Corresponding Manager: Michela Iannotta (michela.iannotta@uniroma1.it)
Track Manager(s): Michela Iannotta, Ginevra Gravili, Eleonora Veglianti, Maria Menshikova, Mauro Gatti, Giuseppe Ceci
Description
Nowadays, when referring to the workforce, it is no longer just about employees but rather about a workforce ecosystem (WE), which includes both people and machines for workforce augmentation (i.e., fourth industrial revolution technologies). Complementarities between different elements of WEs are crucial for collective success or failure, in a way that WEs emerge as systems of collective intelligence, where people and machines together act more intelligently than any person or computer alone. However, controversial issues related to the risk of labor substitution, dehumanization, privacy violations, and algorithmic biases may undermine the promises of human-machine complementarity.
This track aims to critically explore the complexity of work dynamics in WEs, focusing on an in-depth understanding of how modern WEs are transforming society through their effects on individuals, organizations, and institutions. We invite scholars from different fields to expand knowledge on how human and artificial intelligence combine and interact to co-create value in WEs. The aim is to provide both theoretical insights and practical guidance to help HR managers, policymakers, and trade unions make better-informed decisions regarding the design of modern WEs, innovative human resource management (HRM) systems, and policies that adequately protect the quality and dignity of labor.
Keywords
Workforce augmentation; human-machine complementarity; collective intelligence; innovative HRM practices; decent work.
Key References
Hemmer, P., Schemmer, M., Kühl, N., Vössing, M., & Satzger, G. (2025). Complementarity in human-AI collaboration: Concept, sources, and evidence. European Journal of Information Systems, 1-24.
Siaw, C. A., & Ali, W. (2025). Substitution and complementarity between human and artificial intelligence: a dynamic capabilities view. Journal of Managerial Psychology, 40(5), 539-554.
Saluja, A., & Mongia, A. (2025). Human-Machine Collaboration: Augmenting Human Abilities With Robotic Assistance in the Workplace. In Technological Enhancements for Improving Employee Performance, Safety, and Well-Being (pp. 145-170). IGI Global