Reviewable Automated Decision-Making - A Framework for Accountable Algorithmic Systems

Explore a framework for accountable algorithmic systems in this 19-minute conference talk from the FAccT 2021 virtual event. Delve into the concept of reviewable automated decision-making as presented by researchers J. Cobbe, M. Lee, and J. Singh. Gain insights into the challenges and potential solutions for creating more transparent and accountable AI systems. Examine the intersection of technology, ethics, and policy as the speakers discuss their research findings and propose strategies for improving algorithmic accountability. Learn about the importance of human oversight in automated decision-making processes and discover how this framework can be applied to various sectors utilizing AI-driven systems.

Reviewable Automated Decision-Making: A Framework for Accountable Algorithmic Systems