Mediaboss Marketing

26 November 2021

Sheppard Mullin Richter & Hampton

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The Food and Drug Administration recently sought comments on therole of transparency for artificial intelligence and machinelearning-enabled medical devices. The FDA invited comments infollow up to a recent workshop on the topic.

The workshop was part of a series of efforts the FDA has had inthis space. These include its Digital Health Center ofExcellence and a five-part Action Plan for AI andmachine-learning enabled medical devices. As part of the actionplan, the FDA indicated it wants to issue guidance on softwarelearning over time and help the industry be"patient-centered." In other words, that companies betransparent when using AI and machine learning-enabled softwarewith patients. These initiatives are especially important given theincrease in AI/ML in healthcare.

Workshop participants explored how to provide transparency. One idea proposed was using a "nutritionfact label" approach to give individuals enough information tomake informed decisions. The graphic would be similar to a foodlabel, disclosing quickly and visually the key things patientsmight want to know. (This is similar to an approach launched byApple late last year, which we discussed here.) Other agencies havelooked at machine learning and AI with similar transparencyrecommendations. We have written about those in the past, includingfor the financial servicesindustry. Advice about use of these tools has also been issuedby the FTC and the EU.

Putting it Into Practice: While the FDA continues toexplore this area, companies are reminded that the FDA (like otherregulators) expects transparency with consumers. From a privacyperspective, the workshop reminds digital health companies thisincludes telling users when AI or ML-enabled software is beingused.

The content of this article is intended to provide a generalguide to the subject matter. Specialist advice should be soughtabout your specific circumstances.

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