Deconstructing Surveillance Week 4 — Scientific Management of Labor

Nick Rabb
10 min readSep 25, 2023

As a reminder, this is part of a series of write-ups based off a class I’m teaching at Tufts University called Data and Power: Deconstructing Surveillance. If you would like more of a description of what the class is, check out the post from Week 1. If you want to keep up with this series, you can subscribe to receive email updates or on Medium where the write-ups are posted!

This week, we tackle less content, so prepare yourself for a shorter write-up. For class, we spent some time reading from Emily Guendelsberger’s On the Clock, and the second half of the week is spent starting some mid-semester projects. We are also ending the first section of the class (which is broken up into three parts: problem, practice, and application), and concluding our discussions on the “problem” aspect of surveillance systems. Next, we will move onto the “practice” aspect, which will have us learn and think about theories of change to address the problems that we identified in these past weeks.

But we end this first section with another important site of surveillance: the workplace. Guendelsberger’s experiences and the meaning she makes from them are crucial for our understanding of the effects of technological surveillance on workers. This should raise some questions — especially for those of us who construct or maintain these types of systems — regarding our stance on workers’ rights, power dynamics in the workplace, and how we think labor should be structured.

Scientific Management

The “Fulfillment” Center

Guendelsberger opens the chapter with a short description of what she has discussed throughout the preceding parts of the book: what work at an Amazon warehouse (euphemistically called “fulfillment centers”) looks like. She spent time working as a “picker,” someone who roams the warehouse looking for certain products to pick up and deposit into bins where others sort and package them for distribution.

However, the roaming is not self-guided, but dictated to you by a smart scanner, which both tells you what to pick next, how to get there, and how long you have to do it. It constantly knows your location, and times how long it takes you to go from one item to the next. In essence, you do not think, you simply follow the dictates of the scanner.

If you are too slow while picking items, you receive a strike. Too many strikes, you are fired.

Guendelsberger also notes that the paths given to pickers are routed not necessarily in the most efficient way, but in a way so as to keep workers from talking with each other. She notes that despite working in a warehouse with many others, she almost never crosses paths with anyone else. Talking with your coworkers is, of course, time lost; and time lost is money lost. Moreover, workers who talk with each other may get some funny ideas in their head about pushing back against their terrible work conditions once they realize they are all in pain and exploited.

It should also be noted that this work, Guendelsberger shares, is excruciatingly painful. The warehouse also contains vending machines stocked with free painkillers. She recalls that the constant walking, bending over, squatting, carrying, take an enormous toll on her body and others’, causing them to truly need the painkillers to simply survive.

The scene described is nothing less than dystopian and heart-breaking.

Taylor’s Dream

As dystopian as the warehouse grind sounds, it is not without historical precedent. Guendelsberger is a journalist by training, and knowledgeable about labor history in particular. She contextualizes this process by describing the history of industrialization; specifically, the contributions of Frederick Winslow Taylor.

Taylor’s main contribution to history is his 1911 Principles of Scientific Management, in which he formulated techniques to “scientifically” control labor for maximum efficiency. His infamous story involves him timing workers carrying pig iron with a stopwatch, measuring how many bars the best worker can carry in a day, and then holding all other workers to that standard. He justifies this by arguing that he scientifically, objectively measured the capability of workers, and anyone not meeting the standard is obviously being intentionally lazy.

Part of his scientific rationale was also breaking complex tasks into a series of simple tasks, each repeatable and able to be performed by any worker. In this sense, he also sought to demystify what he called the “black magic” performed by skilled workers — a level of craftsmanship that prohibited labor managers from understanding the work being done, and subsequently prohibited them from measuring their productivity and replacing them with other workers if efficiency standards were not met.

In this way, the picture Guendelsberger paints is that before industrialization and scientific management, workers had much more power over their labor — fewer bosses, more skilled labor, and more respect for that skilled labor. Taylor’s method of controlling labor — breaking it into simple tasks, devising measurements of efficiency, making workers replaceable — reduced worker power and autonomy.

We should note that Taylor’s scientific management is an excellent example of Foucault’s theory of disciplinary power: surveillance, examination, and normalization through disciplinary action. Workers are surveilled so that their labor can be measured, it is examined through those measurements, and if they do not make the cut, they are disciplined by being fired or having their pay cut.

Moreover, we see through Guendelsberger’s recounting of Taylor’s writing, that his surveillance also created hierarchies in the manner described by Browne from last week’s reading. Taylor makes a clear division between laborers and managers, calling workers “stupid,” “phlegmatic,” and “[resembling] in his mental make-up the ox than any other type.” This distinction, between intelligent work of managers and mindless work of laborers, creates and reifies class boundaries, and fuels classist oppression.

Guendelsberger notes that this type of thinking was widely adopted by American business management, especially in the neoliberal period which sought to break the power of labor and reassert the supremacy of capital ownership. She also notes that these surveillance practices were more widely adopted in that period as well, while the power of labor was crushed, and resulted in nearly 50 years of labor productivity increases while wages were kept stagnant.

Data from the U.S. Bureau of Labor Statistics

Taylor’s theorizing around scientific management was his attempt at alleviating the poverty that he saw in his society, imagining that workers could become more productive, earn more money, and pull themselves out of their impoverished state. As the graph above demonstrates, he could not have been more tragically wrong. The graph below illustrates what his vision would have looked like, but the reality is that his process, taking power away from workers, allowed capital holders and managers to take all of the profit from productivity gains and force replaceable, precarious workers to put up with low wages.

Technological Management

This story should, as always, make us think a bit more carefully about the technologies that we are analyzing. Amazon’s scanner is one example of data-driven surveillance that gives extraordinary power to managers by making workers entirely robotic and replaceable. The social conditions surrounding this technology — lack of employment opportunities to switch to, incredible economic inequality driving people into precarious working situations, lack of unionized labor prohibiting workers to fight back — are equally as important to analyze.

Technology workers at Amazon who designed the scanner were likely not imagining that it was going to be a technology driving warehouse workers to the free painkiller vending machine. Their managers most likely told them they were building something to increase efficiency, help warehouse workers not have to think so hard about their job, and that it would be a challenging problem to solve. But we can ask if they should have been more aware of the possible consequences. We can ask if it is the responsibility of those technology workers to be thinking about the potential negative consequences of their work, and rejecting something that crosses their line.

These questions are important in more scenarios than simply the Amazon warehouse scanner. There are likely hundreds if not thousands of systems, that technology workers are designing every day, which aggregate data about workers, measure it through algorithmic evaluation, and generate some report that managers can use to police or discipline them. Guendelsberger’s other two examples, which she learned of through working at these companies, are surveillance technologies in call centers and at McDonald’s. Which others can you think of?

Reflection: Let’s ask some more specific questions about the intersections of labor and technological surveillance:

Is efficiency worth the surveillance and discipline of workers? How much do you encounter the language of efficiency when hearing about technological advancements?

What technologies do you know of that are, in essence, “deskilling” workers? When workers’ labor is made more simple and replaceable, what consequences may this have for society or an economy more broadly?

If you were a technology worker being pushed to make a system that you evaluated as harmful, what would you do?

Finally, can you imagine a way of empowering workers through technological development? What would a system look like that would give more equal power to Amazon warehouse workers?

I want to end this section by noting that, in class, we’ve encountered some particular difficulties with questions like the last two posed above. These questions preempt the readings and discussions we will have in the next major course section on “practice”: how to think about taking ethical action given the critiques we have of the systems we examined. But even before we learn some of the techniques, we need to learn how to stretch our imaginative muscles. The final question, asking about a system that would benefit workers, is an exercise in creativity and imagination.

We have had a hard time in class doing this imaginative practice. To fix what we find broken about these systems, we must be radically imaginative. We have to figure out what we think is ethical, and play around with creating a theoretical system that would embody those ethics — not an easy task. But we rarely are given the opportunity or container to practice that kind of imagination. Much of our social discourse is critical and despondent, leaving no room for imagining what a better world would look like. We must push back on this social trend and strengthen our imaginative muscles, which we will do in earnest in the following weeks.

A Synthesis of Material Thus Far

At this point in the semester, we also work towards synthesizing all that we have learned so far with a project. Students will be grouping up and picking a surveillance measure to analyze along some of the lines we have introduced through our material and discussions. They are tasked with answering the following questions about their surveillance measure:

  • What were the ideas justifying this surveillance measure? Was there ‘problem or crisis’ the surveillance measure is/was intended to solve?
  • How does the surveillance measure enact a process of normalization (hint: remember the process of surveillance, examination, and normalization)? Does it interact with any oppressive social logics to create hierarchies along the lines of race, class, gender, or others?
  • How does this surveillance measure interact with both technologies and social processes?
  • How do you judge the impacts of this surveillance measure — both potentially positive and negative? For all impacts, explain why you judge these as positive or negative. If you are struggling to come up with reasons, think of several dimensions we discussed during the preceding weeks (exploiting the surveilled, generating inequality, creating hierarchies, power dynamics, etc.)

Often, the best way to learn is by doing, so this project gives us all an opportunity to put our skills to the test and analyze a real surveillance measure in the world.

As an important note, this work will also span the second half of the week, and the following two weeks, as student groups will present their findings to each other and then reflect on the process. The write-ups for the following weeks will continue (fear not!), but may contain less content sharing and more reflection and analysis.

For next week

Community announcements

None! This week there were no announcements sent in.

Readings and reflections

For next week, we will not read anything! Enjoy the break for your brain.

Lucky for you, however, even though students will not have any reflection assignment to do this week, I will include some reflective questions on our reading from Guendelsberger that may be interesting to the learning community:

As Guendelsberger described her experience being surveilled at the Amazon warehouse, we likely cannot help but start to reflect on our own surveillance in the workplace. Though it may not be as terrifying as the warehouse scanner, we are likely subject to some sort of examination and normalization. Moreover, we also may be subject to this type of “deskilling” that Guendelsberger describes as a result of Taylorism’s management style.

What types of data are collected on you so that you perform as a “good employee?” Do you think that the way you’re being molded as a worker is beneficial to you as much as it is to the employer?

Then reflect on the ways that your labor may intersect with certain processes or technologies that both (1) make measuring your labor easier, and (2) make your job replaceable. What is your assessment of these axes of surveillance and power?

Thanks for reading along, and as a reminder, if you want to keep following these weekly updates or share them with friends, either follow my blog on Medium, or subscribe to the email list via this Google Form.



Nick Rabb

PhD candidate in Computer Science and Cognitive Science at Tufts University, organizer w/ Dissenters, MA Peace Action, formerly Sunrise Mvmt. Philosophy nerd.