A Principles-based Ethics Assurance Argument Pattern for AI and Autonomous Systems
This work addresses the need for structured ethical justification in AI systems for engineers, developers, and regulators, but it is incremental as it builds on existing assurance case methods.
The paper tackles the problem of ensuring ethical acceptability in AI and autonomous systems by developing a principles-based ethics assurance argument pattern called PRAISE, which integrates assurance case methodology with ethical principles like justice and beneficence, and demonstrates its application to a hypothetical autonomous robo-taxi service.
An assurance case is a structured argument, typically produced by safety engineers, to communicate confidence that a critical or complex system, such as an aircraft, will be acceptably safe within its intended context. Assurance cases often inform third party approval of a system. One emerging proposition within the trustworthy AI and autonomous systems (AI/AS) research community is to use assurance cases to instil justified confidence that specific AI/AS will be ethically acceptable when operational in well-defined contexts. This paper substantially develops the proposition and makes it concrete. It brings together the assurance case methodology with a set of ethical principles to structure a principles-based ethics assurance argument pattern. The principles are justice, beneficence, non-maleficence, and respect for human autonomy, with the principle of transparency playing a supporting role. The argument pattern, shortened to the acronym PRAISE, is described. The objective of the proposed PRAISE argument pattern is to provide a reusable template for individual ethics assurance cases, by which engineers, developers, operators, or regulators could justify, communicate, or challenge a claim about the overall ethical acceptability of the use of a specific AI/AS in a given socio-technical context. We apply the pattern to the hypothetical use case of an autonomous robo-taxi service in a city centre.