Health Law Highlights

New Practical Guidance for Balancing Fairness, Privacy

Summary of article from IAPP, by Cobun Zweifel-Keegan:

The tension between achieving fairness and maintaining privacy in the operation of advanced AI and machine learning systems is a major challenge for digital governance teams. To test for bias and ensure equity, demographic data is often needed, potentially infringing on privacy rights. A report by the Center for Democracy and Technology AI Governance Lab offers best practices for navigating this issue, such as gathering data responsibly, pseudonymization, encryption, and conducting privacy impact assessments. Legislation, like the upcoming Colorado bill, may balance these issues by requiring fairness and bias testing in AI systems. Transparency and clear communication of methodologies are essential to build trust and uniform benchmarks in AI governance.