Code on computer.

Building Trust Through Transparency? FDA Regulation of AI/ML-Based Software

By Jenna Becker

To generate trust in artificial intelligence and machine learning (AI/ML)-based software used in health care, the U.S. Food and Drug Administration (FDA) intends to regulate this technology with an eye toward user transparency. 

But will transparency in health care AI actually build trust among users? Or will algorithm explanations go ignored? I argue that individual algorithm explanations will likely do little to build trust among health care AI users.

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AI concept art.

Health Care AI in Pandemic Times

By Jenna Becker

The early days of the COVID-19 pandemic was met by the rapid rollout of artificial intelligence tools to diagnose the disease and identify patients at risk of worsening illness in health care settings.

Understandably, these tools generally were released without regulatory oversight, and some models were deployed prior to peer review. However, even after several months of ongoing use, several AI developers still have not shared their testing results for external review. 

This precedent set by the pandemic may have a lasting — and potentially harmful — impact on the oversight of health care AI.

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NHS building

First Do No Harm: The Independent Medicines and Medical Devices Safety Review

By John Tingle

A new hard-hitting report on medicines and medical device safety published in the U.K. presents controversial proposals that have the potential to improve National Health Service (NHS) patient safety.

The report, The Independent Medicines and Medical Devices Safety Review, was published on July 8th, 2020 after a two year investigation chaired by Baroness Julia Cumberlege. The review investigated two medications — Primodos and sodium valproate — and one medical device — pelvic mesh.

The reviews remit was to examine how the healthcare system in England responded to reports about harmful side effects from medicines and medical devices and how best to respond in the future.

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