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The Current State of AI Governance

Our interdisciplinary team at the Algorithmic Bias Lab has produced one of the very first comprehensive reports on the current state of organizational AI governance. The report, partly funded by Notre Dame-IBM Technology Ethics Lab, is a result of a yearlong study which utilized surveys, interviews, and a literature review to examine the internal governance landscape. We asked what governance tools are being used across sectors, are they working, and if so, why?

Our analysis found that significantly less than half of all organizations that use or develop AI have any formal or substantial governance structures for AI. Among those that do have AI governance structures, there is a variety of governance tools being used and a variety of reasons for adopting them. The organizations that do have some governance structures are, in almost all cases, past the stage of building AI governance frameworks, but have not yet developed metrics to assess their effectiveness. On average, organizations that have built AI governance structures are generally at the beginning of the implementation stage. 


Among those organizations that do have some governance structures, there are some key trends emerging regarding implementation strategies and challenges. These include, for example: the need for repositories and inventories, the importance of risk assessments, difficulties finding employees with the right skills, lack of external stakeholder engagement, importance of organizational culture for uptake of AI governance initiatives, lack of clear metrics, and others.

This report is the first in an ongoing project to track and measure the effectiveness of AI governance tools across industries. The hope is that the results of our analysis can help guide decision makers, many of whom are propping up nascent AI governance structures.

Citation: Davidovic, Jovana, Shea Brown, Ali Hasan, Khoa Lam, Ben Lange, and Mitt Regan, The Current State of AI Governance. Iowa City, IA: BABL AI, 2023.