explainer | 02.06.19
Technology enables employers to increasingly monitor their employees. This explainer by Alexandra Mateescu and Aiha Nguyen identifies four current trends in workplace monitoring and surveillance: prediction and flagging tools; biometrics and health data; remote monitoring and time-tracking; and gamification and algorithmic management.
Mateescu and Nguyen consider how each trend impacts workers and workplace dynamics. For instance, freelancers on Upwork can be tracked through their keystrokes, mouse clicks, and screenshots to measure work time for clients. Work that cannot be measured in this way (for example, group brainstorming or long-term planning) may be devalued or go uncompensated.
The authors observe that information asymmetries are deepening as the boundaries of workplace privacy are changing. Tracking metrics like health data, for instance, can make way for discrimination and raises concerns about consent. The type of data employers collect will determine which work is valued, how they evaluate performance, and how workers are classified and compensated.
This explainer from Data & Society provides a basic introductory overview to concepts and current issues around technology’s impact on the workplace. It is being co-released with an explainer on Algorithmic Management in the Workplace. For more coverage of emerging issues in labor and technology, visit Social Instabilities in Labor Futures.
explainer | 02.06.19
This explainer by Alexandra Mateescu and Aiha Nguyen defines algorithmic management and reviews how this concept challenges workers’ rights in sectors, including retail, the service industry, and delivery and logistics. The authors outline existing research on the ways that algorithmic management is manifesting across various labor industries, shifting workplace power dynamics, and putting workers at a disadvantage. It can enable increased surveillance and control while removing transparency.
Defined as “a diverse set of technology tools and techniques that structure the conditions of work and remotely manage workforces,” algorithmic management relies on data collection and worker surveillance to enable automated decision-making in real time. For example, an algorithm might decide and assign servers’ shifts.
Because companies aren’t “directly” managing their workers, algorithmic management makes it easier to classify workers as independent contractors, thus relieving companies of the pressure of providing standard worker benefits. Algorithmic management can provide avenues for bias and discrimination, while making it difficult to hold companies accountable. Companies ultimately benefit and continue to scale operations while cutting costs and labor.
This explainer from Data & Society provides a basic introductory overview to concepts and current issues around technology’s impact on the workplace. It is being co-released with an explainer on Workplace Monitoring & Surveillance. For more coverage of emerging issues in labor and technology, visit Social Instabilities in Labor Futures.