularly for reasoning in legal contexts on the basis of ASPIC+, and translates the legal ontology into formulas and rules of an argumentation theory. With a particular focus on the design of autonomous vehicles from the perspective of legal AI, we show that using this combined theory of formal argumentation and DL-based legal ontology, acceptable assertions can be obtained based on inconsistent ontologies, and the traditional reasoning tasks of DL ontologies can also be accomplished. In addition, a formal definition of explanations for the result of reasoning is presented.

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