From Talk to Triage: Pluralism is Necessary but Not Sufficient for AI Alignment

As AI systems become both more powerful and prevalent, ensuring that their actions align with human values is paramount. The challenge of AI alignment is thus an interdisciplinary one that involves not only a technical challenge for computer science but one with important ties to the psychology of moral values, decision-making, and trust. Early work identified a static set of universal values, without considering the key questions of to whom and to which values AI should be aligned. This perspective paper challenges the notion of universal alignment and instead argues for dynamic, context-specific alignability across different domains, tasks, and users. Specifically, we emphasize the need to go beyond traditional pluralism and rethink how AI alignment can be achieved through a qualitative and quantitative research process that involves identifying context-specific values, developing alignable AI algorithms using limited human feedback, and evaluating alignment through assessing both an AI’s values and actions, while considering how humans trust and delegate to the AI. We discuss several paths forward for our proposed framework, including the potential ethical and societal implications of context-specific alignability, and draw on examples ranging from chatbots to value-aligned decision-making in the medical triage domain.