Alice Xiang

Treading the Transparency Tightrope: A Taxonomy of Risks and Benefits of Foundation Model Data Transparency for Transparency Advocates

Data powering AI is often opaque. Researchers, NGOs, and law and policy leaders have called for greater transparency about how data is used for training, fine-tuning, and evaluation. While data transparency is often championed as crucial, what it concretely enables is largely implicit. Similarly, the concerns develope…