Karen Levy’s book Data Driven, an incisive and accessible sociolegal study of workplace surveillance in the trucking industry, begins with a tale of superheroes. These superheroes are machines from a far-off world dedicated to saving humanity from other machines bent on our destruction. (Think “The Transformers.”) The problem is: Our would-be saviors can’t move. They’ve worked too hard for too long, saving humanity from all sorts of harm, and now, by law and by design, they must rest.
Levy, a professor in Cornell University’s Department of Information Science, tells this story, drawn directly from the pages of a trucking industry periodical, to introduce us to the electronic logging device, or ELD. ELDs are now integrated by law into every commercial truck driving across state lines. They are designed to force compliance with federal “hours-of-service” regulations, which limit the number of hours truckers can drive before taking rest breaks. Like our would-be robot saviors, trucks constrained by ELDs cannot move when their drivers have reached their hours limits. That isn’t necessarily so bad; trucker fatigue is dangerous to truckers and everyone else on the road. But, as Levy explains, ELDs are a lot more insidious.
ELDs treat the symptom, not the disease. If the symptom is fatigue, the disease is the trucking industry’s perverse economic incentives. Truckers are paid by the miles they drive, and they are paid nothing during the many hours of fueling, loading, unloading, and bathroom and meal breaks necessary to doing their jobs. (Pp. 36-48.) Plus, ELDs do more than trigger federal rest mandates. They reveal to employers when, where, and how fast a trucker is driving, when and for how long they have been resting, and when and where truckers are doing something they shouldn’t. And that is Data Driven’s central story. ELDs were sold as a new technology that would make trucking (and driving) safer. But they also enable extensive workplace surveillance by trucking companies and by the state, give management weapons to manipulate their employees, and perpetuate extractive capitalism.
Data Driven, like much of my own work, explores the gap between the law on the books—ELDs in this case—and the law on the ground, including the way the law is practiced, understood, experienced, and resisted in the real world. The book is based on years of extensive field research. Levy interviewed truckers at truck stops, read their literature, met with regulators and management, sat in on meetings, engaged with labor organizers, all while upholding ethical standards as a sociolegal researcher. Based on this work, Levy finds that ELDs are legal creations, economic tools, and cultural objects all at the same time. They help regulators enforce the law to the letter. They disrupt long-standing norms among truckers, particularly about their knowledge of the road and their independence. And they are part of a larger system of surveillance that helps firms force employee alignment with corporate goals. (P. 55.)
A particularly vivid exchange explores the last point. (P. 61.) One afternoon, starting at 12:57 PM and continuing for the next 90 minutes (sometimes at one-minute intervals!), a trucker received several messages from management: “Are you headed to delivery?” “Please call.” “What is your ETA to delivery?” “Need to start rolling.” “Why have you not called me back?” The trucker was sleeping; management didn’t care. “Why aren’t you rolling? You have hours ….” Having hours refers to additional time before legally mandated rest. Seven minutes later came the next message insisting the trucker get back on the road. Seven minutes later comes another one. The trucker responds: “Bad storm. Can’t roll now.” Three minutes later, management chimes in: “Weather Channel is showing small rain shower in your area, 1-2 inches of rain and 10 mph winds ???”
Workers, many of whom chose this grueling job specifically for its independence, now have employers looking over their shoulders. But disrupting trucking’s cultural norms is the tip of this iceberg. Having hours is a quantified metric, a decontextualized number that presumes that the only barrier to driving is the federal rest mandate. Truckers also get tired, have to use the restroom, and need to eat. “Having hours” elides all of that. Then comes the Weather Channel. Rain “in your area” says little about rain “where I am right now.” Nor does it speak to driving conditions; even light rain “in your area” can mean slippery conditions, landslide risks, and other dangers from hours of heavy rain.
ELDs, just like algorithms that purport to process large data sets try to predict people’s behavior, privilege strict and inflexible data analysis over holistic assessment and discretion. They presume that numbers tell the whole story, or at least enough of a story to make policy. As Levy shows, numbers miss the realities of trucking. (Pp. 50-51.) If you were told you had around 10 hours to complete a journey, you’d drive much more safely than if you were told you must arrive in exactly 10 hours or else. Why? The former gives you flexibility; you can drive faster when it’s safe and slower when you need to; you can factor in bathroom, meal, and rest breaks without stressing that you’re going to be a few minutes late. The latter incentivizes recklessness. The ELD turns trucking into a constant barrage of threats.
Data Driven concludes by speaking to the larger message of the ELD mandate. Faced with an epidemic of dangerous trucker fatigue, policymakers turned to surveillance and technology design rather than to addressing the underlying economic incentives that push truckers to drive while tired in the first place. (P. 153.) A richer, worker-protective solution should have been to pay truckers for their work, not for their miles driven. This would include what truckers call “detention time,” or the hours spent loading and unloading, during which they are at the mercy of dock workers and other laborers who operate on their own schedules and have radically different payment structures and incentives. But no, the neoliberal policymakers of late capitalism chose surveillance. They chose a weapon of managerial control rather than a structural change. In so doing, the trucking industry colluded with policymakers to socially construct the ELD as a tool of social control, and they made the roads more dangerous as a result.
In the end, Levy is right to warn us that truckers are the canaries in the coal mine of workplace surveillance. (P. 9.) Employers may have always kept watchful eyes on their employees, but things are worse now. Remote workplaces like trucks or home offices are no longer immune from tracking. The data—collected from inputs like wearables and social media—are more diverse. The analytics, now driven by complex algorithms, are more invasive. Modern workplace surveillance extends even beyond systems administrators knowing when you’re checking Instagram. Our bosses are watching everything; Levy’s outstanding Data Driven opens our eyes before it’s too late.
