How Uber Uses Psychological Tricks to Push Its Drivers’ Buttons - by Noam Scheiber ; graphics by Jon Huang -
The New York Times
Employing hundreds of social scientists and data scientists, Uber has experimented with video game techniques, graphics and noncash rewards of little value that can prod drivers into working longer and harder — and sometimes at hours and locations that are less lucrative for them.
(…) To keep drivers on the road, the company has exploited some people’s tendency to set earnings goals — alerting them that they are ever so close to hitting a precious target when they try to log off. It has even concocted an algorithm similar to a Netflix feature that automatically loads the next program, which many experts believe encourages binge-watching. In Uber’s case, this means sending drivers their next fare opportunity before their current ride is even over.
(…) pulling psychological levers may eventually become the reigning approach to managing the American worker [Nota: pourquoi American, on sait pas]
(…) other “gig economy” platforms are also involved. Uber’s main competitor, Lyft, and popular delivery services like Postmates rely on similar approaches. So do companies and individuals posting assignments on crowdsourcing sites like Amazon Mechanical Turk (…)
Of course, many companies try to nudge consumers into buying their products and services using psychological tricks. But extending these efforts to the work force is potentially transformative.
(…) Some local managers who were men went so far as to adopt a female persona for texting drivers, having found that the uptake was higher when they did.
(…) whether they enjoy it is separate from the question of #agency — whether they have it, or whether the company does.
(…) Kelly Peters, chief executive of BEworks, a management consulting firm specializing in behavioral science, argued that the same data that makes it easier for Uber to nudge drivers into working an additional 30 or 60 minutes also makes it hard to escape the obligation to look after them.
(…) It is … not too hard to imagine a future in which massive digital platforms like Uber have an appetite for tens of millions of workers