Our paper “A Brief Overview of AI Governance for Responsible Machine Learning Systems” was recently accepted to the Trustworthy and Socially Responsible Machine Learning (TSRML) workshop at NeurIPS 2022 (New Orleans). In this paper, we discuss the framework and value of AI Governance for organizations of all sizes, across all industries and domains.
Our paper is publicly available in arxiv: Gill, N., Mathur, A., Conde, M. (2022) A Brief Overview of AI Governance in Responsible Machine Learning Systems.
Organizations are leveraging artificial intelligence (AI) to solve many challenges. However, AI technologies can pose a significant risk. To avoid such risks, organizations must turn to AI Governance, which is a framework designed to oversee the responsible use of AI with the goal of preventing and mitigating risk.
AI Adoption & Problems within Industry
Problems within Industry
Manage AI Risk with AI Governance
What is AI Governance (AIG)?
AI Governance is a framework to operationalize responsible artificial intelligence at organizations. This framework
Benefits of AI Governance
Alignment and Clarity
Thoughtfulness and Accountability
Consistency and Organizational Adoption
Process, Communication, and Tools
Trust and Public Perception
Stages of a Governed AI Life Cycle
Use Case Planning
AI systems are used today to make life-altering decisions about employment, bail, parole, and lending, and the scope of decisions delegated by AI systems seems likely to expand in the future. The pervasiveness of AI across many fields is something that will not slowdown anytime soon and organizations will want to keep up with such applications. However, they must be cognizant of the risks that come with AI and have guidelines around how they approach applications of AI to avoid such risks. By establishing a framework for AI Governance, organizations will be able to harness AI for their use cases while at the same time avoiding risks and having plans in place for risk mitigation, which is paramount.