Explores the rise of AI image editing and how deep-seated biases in training data result in problematic or stereotypical visual outputs.
Explores the rise of AI image editing and how deep-seated biases in training data result in problematic or stereotypical visual outputs.
Investigates the teams at Anthropic responsible for studying AI's societal impacts, specifically focusing on the measurement and mitigation of bias.
Expert Zahra Shah discusses AI governance, regulation, and the societal implications of deploying technologies that may harbor inherent biases.