CONCEPT
The Polanyi Paradox
David Autor’s 2014 name for Michael Polanyi’s principle that we can know more than we can tell—applied to automation: tasks can only be automated to the extent they can be specified, and a vast domain of economically valuable human work resists specification because it consists of tacit knowledge.
In 2014 the labor economist David Autor gave a name to something that had been sitting in the employment statistics for three decades without one. The pattern was this: automation had devastated middle-skill, routine work—bookkeeping, assembly, data entry—while leaving largely untouched both the high-skilled professional work at the top of the wage distribution and the manual, physical, perceptual work at the bottom. The naive story was that machines take the unskilled work and leave the high-skilled. The data refused that story: what machines had taken was not the unskilled work but the
explicit work, the tasks whose procedures could be fully specified, regardless of whether the specification was high-status or low. What resisted automation was the
tacit: the tasks performed by people who could not say, in complete rules, how they did them. Autor called this the Polanyi paradox, attributing it to
Michael Polanyi’s 1966