Labor & Tech Reading List

Emergent issues at the intersection of labor, technology, and worker rights

This reading list was compiled by Alexandra Mateescu and Eve Zelickson, researchers on the Labor Futures initiative at Data & Society.

This reading list serves as an introductory roadmap for exploring some of the emergent and pressing issues at the intersection of labor, technologies, and worker rights. While largely US-centric, these readings reflect transnational trends in the ways labor is being reconfigured and highlights writing on automation, workplace data collection and digital surveillance, precarious work, and efforts to imagine better futures for workers.

This list is not a comprehensive syllabus; it curates important recent scholarly research, investigative journalism, and insightful essays that highlight the voices of workers, scholars, activists, and journalists looking at technological change in the workplace through a critical lens.

Table of Contents

Section 1: Automation and Invisible Labor

• Automation and Robot Futures
• Invisible Labor

Section 2: Surveillance and Algorithmic Control

• Data and Workplace Surveillance
• Algorithmic Management

Section 3: Worker Precarity and the Gig Economy

• The Rise of Precarious Work
• Challenging the Present

Automation and Invisible Labor

Public debates about the future of work often center on concerns over a robot takeover, leading to broad swathes of the workforce rendered obsolete by automation. Will new technologies create new jobs, occupations, or industries? Or will they displace workers and concentrate wealth and power among those who own the machines? The picture is often more complicated. Automation may change the nature and quality of many jobs, and automated systems will still require maintenance and repair work that may be under-acknowledged. And while many AI systems appear fully autonomous, they often in fact conceal hidden human labor made possible by reconfigured labor arrangements and business practices. Whose labor is erased when technologies appear to work like magic? How is this invisible work devalued, underpaid, or unaccounted for?

Automation and Robot Futures

• At the 2019 Data for Black Lives conference panel session “Black People vs. Robots: Reparations and Workers Rights in the Age of Automation,” panelists discussed the impact of automation in sectors with majority Black workforces. Speakers considered the structural inequalities in access to re-skilling opportunities, the importance of reckoning with the history of slavery in relation to both universal basic income and reparations, and how to envision a just social safety net for the future.
• A Joint Center for Political and Economic Studies report based on a survey of the American workforce focuses on differences across race in how people are experiencing changes to their workplaces on issues such as workforce displacement, job security, and training.
• A report from the Institute for Women’s Policy Research considers how women, and particularly women of color, may be disproportionately affected by shifts towards workplace automation and unequal access to retraining opportunities.
• In the Roosevelt Institute report Beyond Automation, law professor Brishen Rogers argues that information technology, not automation, is the greatest threat to workers today because it grants companies outsized power over workers.
• In The Revolution Need Not Be Automated, economists Daron Acemoglu and Pascual Restrepo argue that a “single-minded focus on automating more and more tasks is translating into low productivity and wage growth and a declining labor share of value added.” MIT Technology Review provides an overview of a wide array of studies forecasting the impact of automation on jobs; each study varied significantly in their predictions of how many jobs will be lost due to automation.
• In the UC Berkeley Labor Center’s report The Future of Warehouse Work, scholars Beth Gutelius and Nik Theodore discuss how technology in warehouses likely won’t cause dramatic job loss, but instead workers will see the content and quality of their jobs shift, as jobs are deskilled and workers are forced to worker harder under more surveillance.
• The Driverless Report from sociologist Steve Viscelli, in partnership with Working Partnerships USA and the UC Berkeley Labor Center, provides an in-depth analysis of how technology, labor practices, and public policy intersect with the future of autonomous vehicles and commercial trucking jobs.
• In the wake of the coronavirus pandemic and renewed public debates about large-scale automation, Data & Society Director of Research Sareeta Amrute, Senior Researcher Alex Rosenblat, and Postdoctoral Scholar Brian Callaci argue that the role of automation does not fully account for the disappearance of good jobs, rather, companies use moments of temporary economic downturn to permanently restructure in ways that informalize work and further fissure the workplace. In a second post, they discuss the ways that management software and digital monitoring are often implemented to intensify the pace of work.
• Towards an AI Economy that Works for All, a report from Keystone Research Center, provides an analysis of AI’s likely consequences, its impact on the labor market, and an examination of policies that could more equitably distribute the benefits of AI.

Invisible Labor

• Data & Society Researchers Madeleine Clare Elish and danah boyd warn us not to call AI magic, a comparison that “denies an accounting of what went into making something work, or that it required work at all.”
• Writer Astra Taylor’s article on fauxtomation describes the overselling of automation and erasure of the “invisible human labor to make computers seem smarter than they are.”
• In their book Ghost Work, anthropologist Mary Gray and computational social scientist Siddharth Suri study the hidden labor of the global workforce that captions photos, flags and removes inappropriate online content, and powers artificial intelligence systems. In her Harvard Business Review article, Gray talks about the paradox of automation’s last mile: “as AI makes progress, it also results in the rapid creation and destruction of temporary labor markets for new types of humans-in-the-loop tasks.”
• In Justice for Data Janitors, communication and science studies scholar Lilly Irani writes on the labor divisions that exist within tech companies, such as Google, between valued, high-status tech workers and the many subcontractors working “off the books/out of sight” of the spotlights that glamorize the tech industry as a site of entrepreneurship and job creation.
• Information studies scholar Sarah T. Roberts’ book Behind the Screen: Content Moderation in the Shadows of Social Media explores the commercial content moderation industry, the hidden labor that is integral to its operations, and the psychological toll and burnout experienced by this low-wage workforce. As anthropologist and Data & Society Director of Research Sareeta Amrute’s work on the experiences of Indian tech workers in Germany shows, migrant tech workers may also be rendered hypervisible and racialized in the office hierarchies and divisions of labor entrenched and reinforced by visa regimes within tech industry workplaces.
• Journalist Adrian Chen and filmmaker Ciaran Cassidy’s short documentary The Moderators follows the everyday work life of five employees at a content moderation center in India.
• In Slate, Data & Society Director of Research Sareeta Amrute considers the rush to accelerate automation in the wake of the COVID-19 pandemic, arguing that such efforts won’t necessarily keep frontline workers safe because automation will continue to require people to fix, repair, and work alongside machines, often behind the scenes.
• Media studies scholar Luke Stark discusses the relationship between the tacit expectations of emotional labor from gig economy workers and the role of customer-rating systems that have a significant hold over workers’ ability to earn their livelihood through a platform. In Slate, sociologist Julia Ticona and Data & Society Researcher Alexandra Mateescu argue that for domestic workers on gig platforms, increased visibility of this workforce through more data tracking does not necessarily translate into more accountability or greater protections for workers.
• In The New York Times’ “Op-Eds From the Future” series, journalist Brian Merchant explores a fictional future where Amazon touts its first “human free” fulfillment center, but which in fact requires the work of third-party contractors, who are often put into dangerous situations.

Surveillance and Algorithmic Control

From CCTV surveillance to facial recognition and productivity apps, new technologies are enabling greater and more pervasive forms of monitoring and surveillance that are shifting power dynamics in the workplace—often placing low-wage workers under the scope of both corporate and government surveillance. Data collection is also enabling algorithmic management of work: a diverse set of technological tools and techniques to remotely manage workforces through automated decision-making. What rights and expectations should workers have for privacy in the workplace? How are monitoring tools being used to make decisions about a worker’s compensation, perceived risk, or even employment? As algorithmic management of work becomes more prevalent, how are power dynamics shifting within the workplace?

Data and Workplace Surveillance

• The 2019 Color of Surveillance conference focused on the surveillance of poor and working people, delving into the past and present of racialized surveillance, social policy, immigration regimes and labor, incarceration, and the class hierarchies embedded within privacy rights. As part of the event, conference organizers published a reading list based around the conference’s themes. Among this list, the work of sociologist Simone Browne in her book Dark Matters: On The Surveillance of Blackness traces the history of slavery with the emergence of modern-day surveillance systems. In a recent interview with WIRED, she discusses the ways the tech industry has coopted and commodified Blackness, while perpetuating practices like the surveillance of warehouse worker activism and profiting from use of facial recognition technologies by law enforcement.
• In her blog post “Expanding Frameworks,” Data & Society Faculty Fellow and Law Professor Michele Gilman argues that to counter surveillance frameworks which disproportionately affect low-income workers, we must recontextualize notions of digital privacy through the lens of economic justice.
• Data & Society Postdoctoral Scholar Brian Callaci argues that the growth of new workplace surveillance technologies represents a “return to crude, early nineteenth-century models of labor discipline.” For context, historian E.P. Thompson’s seminal work “Time, Work-Discipline, and Industrial Capitalism” traces the emergence of clock time as a form of labor discipline in late-eighteenth-century Europe.
• In The Datafication of the Workplace, the Data Justice Lab examines the quantification of work and workers — from hiring and interviewing to employee monitoring and performance assessment. In a report from The Century Foundation, Sam Adler-Bell and Michelle Miller track how the data collection techniques of the consumer realm migrated into the workplace, leading to “the total datafication of employment.”
• In Workplace Monitoring and Surveillance, Data & Society Researchers Alexandra Mateescu and Aiha Nguyen detail four areas of digital workplace surveillance: prediction and flagging tools, biometrics and health data, remote monitoring and real time tracking, and gamification and algorithmic management.
• In the California Sunday Magazine, a collection of short articles from AI experts explains what facial recognition is, where it is being used, and why it matters. Scholars Evan Selinger and Woodrow Hartzog discuss what is at risk when employers use facial analysis tools in the workplace.
• In Limitless Worker Surveillance, researchers Ifeoma Ajunwa, Kate Crawford, and Jason Schultz examine current legal protections and their potential to serve as a check on worker surveillance, delving into the growing use of productivity apps and worker wellness programs as case studies.
• Scholars Karen Levy and Solon Barocas define the term “refractive surveillance,” to describe when information collected about one group facilitates control over another. In contexts akin to retail, data about things, such as customer foot traffic, might be used to make management decisions about retail workers, expanding the sphere of actors implicated in surveillance. Sociologist Madison van Oort provides an account of how digital surveillance shapes feminized and racialized precarious labor in the fast fashion retail sector.
• In a Slate piece, legal scholar Gabrielle Rejouis makes the case for why we need stronger privacy protections for workers. The Georgetown Center on Privacy & Technology has created a draft bill on worker data protection, emphasizing its importance in the wake of the COVID-19 pandemic, which has prompted a boom in sales of workplace surveillance software. Biometric and health data collection in the workplace has rapidly expanded as part of efforts to enforce social distancing, screen workers for illness using on-site infrared cameras and temperature checks, or conduct workplace-specific contact tracing. Immunity ‘badges’ or ‘certificates’ —which would allegedly allow people already exposed to the virus to return to work—have been proposed, prompting critiques over how such systems could “lead to discrimination, create perverse incentives to get infected, and violate privacy.”

Algorithmic Management

• In an op-ed for The New York Times, Data & Society Senior Researcher Alex Rosenblat discusses how Uber drivers have an “algorithmic boss” that manages them through various metrics, such as ride acceptance rates, cancellation rates, hours spent logged in to the app, and trips completed.
• In On Amazon’s Time, reporter Brian Menegus details how managers at Amazon fulfillment centers depend on an extensive tracking and monitoring system to make rapid scheduling decisions that disrupt shifts and ultimately devalue workers. Legal scholar Shaoul Sussman describes how Amazon gained monopolistic control over the market by engaging in tactics including predatory pricing, platform manipulation, and price matching schemes.
• Chris Ramsaroop, advocate with Justice for Migrant Workers, details how surveillance tools, such as computerized time clocks and automated timesheets, have significantly altered work in the Canadian agricultural industry. While automation is creating opportunities for skilled tech jobs, migrant laborers are not being trained for those jobs, instead facing work environments of tightened control and a punitive, sped-up pace of work.
• Researchers Miranda Bogen and Aaron Rieke detail how predictive hiring tools can perpetuate bias and inequity throughout the hiring process. In an op-ed for The New York Times, labor scholar Ifeoma Ajunwa warns that automated hiring has the potential to worsen employment discrimination because “human biases can be introduced at any stage of the process, from the design of the hiring algorithm to how results are interpreted” and lack of transparency can make it difficult to challenge automated decisions.
• In the Philadelphia Inquirer, reporter Juliana Feliciano Reyes chronicles how a hotel housekeeping application meant to make cleaning rooms more efficient didn’t take into account workers’ input and ultimately made work harder for housekeepers.
• The Shift Project at the University of California investigates how on-demand scheduling practices, often aided by workforce management technologies and algorithms, impact worker health and well-being in the food service and retail sectors. Journalist Claire Cain Miller covers the project’s research findings that show that Black and Latinx workers (and women of color overall) are much more likely to be subjected to unstable work schedules than white colleagues, even from the same employer. Unstable schedules were found to bring financial instability, high stress, and negative impacts for children whose parents had irregular hours.

Worker Precarity and the Gig Economy

Unstable and precarious employment did not originate with the platform gig economy; but many of the practices, technological tools, and challenges to labor regulation, worker protections, and provision benefits pushed forward by companies like Uber have changed the landscape of employment more broadly. Worker misclassification, the growth of algorithmic management, and heightened worker precarity are issues affecting gig workers, but also workers in every industry where subcontracting arrangements have become pervasive. What are the realities of working under algorithmic bosses?

The Rise of Precarious Work

• Historian Louis Hyman’s book Temp tracks a series of deliberate decisions made by consultants and CEOs throughout the 1950s and 60s that transformed the understanding of “what a corporation, or a factory, or a shop, was meant to do,” setting the stage for the growth of part-time, on-demand work. Economist David Weil coined the term “fissured workplace” to describe how many large companies are no longer direct employers of the people behind their products and services. In the wake of the coronavirus pandemic, Weil argues that government response towards expanding worker protections and benefits are a “long overdue recognition of issues that come from the fissured workplace.”
• In Time Magazine, sociologist Tressie McMillan Cottom traces the connection between precarious work and racial inequality, and the ways race and class divisions drive what it means to “hustle” in a contemporary economy defined by unsteady income: “Economic injustice isn’t fairer because nearly everyone is hustling. The hustle itself is a site of racial inequality.”
• A 2019 report from New America’s Better Life Lab, Worker Voices: Technology and the Future of Workers, draws on interviews with workers across the US experiencing technological change. The report notes that media coverage and popular conceptions around automation tend to center manufacturing and blue-collar jobs while overlooking the experiences of people working in retail, fast food, and administrative jobs, where technological change will disproportionately impact women, primarily Black and Latinx workers. In particular, the authors find that adoption of new workplace technologies can “exacerbate financial insecurity when jobs change, wages or hours are suppressed, or when workers are displaced altogether.”
• Legal scholar Veena Dubal provides a history of ridehail companies’ ‘disruption’ of the traditional taxi cab industry through the lens of drivers’ first-hand accounts of the various legal battles, strikes, and economic upheavals in the past decade.
• Journalist Susie Cagle discusses how the sharing economy, characterized by peer-to-peer interaction facilitated by an online platform, popularized gig work but did not fulfill its promise of asset and wealth distribution.
• Compiled by legal anthropologist Deepa Das Acevedo, Gig Economy Resources is an online resource for research on the gig economy, including categories on Collective Activity, Consumer Impact, Discrimination, Innovation & Entrepreneurship, Worker Misclassification, The Gig Economy Beyond Work Law, and Work Law Beyond the Gig Economy.
• Data & Society Senior Researcher Alex Rosenblat’s piece on Silicon Valley Nationalism explores the cultural work tech companies like Uber engage in to distort reality and reshape narratives around what it is they do, and how this shapes debates about their legal and societal obligations. Rosenblat explains how their entrenchment in law and practice became a “microcosm of a larger political battle for power and governance.” In a blog post, scholars Katie Wells, Kafui Attoh, and Declan Cullen lay out how Uber became an unchecked regulatory actor in D.C. through partnering with local officials and selling itself as a provider of public services, while placing a “black box” over its practices.

Challenging the Present

• The Clean Slate project from Harvard Law School’s Labor and Worklife Program asks what labor law would look like if, starting from a clean slate, it was designed to empower working people and promote an equitable economy. Journalist Lauren Kaori Gurley delves into the recommendations from the project, including ways to expand workers’ digital rights and rebuild the union movement in an environment where work is fissured but many workers are organizing digitally.
• Many labor and privacy scholars believe current legal frameworks are inadequate to protect workers; the AFL-CIO Commission Report on the future of work outlines the need for increased worker bargaining power to ensure that the benefits of technological change are broadly distributed.
• Is an egalitarian gig economy possible? “Towards a Fairer Gig Economy” is a collection of essays from workers, organizers, and scholars proposing solutions to some of the social and economic problems associated with gig work. Sociologist Juliet Schor’s book, After the Gig, makes the case for regulatory reforms and worker-centric platforms that would reimagine the gig economy.
• The New School hosted Who Owns the World? The State of Platform Cooperativism, a conference that brought together scholars and founders of platform cooperatives from over 30 countries to discuss “theoretical reflections, artistic provocations, and insights from on-the-ground workers, owners, and users.” Livestream recordings of the 2019 conference sessions are available to watch online.
• The Century Foundation report Collective Responses for Independent Contractors During COVID-19 explains how the pandemic has intensified issues of misclassification and inadequate health coverage, calling on the government to take additional action to support gig workers.
• “Collective Action in Tech” is an online database that attempts to document all collective actions from workers in the tech industry. In The Guardian, Nataliya Nedzhvetskaya and JS Tan — who maintain the project — urge us to expand our definition of who counts as a tech worker, noting that while mainstream narratives of tech worker organizing tend to focus on high-wage, white-collar tech workers, a large percentage of organizing efforts are being led by less privileged, precarious tech workers—warehouse pickers, ridehail drivers, and service employees.

The Labor Futures initiative at Data & Society is comprised of Aiha Nguyen, Alexandra Mateescu, Eve Zelickson, Alex Rosenblat, and Brian Callaci. Explore their research here.