Brand: Gender Shades

Gender Shades is a groundbreaking project that aims to raise awareness and address the intersectional accuracy differences in gender classification by AI services. Led by Joy Buolamwini and co-authored by Timnit Gebru, the project sheds light on the biases and limitations in AI algorithms used for facial recognition.

With a focus on examining how well IBM, Microsoft, and Face++ AI services guess the gender of a face, Gender Shades presents compelling research papers and datasets for further exploration. The Algorithmic Justice League, spearheading this initiative, provides a platform to engage with the community through their website and social media channels.

Join Gender Shades in the fight against bias in artificial intelligence. Together, we can work towards a more inclusive and accurate future.