From the alarming forecasts of tech moguls to vigorous debates on online forums, there's a growing public discussion about the risks and benefits of artificial intelligence (AI) and how to manage its development. People often talk about AI by evoking grandiose prophecies about the future. While one day we may be apathetically wiped out by a rogue AI, or instead, become immortal cyborgs worshipping a god-like algorithm, important developments are happening today. And healthcare is a domain in which AI is already having a significant impact. However, these advancements give rise to various policy challenges that will need to be carefully addressed.
Emerging AI in healthcare
Many medical tasks have already been performed very well by new AI. In radiology, for example, there is a growing body of fascinating new research. Recently, scientists in the UK used almost half a million chest X-rays to develop an AI that could reliably identify abnormal images, creating the potential for software to help triage the large backlog of X-rays in many healthcare systems. But AI can do more than just sort images. Researchers at Stanford have produced an algorithm to interpret chest X-rays for 14 distinct pathologies simultaneously within a few seconds. And another recent Finnish study showed that machine learning had overtaken humans at predicting, from imaging data, certain types of heart attack and death. Similar developments are happening with imaging for other diseases.
AI will initially be implemented alongside human expertise rather than in place of it. However, some experts predict that radiologists could eventually be displaced by AI, relegating humans to the role of quality control reviewers. But with multiple factors contributing to increased strain on health professionals, a potential human resource crisis in healthcare could mean we need AI just to get by. And the shift toward AI could come quicker than you think. In April of 2018, the U.S. Food and Drug Administration (FDA) approved the first AI medical device, which analyzes images to detect a form of eye disease caused by diabetes.
Organ donation and transplantation have also benefited greatly from new AI. Kidney donation pairing programs in Canada and United States now use complex algorithms to optimize and match registered donors with transplant candidates based on a multitude of factors. Since potential living donors will only donate a kidney to a stranger if their loved one receives one in...