Papers for

organizational compliance teams

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Align agent responsibilities and powers to avoid system conflicts

Aligning Institutional Power and Operational Ability

Abstract: To be socially sustainable, Agentic AI systems require normative designs that align responsibilities with the ability to fulfil them. Identifying incongruences such as unsatisfiable expectations or privilege escalation is crucial in avoiding normative pitfalls. In this study, we discuss design dimensions suitable for describing multi-agent systems in light of this norm-ability alignment requirement. We propose a formal framework centred on process-oriented modelling and institutional power for the analysis of a given normatively relevant process, discuss strategies for repairing it, and elaborate on how the symmetrical relation between operational process and institutional state affects the lifecycle of normative positions.

Tue 27 OctArtificial IntelligenceMultiagent Systems

The gist

AI systems with multiple agents need to make sure that the responsibilities assigned to each agent match what they can actually do. If an agent is expected to do something impossible or can unfairly gain extra power, problems can arise. The authors propose a way to describe and analyze these systems using models of processes and institutional power. This helps detect and fix mismatches between what agents are supposed to do and what they can do, ensuring more socially responsible AI behavior.

Open → 2610.37342v1