Using AI in clinical care will need

Using AI in clinical care will need to meet particularly high standards to satisfy clinicians and patients. Even if the AI approach has demonstrated improvements over other approaches, it is not (and never will be) perfect, and mistakes, no matter how infrequent, will drive significant, negative perceptions. An instructive example can be seen with another AI-fueled innovation: driverless cars. Although these vehicles are, on average, safer than human drivers, a pedestrian death due to a driverless car error caused great alarm. A clinical mistake made by an AI-enabled process would have a significant chilling effect. Thus, ensuring the appropriate level of oversight and regulation is a critical step in introducing AI into the clinical arena.In addition to demonstrating its clinical effectiveness, evaluation of the cost-effectiveness of AI is also important. Huge investments into AI are being made with promised efficiencies and assumed cost reductions in return, similar to robotic surgery. However, it is unclear that AI techniques, with their attendant needs for data storage, data curation, model maintenance and updating, and data visualization, will significantly reduce costs. These tools and related needs may simply replace current costs with different, and potentially higher, costs.