Abstract Recent technological advances in artificial intelligence and machine learning have led to rapid changes in clinical informatics. With the release of new models, the barrier to creating medical software has markedly decreased. As noted in the now‐viral article by Matt Shumer, we have moved from a world where building a clinical application took a team of engineers working over the course of months to years, to one where a single clinician can develop and deploy a working prototype in hours to days. However, the same innovation driving this ‘explosion’ of tools also carries the risk of flooding health systems with unvalidated ‘AI slop.’ As prohibiting tools developed through AI runs the risk of stifling innovation and limiting potentially impactful discoveries, we suggest abandoning the slow, fear‐based resistance to AI adoption. Further, we propose a ‘go fast and fix things’ framework—utilising target product profiles, regulatory sandboxes, and continuous audit—to harness the speed of generation and prototyping while rigorously validating clinical utility.
Pujol et al. (Wed,) studied this question.