Bias in Foundation Models: Primum Non Nocere or Caveat Emptor?

HomeRadiology: Artificial IntelligenceVol. 5, No. 6 PreviousNext CommentaryBias in Foundation Models: Primum Non Nocere or Caveat Emptor?Julianna Czum , Shane ParrJulianna Czum , Shane ParrAuthor AffiliationsFrom the Department of Radiology and Radiological Sciences, The Johns Hopkins University School of Medicine, 601 N Caroline St, Baltimore, MD 21287 (J.C.); and Brown University, Providence, RI (S.P.).Address correspondence to J.C. (email: [email protected]).Julianna Czum Shane ParrPublished Online:Oct 25 2023https://doi.org/10.1148/ryai.230384MoreSectionsFull textPDF ToolsAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In References1. Vaswani A, Shazeer N, Parmar N, et al. Attention is all you need. Advances in neural information processing systems. arXiv 1706.03762 [preprint] https://doi.org/https://doi.org/10.48550/arXiv.1706.03762. Accessed September 8, 2023. Google Scholar2. Krizhevsky A, Sutskever I, Hinton GE. Imagenet classification with deep convolutional neural networks. 25th Annual Conference on Neural Information Processing Systems Advances in neural information processing systems 2012;25. Google Scholar3. Tajbakhsh N, Shin JY, Gurudu SR, et al. Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning? IEEE Trans Med Imaging 2016;35(5):1299–1312. Crossref, Medline, Google Scholar4. Bommasani R, Hudson DA, Adeli E, et al. On the Opportunities and Risks of Foundation Models. arXiv 2108.07258 [preprint] https://arxiv.org/abs/2108.07258v3. Updated July 12, 2022. Accessed September 8, 2023. Google Scholar5. OpenAI. GPT-4 Technical Report. arXiv 2303.08774 [preprint] https://arxiv.org/abs/2303.08774v3. Accessed March 27, 2023. Accessed September 8, 2023. Google Scholar6. Hu K. ChatGPT sets record for fastest-growing user base - analyst note. Reuters. https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/. Updated February 2, 2023. Accessed September 8, 2023. Google Scholar7. Glocker B, Jones C, Roschewitz M, Winczek S. Risk of bias in chest radiography deep learning foundation models. Radiol Artif Intell 2023;5(6):e230060. Link, Google Scholar8. Deng J, Dong W, Socher R, Li LJ, Li K, Fei-Fei L. ImageNet: A large-scale hierarchical image database. 2009 IEEE Conference on Computer Vision and Pattern Recognition. Miami, Fla; 2009:248–255 Google Scholar9. CheXpert. Stanford ML Group. https://stanfordmlgroup.github.io/competitions/chexpert/. Accessed September 8, 2023. Google Scholar10. Friedler SA, Scheidegger C, Venkatasubramanian S. On the (im)possibility of fairness. arXiv 1609.07236 [preprint] https://arxiv.org/abs/1609.07236. Published September 23, 2019. Accessed September 8, 2023. Google Scholar11. Health and Healthcare Disparities. Johns Hopkins Bloomberg School of Public Health. https://publichealth.jhu.edu/welch-center-for-prevention-epidemiology-and-clinical-research/our-research/research-areas/health-and-healthcare-disparities. Accessed September 8, 2023. Google ScholarArticle HistoryReceived: Sept 11 2023Revision requested: Sept 13 2023Revision received: Sept 27 2023Accepted: Sept 29 2023Published online: Oct 25 2023 FiguresReferencesRelatedDetailsRecommended Articles Radiology Training in Latin America: How RSNA, RadioGraphics, and Subspecialty Societies Are Bridging Educational GapsRadioGraphics2023Volume: 43Issue: 8Artificial Intelligence for Clinical Interpretation of Bedside Chest RadiographsRadiology2022Volume: 307Issue: 1Clinical Validation Is the Key to Adopting AI in Clinical PracticeRadiology: Artificial Intelligence2021Volume: 3Issue: 4Detection and Semiquantitative Analysis of Cardiomegaly, Pneumothorax, and Pleural Effusion on Chest RadiographsRadiology: Artificial Intelligence2021Volume: 3Issue: 4Attention-based Saliency Maps Improve Interpretability of Pneumothorax ClassificationRadiology: Artificial Intelligence2022Volume: 5Issue: 2See More RSNA Education Exhibits Neural Networks in Deep Learning: A Simplified Explanation for RadiologistsDigital Posters2019360-Degree Review Of Lessons Learned From The COVID-19 Pandemic: The Spectrum Of Imaging Findings, Impact On Radiology Departments And The Role Of Artificial IntelligenceDigital Posters2020Introduction to Artificial Intelligence and Big Data Research in Chest RadiologyDigital Posters2019 RSNA Case Collection Pulmonary metastasis causing spontaneous pneumothoraxRSNA Case Collection2020Boerhaave SyndromeRSNA Case Collection2020LymphangioleiomyomatosisRSNA Case Collection2021 Vol. 5, No. 6 Metrics Downloaded 117 times Altmetric Score PDF download