The Federal Trade Commission (FTC) hosted its fifth annual PrivacyCon on July 21, 2020. This was the first time the one-day conference was fully remote, rather than in person at the FTC’s Bureau of Consumer Protection in Washington, D.C.
PrivacyCon should not be confused with Comic-Con, the annual pop culture extravaganza that began the following day with over 350 virtual panels extending over nearly a week. Perhaps the thousands who show up there each year in San Diego with colorful costumes will not miss a beat as they turn on their Zoom cameras to participate in a way never imagined when this year’s Comic-Con was organized.
Among the cutting-edge technologies being employed by public health experts to map various aspects of COVID-19 both at home and abroad, artificial intelligence (AI) faces a test under life-and-death circumstances. The ability of AI systems to undertake pattern detection and predict the spread of the pandemic and its treatments is promising. The benefit of machine learning includes its powerful ability to analyze historic data to find key variables. This task is dependent upon humans, however, specifically in the ability of data scientists who can work on creating data sets that supercomputers then can model. On a global basis, this will require pooling both technical and human resources.
Given the unprecedented nature of COVID-19, historic data inputted for AI analysis may be of limited value. Real-time data comparing growth curves in countries around the world, along with population and demographic information by neighborhood, may prove to be a better vein for producing actionable data anywhere and everywhere. Automated machine learning also may improve the efficiency of data scientists, enabling them to focus on new data generation while relying on computer-to-computer analysis of massive-scale number crunching.
Continue reading “Deploying U.S. AI Leadership for COVID-19”