Usage Governance Advisor: From Intent to AI Governance

TL;DR

This paper introduces Usage Governance Advisor, a system that assesses AI safety, identifies risks, and recommends mitigation strategies to ensure responsible AI deployment and compliance.

Contribution

The paper presents a novel framework for AI governance that integrates heterogeneous safety information and provides actionable recommendations for responsible AI use.

Findings

Effectively identifies safety risks in AI systems.

Provides prioritized mitigation strategies.

Supports responsible AI deployment.

Abstract

Evaluating the safety of AI Systems is a pressing concern for organizations deploying them. In addition to the societal damage done by the lack of fairness of those systems, deployers are concerned about the legal repercussions and the reputational damage incurred by the use of models that are unsafe. Safety covers both what a model does; e.g., can it be used to reveal personal information from its training set, and how a model was built; e.g., was it only trained on licensed data sets. Determining the safety of an AI system requires gathering information from a wide set of heterogeneous sources including safety benchmarks and technical documentation for the set of models used in that system. In addition, responsible use is encouraged through mechanisms that advise and help the user to take mitigating actions where safety risks are detected. We present Usage Governance Advisor which creates semi-structured governance information, identifies and prioritizes risks according to the intended use case, recommends appropriate benchmarks and risk assessments and importantly proposes mitigation strategies and actions.