ESADE Business School - Ramon Llull Univeristy, Spain
This caucus explores how integrating artificial intelligence into the workplace impacts interpersonal dynamics and may contribute to the dehumanization of jobs. Participants will explore key knowledge gaps, brainstorm research questions, and propose collaborative initiatives, fostering interdisciplinary dialogue to address the challenges of balancing AI integration with maintaining human-centered work environments.
This session explores how integrating artificial intelligence (AI) into the workplace may reshape interpersonal dynamics. While much research focuses on AI broadly and examines individuals' engagement with new technologies, less attention is given to how specific types of AI affect real-world human interactions. Moreover, existing evidence lacks clarity which AI characteristics—such as the degree of anthropomorphism—are most beneficial for users. For example, more anthropomorphic AI devices perceived as empathetic are likely to increase user acceptance (Pelau et al., 2021). However, a recent study by Kim & McGill (2024) indicates that perceiving robots as more humanlike due to higher socio-emotional capabilities may lead to viewing actual people as less human, resulting in technology-induced dehumanization. Dehumanization is related to negative behaviors, such as harsher punishment (Fincher & Tetlock, 2016) and reduced helping intentions (Andrighetto et al., 2014). In workplace settings, such effects may influence collaboration, performance, decision-making, and ethics, posing challenges for fostering inclusive and effective teams. Therefore, understanding how AI’s anthropomorphic features influence user perceptions, behaviors, and interpersonal interactions is essential for designing workplaces that leverage AI while maintaining positive human-to-human interactions and maintaining ethical standards. This caucus targets a diverse audience, including researchers and practitioners from fields such as technology in the workplace, organizational behavior, HR management, neuroscience, ethics, and research methodology. This approach aims to encourage interdisciplinary dialogue and collaborative research initiatives, stimulate innovative thinking, and address the challenges posed by integrating AI and robotics into workplace environments. The session starts by outlining objectives and briefly introducing the topic with an overview of existing research on human-machine interaction. This sets the stage for small-group discussions aimed at identifying key knowledge gaps in AI’s workplace effects. Participants are encouraged to approach the topic from both academic and practitioner perspectives, ensuring a well-rounded reflection. The discussions will center on critical focus areas, such as outcomes (changes in interpersonal dynamics), antecedents (e.g., attitudinal, behavioral, or cognitive shifts), and mechanisms (including potential moderators and mediators, e.g., anthropomorphism). Building on these insights, participants will brainstorm, prioritize research questions, and develop a preliminary roadmap to address identified gaps while considering potential methodological challenges. To foster collaboration, attendees will form teams to propose joint research initiatives, drafting a longlist of ideas. The session will conclude with a summary and a call to action, encouraging ongoing collaboration.
References: Andrighetto, L., Baldissarri, C., Lattanzio, S., Loughnan, S., & Volpato, C. (2014). Human-itarian aid? Two forms of dehumanization and willingness to help after natural disasters. British journal of social psychology, 53(3), 573-584. Fincher, K. M., & Tetlock, P. E. (2016). Perceptual dehumanization of faces is activated by norm violations and facilitates norm enforcement. Journal of Experimental Psychology: General, 145(2), 131. Kim, H. Y., & McGill, A. L. (2024). AI-induced dehumanization. Journal of Consumer Psychology. Pelau, C., Dabija, D. C., & Ene, I. (2021). What makes an AI device human-like? The role of interaction quality, empathy and perceived psychological anthropomorphic characteristics in the acceptance of artificial intelligence in the service industry. Computers in Human Behavior, 122, 106855.
