Labor Under Many Eyes: Tracking the Long-Haul Trucker


Karen Levy (@karen_ec_levy) is an associate professor in the Department of Information Science at Cornell University and an associate member of the faculty at Cornell Law School.


Karen Levy (@karen_ec_levy) is an associate professor in the Department of Information Science at Cornell University and an associate member of the faculty at Cornell Law School.

This post is part of a symposium on Worker Surveillance & Collective Resistance. Read the rest of the posts here.


In 2017, the United States government required that all long-haul truck drivers install electronic logging devices, or ELDs. ELDs were intended to address one of the most pervasive, longstanding, and notorious problems in trucking: fatigue. Truckers are famously overworked and underslept, and digital monitoring was intended to automate truckers’ compliance with federal regulations that constrain the number of hours truckers can legally drive each day and each week.

For a variety of reasons—which I detail in my new book, Data Driven: Truckers, Technology, and the New Workplace Surveillance—the ELD mandate has had limited success in achieving its goals of making the roads safer and reducing trucker fatigue. But it has achieved something else: through federally required digital monitoring, the government has provided an essential foundation for surveillance of truckers by their employers and other profit-seeking companies.

An analogy that suits this situation: imagine that the government required every worker in the industry to get a cell phone that makes calls. On its face, such a requirement might seem like not so big an intrusion (and perhaps even justifiable from a safety perspective). But of course, it’s nearly impossible to find a phone that only makes calls—it’s far more likely that the device also connects to the internet, has GPS capability, takes photos, and possesses all the other features that we’ve come to expect in modern cell phones. By virtue of this commonplace feature bundling, the government has effectively ordered everyone to get a smartphone (with all the monitoring capacities that it entails) without explicitly doing so. The same dynamics are at play with electronic logging devices. The federal regulations and bundled technologies create a scaffold that supports a much broader swath of surveillance by other parties.

In trucking, the government mandate serves as the backbone for corporate surveillance: now that companies have had to buy electronic logging devices, they may as well benefit by gathering driver performance data. Often, the regulatory functionality of the ELD is merely a module in a broader “fleet management system,” through which companies gather and run analytics on all kinds of fine-grained, real-time information about how truckers are doing their work—how fast they’re driving, how much fuel they’re using, whether they’re taking a different route than the mapping software recommends, how tired a driver’s body is (inferred by things like AI-augmented camera systems that monitor drivers’ eyelids for signs of tiredness).

And it doesn’t end there. In addition to the eye of the government and the eye of the manager, third party companies also stand to benefit financially from the harvest of truckers’ data via these devices. Data collected about fleets of truckers and their behaviors are extremely valuable to insurers, to companies that sell services (like overnight parking reservations) to truckers, and to other firms.

I call this phenomenon surveillance interoperability. Governments, trucking firms, and third-party companies have different goals, and put different data streams to use in reaching those goals—but each type of surveillance is innately compatible with one another. In the trucking context, thinking about government data collection, or corporate surveillance, or third-party data harvesting in isolation gives an incomplete picture of how tightly the three are bound up together: each is part of a mutually enforcing whole.

Surveillance interoperability clearly has a strong technical dimension: the electronic logging device is a black box that facilitates the collection of multiple types of data about the trucker, to be put to use by different observers with various forms of power over him. But there are other important dimensions to the phenomenon, too. Surveillance in trucking is legally interoperable, in that the federal mandate buttresses corporate surveillance built on top of these systems. (Regulators, for their part, knew this is what they were doing; they acknowledged that many firms would meet the legal requirements by purchasing fuller-featured management systems, and premised some of their cost/benefit calculations on such systems.)

The regimes interoperate economically as well. The ELD is a legal tool with a business rationale: the government mandate is a compelling reason for trucking companies to consider deploying broader monitoring technologies. Larger firms—which could both more easily stomach the costs of the mandate and derive greater benefits from the fleet-wide analytics they could run based on ELD data—voiced support for the mandate in part because it gave them a competitive advantage over smaller firms. And the trucking press has described third parties’ desire to capitalize on ELD data as a “gold rush”; the only parties not poised to benefit are truckers themselves.

Finally, and critically, the surveillance regimes truckers face are socioculturally interoperable. Trucking is an occupation valued for its independence and autonomy. Truckers tend to bristle at too much oversight from law enforcement, from employers, from insurers, or from anybody else—especially anybody deigning to tell them how to do their jobs. The ELD, however, represents the confluence of all these overseers. In trucking, the worker is under everyone’s eye all at once.

The layering of government, employer, and commercial surveillance into one apparatus stacks the deck against the worker, and is a marked affront to the dignity of an essential profession. And, ironically, there’s little evidence that the ELD accomplishes the ostensible safety goals that led to its adoption in the first place: in fact, truck crashes in some segments of the industry increased after the mandate, and truck-crash fatalities hit a thirty-year high. Truckers and analysts agree on the underlying reason: the technological regime creates extra rigidity in the timekeeping rules, leading drivers to compensate by speeding and otherwise seek ways to make up lost time. In one industry survey (albeit a nonrepresentative one), 78 percent of drivers reported that after the ELD mandate, they felt more pressure to drive when they felt it was better to stop.

On top of this, longtime professional drivers, who tend to have the strongest safety records, are more often compelled to “hang up their keys” because of the distrust and loss of dignity in their occupation evinced by surveillance. That leaves more openings to be filled by younger drivers (even 18-year-olds) with fresh CDLs, who’ve never known the industry any other way and may be less resistant to the surveillance it entails; younger drivers who are less safe and less capable than the old hands.

The interoperable surveillance truckers face may be a bellwether of things to come in other workplaces, especially in regulated industries. Regulatory compliance monitoring may come to support broader forms of workplace surveillance in industries from finance to transportation to agriculture. When surveillance technology serves complementary goals for powerful parties, what hope is there for workers to push back?

One prospect is to compel de-bundling of related technologies—a conceptual cousin of arguments made in the antitrust context. The idea of the “governance seam,” developed by Paul Ohm and Brett Frischmann, may be instructive here—by intentionally creating friction and segmentation of a technology to constrain data collection or use, we might limit the degree to which regulatory data collection scaffolds other forms of surveillance. (Such a limitation was discussed by regulators, but was ultimately unsuccessful, in the trucking context.) Data deletion and minimization policies may also aid in curbing re-use of regulatory data by employers and other private actors. But on the whole, it’s most critical to recognize what workers find themselves up against: a surveillance regime that is greater than the sum of its parts.

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