To establish that trust, researchers at Cornell University attempted to create a more transparent AI system that works by counseling doctors in the same way a human colleague would — that is, arguing over what the medical literature says.
After interviewing and surveying a group of twelve doctors and clinical librarians, the researchers found that when these medical experts disagree on what to do next, they turn to the relevant biomedical research and weigh up its merits. Their system, therefore, aimed to emulate this process. The AI tool Yang's team created is based on GPT-3, an older large language model that once powered OpenAI's. The tool's interface is fairly straightforward: on one side, it provides the AI's suggestions. The other side contrasts this with relevant biomedical literature the AI gleaned, plus brief summaries of each study and other helpful nuggets of information like patient outcomes.
...it makes a weird suggestion and the doctor goes 'that's weird' and ignores it? Ultimately it's a question of money into healthcare and the insurance industry. Testing people for edge case possibilities costs insurance companies money, and they don't like that.