When: Friday, March 12, 2021, 9:00 - 10:15 a.m. EST
What: Policymakers and researchers throughout the world are considering strategies for reducing biased decisions made by machine-learning algorithms. To date, the U.K. has been the most forward in outlining a role for government in identifying and mitigating biases and their unintended consequences, especially decisions that impact marginalized populations. In the U.S., legislators and policymakers have focused on algorithmic accountability and the explanation of models to ensure fairness in predictive decisionmaking.
On March 12, the Center for Technology Innovation at Brookings will host a webinar on the role of government in identifying and reducing algorithmic biases. Speakers will discuss what is needed to prioritize fairness in machine-learning models and how to weed out artificial intelligence (AI) models that perpetuate discrimination. How are the European Union, U.K., and U.S. differing in their approaches to bias and discrimination? What lessons can they learn from each other? Should approaches to AI bias be universally applied to ensure civil and human rights for protected groups?