May 7, 2021
Federal officials are reporting that the Food and Drug Administration is poised to authorize Pfizer’s COVID-19 vaccine for children ages 12 to 15 by early next week—just as Canada became the first country to do so on Wednesday of this week. Pfizer has said they will seek out emergency authorization for even younger kids by the fall. But as most countries still lag far behind the United States in vaccine access for adults, public health officials are questioning the ethics of prioritizing American teens over adults from other countries.
Since the start of the pandemic, we’ve equated getting out of this mess with the concept of herd immunity—when a certain percentage of the population is immune to a disease, mostly through vaccination.
With COVID-19, experts have said we need somewhere around 70 to 90% of the population to be immunized to meet this goal. Now that all adults in the U.S. are eligible for the vaccine, how far are we from that goal? And what is our trajectory?
Some experts now say with variants and vaccine hesitancy, herd immunity may not be possible here in the U.S. Joining Ira to break down this and other coronavirus quandaries is Angela Rasmussen, research scientist at VIDO-InterVac, the University of Saskatchewan’s vaccine research institute in Saskatoon, Saskatchewan.
In 2012, a computer program named Dr. Fill placed 141st out of some 660 entries in that year’s American Crossword Puzzle Tournament, a competition for elite crossword puzzle solvers. This year, the algorithm beat the human competition, completing the final playoff puzzle in just 49 seconds.
The A.I. relies on a collection of different techniques to make sense of a puzzle. Sometimes, a simple fact is needed—who was the First Lady before Eleanor Roosevelt? (Lou Henry Hoover.) More often, however, crossword puzzle solutions rely not just on factual knowledge, but an ability to recognize themes that puzzle constructors have embedded in the crosswords, along with an understanding of puns, homonyms, and word play. (Think: Five letters, “dining table leaves”—SALAD!) The program makes a series of statistical calculations about likely answers, then tries to fit those possibilities into the puzzle squares.
This year, researchers from the Berkeley Natural Language Processing group added their expertise to Dr. Fill’s algorithms—a contribution that may have helped push Dr. Fill to its crowning victory.
But the program isn’t infallible. This year, it made three mistakes solving puzzles during the tournament, while some human solvers completed the puzzles perfectly. It can make these errors with any unique puzzle form it’s never seen before.
Matt Ginsberg, the computer programmer behind Dr. Fill, joins Ira to talk about the competition and the advances his program has made over the years.