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.
Figures & tables
Figure 1. SLEEC norm operationalisation process. Successful completion of all stages is necessary for the deployment of a SLEEC-norm-compliant AI agent; failure at any point precludes the agent’s deployment. Diagram of the SLEEC norm operationalisation process.
Figure 2. Stills from the ALMI project ( 26 ) demonstration video at https://youtu.be/VhfQmJe4IPc . The images show the robot providing user assistance during a cooking task and after a simulated user fall (right). Stills from the ALMI project demonstration video showing the TIAGo robot used by the project helping the user with the preparation of a pasta meal (left) and providing assistance after to the user who had a fall (right).