Empirical Studies

Explore cutting-edge research on fairness, accountability, and transparency in algorithmic systems through this conference session from FAT* 2019. Delve into four presentations covering crucial topics: algorithmic bias in risk assessments, racial disparities in healthcare algorithms, ethical challenges in inferring mental health from social media, and China's social credit system. Gain insights from leading researchers as they discuss empirical studies addressing critical issues at the intersection of technology, society, and ethics. Learn about methodologies for analyzing algorithmic fairness, understand the real-world impacts of AI systems on marginalized communities, and examine the ethical implications of large-scale behavioral scoring systems.