When research participants were asked to bet on either their own prediction ability or the clearly superior acumen of an algorithm, they were more likely to bet on their own ability if they had seen that the algorithm was imperfect, according to a team from the University of Pennsylvania’s Wharton School.

This is a case of algorithm aversion, Walter Frick writes. People don’t like to rely on algorithms, especially if they’ve seen them fail, even a little. To err may be human, but when an algorithm makes a mistake, we’re not likely to trust it again.

(Source: HBR.org)

Published in Dawn, Economic & Business, March 23rd , 2015

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