Exploring human-artificial intelligence interactions in a negative pragmatic trial of computer-aided polyp detection

Background and aims The progress of artificial intelligence (AI) in endoscopy is at a crossroads. The positive results of randomized controlled trials (RCT) of computer-aided detection (CADe) have not been replicated in multiple pragmatic CADe trials, including ours. This gap between efficacy and effectiveness remains to be understood. We surveyed and interviewed our trial’s colonoscopists to gain insight into human-AI interactions. Methods We used a sequential, mixed-methodology design. Following the trial, we administered Survey 1 focusing on attitudes and beliefs before and after trying CADe. The trial’s null results were disclosed, and we then administered Survey 2 and conducted open-ended interviews, focusing on reactions to the null results. Responses were analyzed overall and by baseline adenoma detection rate (ADR) tertile. We identified key themes utilizing thematic analysis and qualitative software. Results Nearly all colonoscopists responded (22 and 21 of 24 [92%, 88%] for Surveys 1 and 2). Most (96%) regarded endoscopic ability as critical to their professional identity. Large majorities conveyed trust in and enthusiasm for AI before and after trying CADe (82-87%), and desired to have CADe available (72%). Nearly two-thirds (62%) were surprised by the null results. There were few differences by ADR. No unifying explanation for the null results emerged from surveys or individual interviews. Colonoscopists expressed a range of expectations for AI in endoscopy. Conclusions Lack of enthusiasm or mistrust of AI/CADe do not explain our pragmatic CADe trial’s null results. AI may need to target dimensions beyond optical recognition to realize its promise in endoscopy.