Artificial intelligence and the situational rationality of diagnosis: Human problem‐solving and the artifacts of health and medicine

What is the problem-solving capacity of artificial intelligence (AI) for health and medicine? This paper draws out cognitive sociological context diagnostic medical sociology regarding limits automation decision-based tasks. Specifically, it presents a practical way evaluating artificiality symptoms signs in encounters, with an emphasis on visualization process doctor-patient relationships. In doing so, details logical differences underlying task performance between man machine problem-solving: its principle rationality, priorities means adaptation to abstraction, effects seeking optimization process. Using these parameters as heuristic AI address issues error through design, conceptual review discipline medicine. Studies relying procedural rationality describe models that treat diagnosis “natural artifact” by employing symbolic methods designed simulate human problem-solving. Research adhering probabilistic describes ecological image utilizing sub-symbolic neural networks. guided situational require treating “socio-cognitive artifact,” which organized discourses patient-centered decision-making. The concludes commentary ethical application medicine, given performance.