CHS: Small: Collaborative Research: Reconstructing the data-driven workplace

Indiana University, Bloomington IN

Investigators

Abstract

This research will develop evaluation heuristics and methodological innovations to better incorporate worker perspectives into the research and design of data-driven workplace systems. Advances in sensing technology and data collection are moving us toward a data-driven workplace. Employers can now gather detailed, granular information about workers from digital communication and wearable sensors, leading to benefits such as improved workplace safety and performance improvements. Yet, these same technologies also have potential for negative impacts on workers: to be invasive, hinder worker self-management, and exacerbate poor working environments. Research into designing workplace analytics to work better for workers faces two key challenges: (1) given complex organizational dynamics, it is hard to immediately predict the long-term outcomes of design decisions on workers; and (2) researchers lack access to information about and data from proprietary systems currently being deployed in the workplace. This project addresses these challenges by collecting and analyzing available archival data from the development of earlier forms of work measurement that form the precedent for systems used today. This data will be used to understand the long-term impact of data advocacy, and to develop heuristics and methods that will provide guidance for contemporary technology practitioners in design of and advocacy for the data-driven workplace. This research will also inform curriculum design for courses on HCI methods and designing technology for social impact, and a summer school for underrepresented scholars on the same topic. This research answers three questions: (1) How has workplace data been used to advocate for US workers in the past, in an industry facing analogous challenges to data-driven workplaces today? What was effective and ineffective? (2) How do the decisions and challenges of using data to represent worker perspectives map onto analogous methodological challenges that impact the design of workplace measurement analytics today? (3) How can these design techniques and insights from the past be used in present-day workplace analytics and advocacy for workers in data-driven workplaces? This project answers these questions by combining historical and design research, organized around a case study of management-engineering projects conducted by the International Ladies Garment Workers Union (ILGWU). Archival data will be gathered and analyzed to identify strategies to use data to advocate for workers and to evaluate the long-term impact of those strategies on work in an industry threatened by a volatile economic climate, outsourcing, and automation. Through an analysis of historical data-driven design methods for the workplace and an interview study with contemporary union organizers on the use of data systems in contemporary organized labor, the project will identify how and in what ways past union strategies, opportunities, and challenges are relevant to contemporary issues in HCI research in data-driven workplaces. 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.