Research scientist at Google. Previously Stanford Biomedical Informatics. Researching #fairness #equity #robustness #transparency #causality #healthcarehttps://bsky.app/profile/stephenpfohl.bsky.socialhttps://bsky.app/profile/stephenpfohl.bsky.social/post/3mjaxpwyyps2zThe most ignored instructions for ML conference review has got to be the "Please use sparingly" designation for weak accept/reject recommendations11 Apr 2026 23:15 +0000at://did:plc:hh56k55mmqk5o7z53dfpe65a/app.bsky.feed.post/3mjaxpwyyps2zhttps://bsky.app/profile/stephenpfohl.bsky.social/post/3m47ou4h36c2xExcited to share that our paper, “Understanding challenges to the interpretation of evaluations of algorithmic fairness” has been accepted to NeurIPS 2025! You can read the paper now on arXiv: arxiv.org/abs/2506.04193. https://arxiv.org/abs/2506.0419328 Oct 2025 00:36 +0000at://did:plc:hh56k55mmqk5o7z53dfpe65a/app.bsky.feed.post/3m47ou4h36c2xhttps://bsky.app/profile/stephenpfohl.bsky.social/post/3ldlzntehuk2yCheck out our new paper "Tackling Algorithmic Bias and Promoting Transparency in Health Datasets: The STANDING Together Consensus Recommendations" jointly published in NEJM AI and The Lancet Digital Health, led by @jaldmn.bsky.social @xiaoliu.bsky.social [contains quote post or other embedded content]18 Dec 2024 18:51 +0000at://did:plc:hh56k55mmqk5o7z53dfpe65a/app.bsky.feed.post/3ldlzntehuk2y