Customers as a Factor of Production: Incorporating Pseudo-Automation into Task-Based Models

Moradi, Levy, and Cheyre (2024) show that self-checkout doesn’t fully automate; it offloads tasks to customers, shifting cashiers’ work toward problem-solving, monitoring, and conflict management (“relational patchwork”). Current task-based frameworks (e.g., Acemoglu & Restrepo 2021) classify displacement as capital expanding into tasks previously performed by labor. We propose a third input: customer labor. The model treats pseudo-automation as reallocating routine transaction tasks to consumers, while creating new “relational/monitoring” tasks for workers with distinct skill intensities. Using store-level rollouts of self-checkout as quasi-experiments, we (i) estimate the substitution elasticity between employee and customer tasks, (ii) quantify hidden labor intensification (problem-resolving, policing), and (iii) assess impacts on wage structures, turnover, shrinkage, and conflict events. We cross-validate with sectors that use “patient labor” (health check-ins) and “citizen labor” (public e-services; Savignon et al. 2023). This diverges from standard automation studies by explicitly modeling and measuring a third production factor—unpaid end-user labor—missing in both Acemoglu & Restrepo (2021) and AI partial-equilibrium models like Gries & Naudé (2022). The contribution is both conceptual (a revised production function) and empirical (identification of pseudo-automation’s distributional and relational consequences), with implications for regulation, ergonomics, and pricing of “customer effort.”

References:

1. Automation in public sector jobs and services: a framework to analyze public digital transformation’s impact in a data-constrained environment. Andrea Bonomi Savignon, Riccardo Zecchinelli, Lorenzo Costumato, Fabiana Scalabrini (2023). Transforming Government: People, Process and Policy.
2. Pseudo-Automation: How Labor-Offsetting Technologies Reconfigure Roles and Relationships in Frontline Retail Work. Pegah Moradi, Karen Levy, Cristobal Cheyre (2024). Proc. ACM Hum. Comput. Interact..
3. Modelling artificial intelligence in economics. Tom Gries, W. Naudé (2022). Journal for labour market research.
4. Tasks, Automation, and the Rise in US Wage Inequality. D. Acemoglu, P. Restrepo (2021). Social Science Research Network.