As data is collected about workers, how does it impact them and how do they respond to it?
Contemporary workplaces have increasing capabilities to log, collate, and analyze data about workers to make critical decisions about labor. This is often to the disadvantage of workers, who are monitored and surveilled in great detail. At the same time, union movements in the US have made some critical wins in the past year. For example, successful unionization efforts at major corporations like Amazon, Starbucks, and Google point to a resurgence in the labor movement. The looming role of data alongside the renewed labor movement raises the question: as data is collected about workers, how does it impact them and how do they respond to it?Understanding this is key to imagining what the future of work could (or should) become.
In this interview, we discuss research on the role of technology and data expertise in supporting worker advocacy movements conducted by Dr. Vera Khovanskaya, an NSF/CRA/CCC Computing Innovation Postdoctoral Fellow at the University of California, San Diego.
The following is an edited transcript of our conversation.
Sohyeon: To start, what were the questions drawing you into your work on data and labor unions?
Vera: While in the middle of another project on labor, I got really interested in questions about unions’ engagement with technology. How has the labor movement responded to technological change in the workplace?
Sohyeon: A lot of your work is very historically grounded — when did you make the connection there?
Vera: My research led me to a book called A Trade Union Analysis of Time Study, by William Gomberg, who, at the time, was working as the head of the Management Engineering Department of the International Ladies Garment Workers Union (ILGWU). And it was just shocking to me that a labor union spearheaded a systematic takedown of the “scientific objectivity” claims underlying the foundations of scientific management. This led me to the records of the ILGWU Management Engineering Department at the Kheel Center for Labor-Management Documentation & Archives at Cornell. These archives document the union’s strategy of hiring in-house industrial engineers to do time studies where the union thought a union time study would be useful to counter the management’s time study, as well as their efforts to assert the role of organized labor in academic and professional discourses around scientific management. My dissertation was trying to understand, how did this analysis and data work happen? And what did it do and at what cost?
Sohyeon: When you say at what cost — what is it about the relationship between data, technology, and labor that you find compelling?
Vera: Well, I think data collection isa key part of automation. People who don’t study automation sometimes think that automation is robots or mechanization. But the first step of automation is to collect data about how people do work. First you collect data about each part of the job, how long it takes, the order in which the parts are done, and what dependencies exist between tasks that are being done in sequence. This paves the way for the reorganization of work so that everybody does a smaller part, thereby rendering the worker more replaceable, and the work more amenable to mechanization.
There’s a strong centralizing tendency in the data collection and usually, it’s not good for the worker.
