A Brief Overview of AI Governance for Responsible Machine Learning Systems
It addresses the problem of managing AI risks for organizations across industries, but it is incremental as it presents a brief overview without new empirical results.
This position paper introduces AI governance as a framework to oversee the responsible use of AI, aiming to prevent and mitigate risks such as regulatory, reputational, and societal issues, while maximizing value and consistency in organizational adoption.
Organizations of all sizes, across all industries and domains are leveraging artificial intelligence (AI) technologies to solve some of their biggest challenges around operations, customer experience, and much more. However, due to the probabilistic nature of AI, the risks associated with it are far greater than traditional technologies. Research has shown that these risks can range anywhere from regulatory, compliance, reputational, and user trust, to financial and even societal risks. Depending on the nature and size of the organization, AI technologies can pose a significant risk, if not used in a responsible way. This position paper seeks to present a brief introduction to AI governance, which is a framework designed to oversee the responsible use of AI with the goal of preventing and mitigating risks. Having such a framework will not only manage risks but also gain maximum value out of AI projects and develop consistency for organization-wide adoption of AI.