Is Uber an ‘Algorithmic Manager’?

The question of whether Uber, Lyft, and other ridesharing platforms “manage” the drivers who work through them is the subject of much controversy and multiple class-action lawsuits by drivers who say they are employees, not independent contractors as Uber and Lyft consider them. A fascinating new study in the International Journal of Communication explores how Uber uses “algorithmic management” to exercise control over its drivers’ work habits without technically “managing” them. The study examines several means by which Uber’s platform regulates how drivers use it:

Blind Passenger Acceptance and Minimum Fares

When active Uber drivers receive a ride request through the system, they have about 15 seconds to accept it or reject it. When Uber drivers accept a ride request, they take on the risk that the ride’s fare will not be profitable; yet, drivers are not shown destination or fare information before they accept a ride. Jason from Raleigh, North Carolina, who had driven for about a year, said, “You’re driving around blind. When it does ping, you might drive 15 minutes to drive someone half a mile. There’s no money in it in that point, especially in my SUV.” Although hiding the destination before a driver chooses to accept or decline a ride request can potentially prevent destination-based discrimination, it can also foster reduced wages for drivers. In addition, drivers risk “deactivation” (being suspended or removed permanently from the system) for cancelling unprofitable fares. …

Surge Pricing and Algorithmic Logistics Management

Among drivers interviewed and posts collected from forums, the ambiguity and resistance surrounding “surge pricing” surfaced as the most obvious intersection of data collection and information asymmetry in everyday driver experience. …

Surge pricing is unreliable for drivers: Notably, pricing is based on the passenger’s geolocation, not the driver’s. Drivers travel to surge pricing zones in search of fares advertised at a given rate, but they can and do receive ride requests from passengers in other, adjacent areas. A driver may enter a zone that is surging at 3.5x, but receive ride requests at a lower surge rate, such as 1.5x. Some drivers report that passengers game the system by placing their pick-up location pin outside a surge zone, and then calling drivers to redirect them to their actual pick-up location. … It is unclear whether surge is designed equally to optimize for satisfying passenger demand or for increasing driver earnings, but Uber’s stance against “surge manipulation” by drivers suggests the former. …

Driver Ratings and Surveillance

In the driver rating system offered to riders, passengers are empowered to act as middle managers over drivers, whose ratings directly impact their employment eligibility. This redistribution of managerial oversight and power away from formalized middle management and toward consumers is part of a broader trend in flexible labor: Companies or platforms can create expectations about their service that workers must fulfill through the mediating power of the rating system. This business model is rooted in Taylorist traditions of using worker monitoring to identify and create new efficiencies in workflows. For laborers whose work is primarily mediated electronically, worker monitoring is more passive and the prominence of control is not as perceptible. The loss of worker efficacy as power is transferred from labor to capital is not new or unique to digitally mediated labor, but digital spaces facilitate and scaffold new systems of monitoring and opportunities for remote control over workers.

Fast Company’s Sarah Kessler, who flagged the study and spoke to one of its authors, expects that it will only add fuel to the controversy over the management and classification of gig economy workers:

This research comes with a few caveats, including that people who participate in forums may be full-time drivers who are more invested in working for Uber, or they could be drivers who are less happy with their experience than the typical driver. Both could slant the results. Another study found that drivers were “generally satisfied with their level of control over assignment algorithms.” Regardless of how Uber drivers feel about it, however, the study illustrates how Uber has some control over its drivers’ work hours and decision making. It’s far from the first academic work to do so.

Some argue this control warrants a new category of worker. … [The study’s co-author Alex] Rosenblat says that she’ll leave the classification question to legal scholars, but suggests that there may be another recourse that isn’t as frequently discussed: Uber has positioned its drivers as customers who pay a commission to use its software. That could make the ways that Uber nudges them toward certain practices interesting to customer-protection agencies.