Evaluating AI Governance:
Insights from Public Disclosures
About this Project
This research studies how companies govern their AI systems based on public information.
We looked for benchmarks and trends to better understand the relationship between potential signals of good governance, such as having AI ethics principles, and implementation activities, such as measuring and minimizing risks.
Our analysis is based on data collected by EthicsGrade, and analyzed using the NIST AI Risk Management Framework (NIST AI RMF). It includes 254 companies.
Our goal is to empower those who need to evaluate companies with little or no access to internal information, such as consumers, investors, and procurement teams.
I led this project, and it was supported by EthicsGrade and by the IBM-Notre Dame Tech Ethics Lab.
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