What the U.K.’s pandemic exam-results fiasco tells us about algorithms and the future
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Good morning. David Meyer here in Berlin, filling in for Alan.
This pandemic is devastating in many ways, but its long-term impact on children will be one of the most terrible. That much is becoming apparent in the U.K., thanks to a fiasco around pupils’ end-of-schooling “A-level” results.
In the U.K., A-level exam results are the big determinant of university placements. Due to the pandemic, this year’s exams could not take place. So the government introduced a complex grading system that took a variety of factors—teachers’ estimates of how their pupils might have performed in the A-level exams; plus the pupils’ results from their earlier “mock” A-levels; plus information about their schools’ past performance—and ran everything through an algorithm to come up with their final grades.
The result? Downgrading for 280,000 students including, for example, outliers who were excellent performers at otherwise poorly-performing schools—and a boost in results for lackluster pupils at schools that have historically performed well. There is an appeals process, but for many it will come too late; the university places they thought they had earned are already filling up.
In short, many kids feel right now that their lives have been ruined. The result? Legal threats and a political battering for Boris Johnson’s government, plus a revolt within the examination body Ofqual.
So, what can we learn from this?
Firstly, algorithms can have a big impact on people’s lives. And if they go wrong on a massive scale—as many argue happened here—the result can be explosive. Witness these hundreds of kids protesting the debacle with a chant of “F—k the algorithm.” Many of today’s A-level students are too young to vote, but they won’t be when the next national election rolls around, several years from now.
Secondly, algorithms can entrench existing biases and inequalities. (See also: the now-scrapped algorithm that was being used by the U.K.’s immigration authorities—whether deliberately or not—to prioritize visa applications for white people.) As the political philosopher Annette Zimmermann wrote about the A-levels furore: “Statistical models often pick up on large-scale historical patterns or racial, gender and class inequalities and replicate them as data patterns, while simultaneously endowing these patterns with an air of certainty, neutrality and objectivity.”
Thirdly, if an algorithm is going to be used for automated decision-making, it has to be easy and meaningful to appeal that decision. That rule is part of the EU’s General Data Protection Regulation (GDPR) and it may have been broken in this case.
And finally, a return to the start of this essay: kids may be less likely to die as a result of COVID-19, but the pandemic is messing up their lives in ways we cannot yet fathom. Many will come out of it with damaged faith in our institutions and establishments—a trend that’s already had plenty to fuel it in recent years.
There really will be no return to our old normality. More news below.
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Belarus and Russia
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AROUND THE WATER COOLER
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This edition of CEO Daily was edited by David Meyer.