Shadow Work and Social Inequality in the Age of Domestic Robots: A Q Methodology Approach

Abstract

This study explores how domestic humanoid robots reconstruct unpaid labor in the form of digital shadow work and influence perceptions of social inequality. Drawing on Illich’s concept of shadow work and Lee’s typology of digital shadow work, we used Q methodology with 30 participants who sorted 40 statements across four types: chore, make-up, routine, and quest. Analysis identified four user perspectives—Realist, Cautious Critic, Pragmatist, and Optimistic Explorer—each reflecting distinct labor burdens and attitudes toward automation. The findings reveal that humanoid robots do not merely reduce domestic tasks but reshape them, often redistributing invisible labor unequally. These dynamics raise concerns about digital inequality and challenge simplistic narratives of convenience. The study highlights the need for inclusive design and policy frameworks to address emerging forms of unpaid labor in human–robot collaboration.