Learn from the blame game when AI causes harm
| dc.contributor.author | Killoran, Jay | |
| dc.contributor.author | Park, Andrew | |
| dc.date.accessioned | 2026-06-25T20:15:20Z | |
| dc.date.available | 2026-06-25T20:15:20Z | |
| dc.date.issued | 2026 | |
| dc.description.abstract | In 2023, families of deceased Medicare Advantage patients filed a class action lawsuit against UnitedHealth Group, alleging that an AI algorithm, nH Predict, systematically denied medically necessary post-acute care. Physicians had approved the care, but nH Predict denied it. The lawsuit alleged that UnitedHealth knew the tool had a 90% error rate, yet continued to deploy it, counting on fewer than 1% of patients appealing. For its part, UnitedHealth has denied wrongdoing, maintaining that nH Predict was never used to make coverage determinations but, rather, served only as a clinical guide and that all coverage decisions were made by human reviewers. The case, which is ongoing, ignited a wider debate: Who was to blame? The engineers? The company? The case managers? Or the AI system? | |
| dc.description.reviewstatus | Reviewed | |
| dc.description.scholarlevel | Faculty | |
| dc.identifier.citation | Killoran, J., & Park, A. (2026). Learn from the blame game when AI causes harm. Proceedings of the National Academy of Sciences - PNAS, 123(17), Article e2528408123. https://doi.org/10.1073/pnas.2528408123 | |
| dc.identifier.uri | https://doi.org/10.1073/pnas.2528408123 | |
| dc.identifier.uri | https://hdl.handle.net/1828/24011 | |
| dc.language.iso | en | |
| dc.publisher | PNAS | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject.department | Peter B. Gustavson School of Business | |
| dc.title | Learn from the blame game when AI causes harm | |
| dc.type | Article |