Designing normative theories for ethical and legal reasoning: LogiKEy framework, methodology, and tool support

作者:

摘要

A framework and methodology—termed LogiKEy—for the design and engineering of ethical reasoners, normative theories and deontic logics is presented. The overall motivation is the development of suitable means for the control and governance of intelligent autonomous systems. LogiKEy's unifying formal framework is based on semantical embeddings of deontic logics, logic combinations and ethico-legal domain theories in expressive classic higher-order logic (HOL). This meta-logical approach enables the provision of powerful tool support in LogiKEy: off-the-shelf theorem provers and model finders for HOL are assisting the LogiKEy designer of ethical intelligent agents to flexibly experiment with underlying logics and their combinations, with ethico-legal domain theories, and with concrete examples—all at the same time. Continuous improvements of these off-the-shelf provers, without further ado, leverage the reasoning performance in LogiKEy. Case studies, in which the LogiKEy framework and methodology has been applied and tested, give evidence that HOL's undecidability often does not hinder efficient experimentation.

论文关键词:Trustworthy and responsible AI,Knowledge representation and reasoning,Automated theorem proving,Model finding,Normative reasoning,Normative systems,Ethical issues,Semantical embedding,Higher-order logic

论文评审过程:Received 20 March 2019, Revised 20 May 2020, Accepted 1 June 2020, Available online 12 June 2020, Version of Record 20 June 2020.

论文官网地址:https://doi.org/10.1016/j.artint.2020.103348