Can AI flag disease outbreaks faster than humans? Not quite
Comedians are making their return to the White House Correspondents’ Dinner after last year’s hiatus.
Kenan Thompson of “Saturday Night Live” and Hasan Minhaj of Netflix’s “Patriot Act with Hasan Minhaj” will headline this year’s dinner, which takes place April 25.
Presidents and first ladies have traditionally attended the dinner, which serves as a celebration of the First Amendment as well as a fundraiser for college scholarships. Reporting awards are given out as well.
But President Donald Trump has skipped the dinner throughout his presidency and instead has elected to hold campaign rallies. Just four days before last year’s dinner, the White House announced that administration officials would be joining Trump in boycotting the dinner.
The White House declined to comment about whether the president would attend this year.
Last year’s dinner featured Pulitzer Prize-winning author Ron Chernow after some dinner attendees and commentators complained that a sharply anti-Trump performance by comedian Michelle Wolf in 2018 was too pointed and unfairly targeted then-White House press secretary Sarah Sanders.
Thompson will serve as this year’s host. Minhaj will be the featured entertainer.
Did an artificial-intelligence system beat human doctors in warning the world of a severe coronavirus outbreak in China?
In a narrow sense, yes. But what the humans lacked in sheer speed, they more than made up in finesse.
Early warnings of disease outbreaks can help people and governments save lives. In the final days of 2019, an AI system in Boston sent out the first global alert about a new viral outbreak in China. But it took human intelligence to recognize the significance of the outbreak and then awaken response from the public health community.
What’s more, the mere mortals produced a similar alert only a half-hour behind the AI.
For now, AI-powered disease-alert systems can still resemble car alarms — easily triggered and sometimes ignored. A network of medical experts and sleuths must still do the hard work of sifting through rumors to piece together the fuller picture. It’s difficult to say what future AI systems, powered by ever larger datasets on outbreaks, may be able to accomplish.
The first public alert outside China about the novel coronavirus came on Dec. 30 from the automated HealthMap system at Boston Children’s Hospital. At 11:12 p.m. time, HealthMap sent an alert about unidentified pneumonia cases in Wuhan. The system, which scans online news and social media reports, ranked the alert’s seriousness as only 3 out of 5. It took days for HealthMap researchers to recognize its importance.
Four hours before the HealthMap notice, New York epidemiologist Marjorie Pollack had already started working on her own public alert, spurred by a growing sense of dread after reading a personal email.
“This is being passed around the internet here,” wrote her contact, who linked to a post on Chinese social media forum Pincong. The post discussed a Wuhan health agency notice and read in part: “Unexplained pneumonia???”
Pollack, of the volunteer-led Program for Monitoring Emerging Diseases, known as ProMed, mobilized a team to look into it. ProMed’s more detailed report went out about 30 minutes after the terse HealthMap alert.
Early warning systems that scan social media, online news articles and government reports for signs of infectious disease outbreaks help inform global agencies — giving international experts a head start when local bureaucratic hurdles and language barriers might otherwise get in the way.