A Brief Overview of AI Governance for Responsible Machine Learning Systems

TL;DR

This paper introduces AI governance frameworks that help organizations responsibly manage AI risks, ensuring ethical use, compliance, and maximizing AI benefits across various sectors.

Contribution

It provides a concise overview of AI governance principles and highlights their importance for responsible AI deployment in organizations.

Findings

AI governance helps mitigate regulatory and societal risks.

Frameworks promote responsible and consistent AI use.

Effective governance enhances trust and value in AI systems.

Abstract

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.