For AI to make a truly damaging dent in COVID-19’s armor, developers need to better connect big-data analytics with regularly refreshed input from frontline healthcare workers.
Stated another way, AI assigned to the COVID case needs to incorporate human-in-the-loop machine learning, or “HIL ML.”
An exec with a healthcare AI company spells out the particulars of the opportunity in an opinion piece published online by the Brookings Institution.
A “fundamental disconnect has hindered healthcare for decades—those who deliver the care have the least voice in how care is delivered,” writes Drew Arenth of Seattle-based macro-eyes. “It can be resolved with minimal disruption using HIL ML to engage an educated and impassioned community of health workers.”
Defining HIL ML as the process of receiving data-rich insights from people, analyzing them in real time and sharing recommendations back, Arenth points out that AI in healthcare has been successful in spots but underutilized overall.
“COVID-19 is the greatest global crisis of our time: an immediate health challenge and a challenge of yet unknown duration on the economic and psychological well-being of our society,” he writes. “The lack of data-driven decisionmaking and the absence of adaptive and predictive technology have prolonged and exacerbated the toll of COVID-19. It will be the adoption of these technologies that helps us to rebuild health and society.”
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