ARTIFICIAL INTELLIGENCE IN HEALTHCARE: ITS POTENTIALS AND RISKS
Abstract
Artificial intelligence has moved from science fiction into the clinic with remarkable speed. Machine learning systems now read medical scans, flag sepsis before symptoms declare themselves, draft clinical notes, and coach patients through their smartphones. This article examines the promise and the peril of this transformation in narrative form, and then applies the lens to a single, vivid case: the intertwined epidemics of sleep deprivation and migraine in young adults, where wearable sensors and predictive algorithms are beginning to change how these conditions are detected, studied, and managed. The evidence suggests that AI's greatest near-term contribution is not replacing clinicians but extending their reach — while its greatest dangers, including algorithmic bias, opaque decision making, data privacy erosion, and over-reliance, demand deliberate governance. The article argues that the future of medical AI will be decided less by the sophistication of the algorithms than by the wisdom of the humans who deploy them.
