Guest post by Dr. Lyric Jorgenson, NIH Associate Director for Science Policy, originally posted on the Under the Poliscope blog.
One of the hardest (and most fun) parts of my job is conjuring up my crystal ball to foresee the policy needs of tomorrow. Of course, forecasting the future isn’t really that easy. Technology moves at light speed, while policy… well, policy often moves slower (we can get into that in another blog). How can we ready the biomedical research enterprise for the future when the future itself is a moving target? Paradoxically, to quote Taylor Swift, “lookin’ backwards might be the only way to move forward.”
As policymakers, we are continuously striving to develop policies capable of evolving alongside science and technology, taking into consideration that we know there will be unexpected twists and turns along the way. This is why we built a certain degree of flexibility into the NIH Data Management and Sharing Policy – because new tools for creating, sharing, and accessing data are being developed every day.
This is especially the case for machine learning algorithms, natural language processing, and other forms of “artificial intelligence” that are creating new research opportunities and transforming a new wave of improved health outcomes. Artificial intelligence (AI) has been around in some shape or form for some time. However, the ease in which AI approaches can be developed and deployed (similar to what CRISPR did for gene editing) has leveled the playing field for researchers around the globe to find new patterns in rich and complex datasets.
Of course, with great power comes great responsibility. At NIH, we prioritize the safe and responsible development and use of algorithms and models for research. We also implement policies and practices to ensure deposition of AI-ready datasets that are reliable, representative, and robust. To achieve these aims, NIH relies on its forward-leaning policy infrastructure to safeguard our work. While these policies might not specifically state AI in the title, the anticipated use of AI and risks from those uses is what we intended to address. To help the research community understand how these policies guide AI-related research, OSP recently released a centralized NIH policy resource illustrating the applicability of existing policies to AI, including policies related to participant protections, intellectual property, peer review, and many other topics.
An important thing to keep in mind is that NIH’s current policy landscape is well positioned to ensure the responsible use of AI technologies. However, as a policy office, we know that sometimes new policies are indeed warranted to capture new risks as science and technology progresses. NIH is committed to monitoring the field of AI and other emerging technologies and we will continue to update this resource to make sure we are keeping pace from a policy perspective. I invite you to check out this new resource and let us know your thoughts. Research that leverages the most promising technologies in a responsible manner will lead to better health for all. That is a future we can all hope for.
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