Want to supercharge AI vs. COVID? Get more humans in the learning loop
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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Dave P. has worked in journalism, marketing and public relations for more than 30 years, frequently concentrating on hospitals, healthcare technology and Catholic communications. He has also specialized in fundraising communications, ghostwriting for CEOs of local, national and global charities, nonprofits and foundations.