Assuring Data Authenticity in the Age of Generative AI
This commentary examines the challenges that generative artificial intelligence poses to the authenticity and integrity of scientific data. It proposes data-attestation requirements to strengthen accountability, preserve access to original research records, and help journals and institutions distinguish authentic evidence from synthetic or fabricated data.