Social, Legal, Ethical, Empathetic and Cultural Norm Operationalisation for AI Agents
This addresses the critical problem of ensuring AI agents behave in accordance with human norms for applications in fields like healthcare and law enforcement, though it is incremental as it builds on existing frameworks.
The paper tackles the challenge of aligning AI agents with social, legal, ethical, empathetic, and cultural norms in high-stakes domains by proposing a systematic operationalisation process to translate abstract principles into concrete requirements, establishing a framework for developing norm-aligned AI agents.
As AI agents are increasingly used in high-stakes domains like healthcare and law enforcement, aligning their behaviour with social, legal, ethical, empathetic, and cultural (SLEEC) norms has become a critical engineering challenge. While international frameworks have established high-level normative principles for AI, a significant gap remains in translating these abstract principles into concrete, verifiable requirements. To address this gap, we propose a systematic SLEEC-norm operationalisation process for determining, validating, implementing, and verifying normative requirements. Furthermore, we survey the landscape of methods and tools supporting this process, and identify key remaining challenges and research avenues for addressing them. We thus establish a framework - and define a research and policy agenda - for developing AI agents that are not only functionally useful but also demonstrably aligned with human norms and values.