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.

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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

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article

Data-hugging shields proprietary AI models from research that could disprove them

Cynthia Rudin, Xiao Hu, Anish Karpurapu, Zhicheng Guo
npj Artificial Intelligence
Artificial Intelligence in Healthcare and Education
article

Data-hugging shields proprietary AI models from research that could disprove them

Cynthia Rudin, Xiao Hu, Anish Karpurapu, Zhicheng Guo
article en

Abstract

No abstract available for this paper.

npj Artificial IntelligenceVol. 2(1)
Emory University (US), Duke University (US), Duke Medical Center (US)
National Institutes of Health, National Heart, Lung, and Blood Institute
Openalex Percentile: Top 23%
Artificial Intelligence in Healthcare and Education
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