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

arXiv: https://arxiv.org/abs/2603.11864 · HTML: https://mlsanity.com/paper/2603.11864/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 32 references that are in the map.
- First posted on arXiv 12 Mar 2026.

## Builds on (most cited first, 8 of 8)

- [Specification, Validation and Verification of Social, Legal, Ethical, Empathetic and Cultural Requirements for Autonomous Agents](https://mlsanity.com/paper/2307.03697/) (2023)
- [Analyzing and Debugging Normative Requirements via Satisfiability Checking](https://mlsanity.com/paper/2401.05673/) (2024)
- [Normative Requirements Operationalization with Large Language Models](https://mlsanity.com/paper/2404.12335/) (2024)
- [Towards Adaptive Planning of Assistive-care Robot Tasks](https://mlsanity.com/paper/2209.14041/) (2022)
- [Early Verification of Legal Compliance via Bounded Satisfiability Checking](https://mlsanity.com/paper/2209.04052/) (2022)
- [Social, Legal, Ethical, Empathetic, and Cultural Rules: Compilation and Reasoning (Extended Version)](https://mlsanity.com/paper/2312.09699/) (2023)
- [Diagnosis via Proofs of Unsatisfiability for First-Order Logic with Relational Objects](https://mlsanity.com/paper/2409.09223/) (2024)
- [Tool for Supporting Debugging and Understanding of Normative Requirements Using LLMs](https://mlsanity.com/paper/2507.05504/) (2025)

## Abstract (arXiv)

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.