Social, Legal, Ethical, Empathetic and Cultural Norm Operationalisation for AI Agents

TL;DR

This paper presents a systematic process for operationalising social, legal, ethical, empathetic, and cultural norms in AI agents, bridging the gap between high-level principles and concrete, verifiable requirements in high-stakes domains.

Contribution

It introduces a comprehensive framework for translating abstract norms into operational requirements and surveys supporting methods, outlining challenges and future research directions.

Findings

Proposed a systematic norm operationalisation process.

Surveyed existing methods and tools supporting norm implementation.

Identified key challenges and research avenues for norm alignment.

Abstract

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.