Shortcuts Are Bad – Even for AI

Relying on shortcuts for work isn't always a great idea – and that holds true for artificial intelligence (AI) with chest X-rays and COVID-19, as well. New research from the University of Washington (UW), shows that AI, like humans, has a tendency to lean on shortcuts for disease detection with these scans. If the tools are deployed clinically, investigators said, the result could be diagnostic errors that impact real patients. Rather than learning from actual medical pathology and clinically significant indicators, the team, led by Paul G. Allen School of Computer Science & Engineering doctoral students, Alex DeGrave, who is also a medical student in the UW Medical Scientist Training Program, and Joseph Janizek, also a UW medical student, showed that algorithms used during the pandemic relied on text markers and patient positioning specific to each dataset to predict whether someone was COVID-19-positive. The team published their results May 31 in Nature Machine Intelligence.