Data-hugging shields proprietary AI models from research that could disprove them
"Data hugging" blocks independent verification of medical AI. Apple claims age estimation with a mean absolute error of 2.9 years using photoplethysmographic (PPG) signals. Given PPG's noise, such accuracy is questionable, raising concerns about other tech companies' claims. Using UK Biobank data, we find this accuracy unreplicable, achieving results only marginally better than predicting mean age. We advocate for curated public benchmark datasets and evaluation platforms to protect the public from unverifiable claims.
Authors
- Cynthia Rudin
- Xiao Hu
- Anish Karpurapu
- Zhicheng Guo
Institutions
- Emory University (US)
- Duke University (US)
- Duke Medical Center (US)
Publication Details
- Journal
- npj Artificial Intelligence
- Published
- 2026-04-17
- DOI
- https://doi.org/10.1038/s44387-026-00094-2
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute