RAPID: Revisting Infrastructures of Workplace Accountability amidst 2023 Tech Layoffs

This project seeks to learn about tech workers' experiences, attitudes, and conceptualizations of layoffs to develop principles for co-design of tools and techniques for better workplace accountability towards management software. In early 2023, major technology companies announced layoffs affecting at least 50,000 people. These layoffs came at a time when tech workers are increasingly critical of their employers’ values and practices. As a result, many workers are seeking new means of accountability within and outside the workplace, which could require new principles of software design. A key issue recently has been the role of Human Resources Management (HRM) software in the decision-making that led to these mass layoffs. Media articles reported on the possible role of artificial intelligence (AI) in layoff decisions, based on parameters such as performance reviews and predictions of flight risks. Laid-off employees quickly gathered on online platforms to make sense of the layoffs, including the role of HRM software. While AI-based decision-making is already reportedly common in evaluating performance of gig workers, delivery workers, and other under-paid employees and deciding their futures in the companies, the specific case of software involvement in the management (particularly in the hiring/firing) of a more privileged class of workers is less studied. This project aims to examine the role of existing software technologies in managerial decision-making, while simultaneously developing design principles for better worker-centered accountability tools and techniques applicable for a wide range of techworkers. The research is supported as a RAPID, because it will quickly collect data of scientific value that unexpectedly became available, while tech workers' experiences and attitudes are still fresh in their minds. It will use survey, interview, and asynchronous remote community methods to collect answers to two important questions: (1) What are some perceptions, meaning-making processes, and folk theories - held by laid-off employees - around the role of technologies (such as HRM software) in the 2023 technology layoffs? (2) How can we leverage these grounded folk theories of layoff technologies towards developing counter-strategies and infrastructures of accountability in the workplace? Interviews with ex-employees will focus on algorithmic decision-making in firing and other processes. The results will help shape theories of how tech layoffs impact both employed and recently laid off workers, and contribute to understandings of the sociotechnical infrastructures of workplace accountability by illuminating the interdependencies between workers, management, and information technologies. Findings and analysis will strive to inform labor policies surrounding workers' rights and protections against algorithmic biases. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.