One of the most touted promises of medical artificial intelligence tools is their ability to augment human clinicians' performance by helping them interpret images such as X-rays and CT scans with greater precision to make more accurate diagnoses.
Mar 19 2024Harvard Medical School One of the most touted promises of medical artificial intelligence tools is their ability to augment human clinicians' performance by helping them interpret images such as X-rays and CT scans with greater precision to make more accurate diagnoses.
We find that different radiologists, indeed, react differently to AI assistance -; some are helped while others are hurt by it." Instead, the results should signal the need to better understand how humans and AI interact and to design carefully calibrated approaches that boost human performance rather than hurt it.
In contrast, the new study looks at how individual clinician factors -; area of specialty, years of practice, prior use of AI tools -; come into play in human-AI collaboration. AI tools influenced human performance unpredictably AI's effects on human radiologists' performance varied in often surprising ways.
While the analysis was not done in a way that allowed researchers to determine why this happened, the finding points to the importance of testing and validating AI tool performance before clinical deployment, the researchers said. Such pre-testing could ensure that inferior AI doesn't interfere with human clinicians' performance and, therefore, patient care.
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