Should-Read: A. Michael Froomkin, Ian R. Kerr, Joelle Pineau: When AIs Outperform Doctors: The Dangers of a Tort-Induced Over-Reliance on Machine Learning and What (Not) to Do About it
Should-Read: I am not sure I see the problem here: diagnoses are assignments of patients to human-specified categories. You cannot take the human doctors out of the loop here—they are the people who retrospectively assess whether the diagnosis is correct. The potential problems seem to me to still be far down the road—at the point where the ML algorithm starts saying “people with this diagnosis have done better under that treatment regimen” without any ability to explain why: A. Michael Froomkin, Ian R. Kerr, Joelle Pineau: When AIs Outperform Doctors: The Dangers of a Tort-Induced Over-Reliance on Machine Learning and What (Not) to Do About it: “Someday, perhaps soon, diagnostics generated by machine learning (ML) will have demonstrably better success rates than those generated by human doctors…
…What will the dominance of ML diagnostics mean for medical malpractice law, for the future of medical service provision, for the demand for certain kinds of doctors, and—in the longer run—for the quality of medical diagnostics itself?… Effective machine learning could create overwhelming legal and ethical pressure to delegate the diagnostic process to the machine. Ultimately, a similar dynamic might extend to treatment also…. This may result in future decision scenarios that are not easily audited or understood by human doctors….
The article describes salient technical aspects of this scenario particularly as it relates to diagnosis and canvasses various possible technical and legal solutions that would allow us to avoid these unintended consequences of medical malpractice law. Ultimately, we suggest there is a strong case for altering existing medical liability rules in order to avoid a machine-only diagnostic regime. We argue that the appropriate revision to the standard of care requires the maintenance of meaningful participation by physicians in the loop…