Implementing Intersectionality in Algorithmic Fairness - Keynote Panel I

Explore the critical topic of implementing intersectionality in algorithmic fairness through this insightful keynote panel discussion. Delve into the challenges and potential approaches for addressing discrimination in sociotechnical systems that arise from intersecting identities and experiences. Learn from a diverse panel of experts including Dr. James Foulds, Youjin Kong, Dr. Yolanda A. Rankin, and Dr. Olga Russakovsky as they share their perspectives on integrating intersectionality into AI and machine learning practices. Gain valuable insights into the complexities of detecting and mitigating algorithmic bias, particularly when considering multiple demographic features and their unique interactions. Examine how intersectionality research can inform more equitable and inclusive technological design and development processes. Discover the importance of centering underrepresented voices and experiences in creating fairer AI systems. Engage with cutting-edge discussions on the ethical implications of AI, the role of diverse perspectives in shaping technology, and strategies for promoting justice and equality in the field of computing.

Keynote Panel I: Implementing Intersectionality in Algorithmic Fairness