March 12, 2018


Basic Income in a Just Society (BRISHEN ROGERS, 5/15/17, Boston Review)

Consider the life of a truck driver forty years ago versus today. In 1976 long-haul truck drivers had a powerful, if flawed, union in the Teamsters and enjoyed middle-class wages and excellent benefits. They also had a remarkable degree of autonomy, giving the job a cowboy or outlaw image. Drivers had to track their hours carefully, of course, and submit to weigh stations and other inspections of their trucks. But dispatchers could not reach them while they were on the road, since CB radios have limited range. Truckers would call in from pay phones, if they wanted. 

No longer. Trucking companies today monitor drivers closely through "telematics" devices that gather and analyze data on their location, driving speed, and delivery efficiency. Some even note when a driver turns the truck on before fastening his seat belt, thereby wasting gas. As sociologist Karen Levy has shown, some long-haul trucking companies use telematics to push drivers to drive for all the hours permitted per day under federal law, at times waking them up or even overriding drivers' own judgments about whether it is safe to drive. UPS has used the technologies to reduce its stock of drivers, and many have noted the stress that "metrics-based harassment" puts on workers.

While the specter of self-driving vehicles is out there, this is the current reality for many drivers and will be for the foreseeable future. We have seen stunning advances in autonomous vehicles in recent years, but there is a vast difference between driving on a highway or broad suburban streets in good weather conditions and navigating narrow and pothole-filled city streets, not to mention making the actual delivery to houses, apartments, and businesses. As labor economist David Autor and others have argued, we are nowhere close to fully automated production or distribution of goods, since so many jobs involve nonrepetitive tasks. In other words, the reports of the death of work have been greatly exaggerated.

Technological development is nevertheless altering the political economy of labor markets in profound ways. As we can see in the truck driver example, many firms are deploying information technologies to erode workers' conditions and bargaining power without displacing them.

And of course truck drivers are not alone. Many other firms today use advanced information technologies to push for more efficiency, in the process reducing workers' discretion, ultimately requiring them to work harder, faster, and for less. For example, where once taxi drivers' folk knowledge of the optimal path from A to B in a crowded city was a valuable skill, now Uber and Lyft can calculate the best route through GPS technology and machine learning processes based on data gleaned from hundreds of thousands of trips.

Other technological innovations make it easier--which is to say more efficient--to purchase labor without entering formal employment relationships and accepting the attendant legal duties. In the past firms tended to employ workers rather than contractors, or to pay employees above-market wages, in scenarios where it was difficult to train or monitor them. Workers who felt valued in this way would work diligently and remain loyal toward firms, ultimately reducing overall labor costs.

Again Uber's model helps illustrate. The company's app reduces consumers' and drivers' search costs significantly. Rapid scalability reduces Uber's costs of identifying and contracting with new drivers and riders; its GPS-based monitoring of its drivers enables it to know whether they are speeding or otherwise driving carelessly and whether they are accepting a sufficient number of fares; and its customer rating system enables it to manage an enormous workforce without managerial supervision. The net result is an economic organization of global scope based largely on contract where the firm disclaims any employment relationship toward its workers and therefore any employment duties toward them.

To be clear, there are powerful arguments that Uber drivers meet the legal test for employment, given the company's pervasive control of their work and its economic power over them. But given the ambiguities of current law, Uber has few economic incentives to bring drivers inside the firm, making them employees, or to extend them generous wage and benefit packages. Similarly Amazon's analytics help it to keep wages low: with barcode scanners tracking pickers' and packers' efficiency, the company does not have to pay workers as well to keep them motivated.

Finally, extensive data about market structures and consumer demand can enable firms to exert power over their suppliers or contractual partners, driving down costs--and therefore wages and conditions--through their supply chains. Walmart has long leveraged its unparalleled market data to estimate the lowest possible price suppliers will accept for goods, putting downward pressure on their profits and their workers' wages. Amazon does the same today, and franchisors such as McDonald's set prices and detailed product specifications for their franchisees.

Many firms today have substituted algorithmic scheduling for middle-managers' local knowledge, using data on past sales, local events, and even weather forecasts to schedule work shifts. A Starbucks employee, for example, has little schedule predictability since she is at the mercy of the algorithm, and a McDonald's worker can be sent home early if computers say sales are slow. This push to limit labor costs through finely tuned scheduling practices also alters workplace norms, since workers cannot appeal to a computer's emotions in asking for more or less time, a raise, or a slower pace of work. The net effect of all of this is that power in our labor and product markets is increasingly concentrated in a few hands.

Crucially such management techniques and new production strategies are often more efficient than the status quo. Amazon has undeniably lowered prices for goods through its use of automation. Similarly a recent MIT study calculated that just three thousand multi-passenger cabs using a version of Uber's algorithm could serve Manhattan's need for taxis. The potential benefits here are staggering, especially if coupled with a modern mass transit system: shorter commutes, less car ownership, less pollution, and more urban space.

But the line between innovation and exploitation is far from clear. While some workers will thrive as their unique skills and talents are rewarded by new technologies, many others will have less autonomy, less generous wages, less time for social connection, and unpredictable schedules.

And the point of an economy is to create wealth more efficiently, not to maximize labor.

Posted by at March 12, 2018 7:31 AM