United States: FDA Joins Other Regulators In Focus On AI And Machine Learning
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The Food and Drug Administration recently sought comments on the
role of transparency for artificial intelligence and machine
learning-enabled medical devices. The FDA invited comments in
follow up to a recent workshop on the topic.
The workshop was part of a series of efforts the FDA has had in
this space. These include its Digital Health Center of
Excellence and a five-part Action Plan for AI and
machine-learning enabled medical devices. As part of the action
plan, the FDA indicated it wants to issue guidance on software
learning over time and help the industry be “patient-centered.” In other words, that companies be
transparent when using AI and machine learning-enabled software
with patients. These initiatives are especially important given the
increase in AI/ML in healthcare.
Workshop participants explored how to provide transparency. One idea proposed was using a “nutrition
fact label” approach to give individuals enough information to
make informed decisions. The graphic would be similar to a food
label, disclosing quickly and visually the key things patients
might want to know. (This is similar to an approach launched by
Apple late last year, which we discussed here.) Other agencies have
looked at machine learning and AI with similar transparency
recommendations. We have written about those in the past, including
for the financial services
industry. Advice about use of these tools has also been issued
by the FTC and the EU.
Putting it Into Practice: While the FDA continues to
explore this area, companies are reminded that the FDA (like other
regulators) expects transparency with consumers. From a privacy
perspective, the workshop reminds digital health companies this
includes telling users when AI or ML-enabled software is being
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