AMIA encourages stricter FDA oversight of machine learning algorithms

The American Medical Informatics Association submitted a letter to the FDA this week not only praising the agency's proposed regulatory framework concerning the use of self-updating artificial intelligence in medicine, but also encouraging even stricter regulations.

In April, the FDA issued a discussion paper and request for feedback regarding this proposed framework, which would regulate the use of medical device algorithms that use machine learning to continually update as they are fed more data. Currently, the FDA only authorizes the use of AI products that operate on a fixed algorithm.

After "applauding" the FDA's drafted framework, the AMIA proposed four major modifications:

  • A stronger emphasis on the stark difference between the two types of algorithms.
  • Acknowledgement of the risk that machine learning algorithms can "learn" from weak or biased data and are not always able to explain their decisions.
  • A warning about the possibility that algorithms can be exposed to cybersecurity risks with unregulated updates.
  • Provisions to ensure algorithms are developed to be as unbiased as possible.

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