December is both a festive and frantic month. Along with all the caroling, wassailing, and gift-buying, the last month of the year invariably sees us squeezing in continuing legal education (CLE) credits, reconnecting with old friends at the ACI drug and device conference in New York City, and wrapping up the Fall/Winter semester class we
Some of us are participating in beta testing of generative artificial intelligence (“AI”) for legal applications in the law firm environment. So far the verdict is – associates can breathe easy, at least for now. Nothing we’ve seen is capable of replicating legal research even at a first-year level of quality.
But that doesn’t mean that AI won’t impact prescription medical product liability litigation. In particular, we’re not surprised to learn that AI is being used in the context of FDA-required adverse event reporting, purported problems with which have become one of the other side’s go-to preemption dodges. Just a few examples from a simple Google search:Continue Reading Musing about Discovery and Artificial Intelligence
We’re interested in artificial intelligence, particularly as it affects medical devices, but we don’t know all that much about it, and it’s yet to make much of an impact in our product liability sandbox. Fortunately, we know some folks who do stay informed on this topic, and that’s what today’s guest post is about. In
Today’s guest post is by Corinne Fierro, Mildred Segura, and Farah Tabibkhoei, all of Reed Smith. These three are all part of the firm’s left-coast, techno side of the product liability practice, and bring our readers a recent appellate decision that addresses the intersection of 21st Century high technology and 20th Century
A week or so ago, Bloomberg Law published (behind a pay wall) an article entitled “Medical Device Makers May Risk Liability Following FDA Effort.” The Bloomberg article relied upon the same FDA initiative regarding artificial intelligence/machine learning (“AI/ML”) in medical devices that we covered here, in a guest post. Our guest post raised preemption
If the promise of adaptive artificial intelligence (sometimes called “Machine Learning”) is to be achieved in the medical area, FDA’s regulation of medical devices is going to have to graduate from geometry to calculus. By its nature, machine learning changes the details of its output constantly. The rigid regulatory model requiring FDA pre-approval of all
The 21st Century Cures Act is noteworthy as the first legislative attempt at regulating artificial intelligence (“AI”) in the medical field. The Act added this provision to the FDCA:
(o) Regulation of medical and certain decisions support software: (1) The term device . . . shall not include a software function that is intended
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In the July 7, 2017, “Artificial Intelligence” issue of Science, we were intrigued by a short piece in the “Insights” section on “Artificial Intelligence in Research” that discussed the future use of autonomous robots in surgery. Surgeonless surgery would “allow[] work around the clock with higher productivity, accuracy, and efficiency as well as shorter