Artificial intelligence and predictive algorithms in medicine: Promise and problems

Phillips et al discuss artificial intelligence (AI) and predictive algorithms in medicine. AI is defined as a "machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments." By incorporating volumes of real-world electronic medical record (EMR) data, AI addresses the effectiveness rather than only the efficacy of clinical trials, while concurrently incorporating key social determinants of health as predictors. To merge known social and biological predictors of health, AI requires availability and precision of sociodemographic parameters such as race and socioeconomic status, data not routinely included in Canadian EMRs. Artificial intelligence algorithms that are proprietary, as most have been to date, tend to lack transparency, necessitating clever workarounds to audit them for such disparities or distortion, and to find bias, inequality, and sources of misdiagnosis or overdiagnosis.