Organising AI for safety: Identifying structural vulnerabilities to guide the design of AI-enhanced socio-technical systems

Artificial intelligence is increasingly being integrated into socio-technical systems. Existing design principles for ethical, safe and trustworthy AI tend to be highly abstract and focus on AI systems in isolation. They have rarely considered the adverse effects on safety that may emerge from interactions between AI and other technical components. Organisational theories of safety take such emergent outcomes of interactions between entities in socio-technical systems into account. They offer guidance on how to identify structural vulnerabilities in socio-technical systems enhanced by AI, and how to organise the design and operation of such systems for safety. In this paper, which is the result of a collaboration between sociologists and computer scientists (AI consultants), we conduct an analysis that can support the process of designing AI-enhanced autonomous systems in order to avoid structural vulnerabilities. It builds on organisational theories of safety and derives five key descriptors from them, the examination of which can guide the design of AI-enhanced systems. We demonstrate the utility of the descriptors by applying them to proposals for AI-enhanced critical functions in advanced microgrids. We discuss these proposals from the research literature on microgrids and review their effects on structural vulnerabilities. We then explore the implications that go beyond the example of advanced microgrids and propose steps for reviewing and reflecting on structural vulnerabilities that AI controllers may introduce into socio-technical systems. • Novel sociotechnical perspective on safety design principles of AI. • Systematises the social actors responsible for the safe design of autonomous systems. • Applies descriptors of structural vulnerability to the case of advanced microgrids. • Discusses the implications of our analysis for other AI-enhanced systems.