Gender Shades - Intersectional Accuracy Disparities in Commercial Gender Classification

Watch a thought-provoking conference talk from FAT* 2018 where Joy Buolamwini presents groundbreaking research on intersectional accuracy disparities in commercial gender classification systems. Explore the motivations behind the study, understand the benchmarking process, and delve into the evaluation of gender classification accuracy across different skin types and genders. Learn about the responses from major tech companies like Microsoft, Face Plus, and IBM to the findings. Gain insights into the importance of intersectionality in AI, the dangers of biased data, and the ethical implications of using such technology. Engage with key takeaways and participate in a Q&A session addressing critical questions about the Fitzpatrick scale and the broader implications of this research for the field of artificial intelligence and society at large.