Does Artificial Intelligence Stimulate or Diminish Human Interactions? An Affordance Perspective on AI,Relational Coordination,and Performance

Abstract

Emerging technologies like artificial intelligence (AI) can influence the way people relate and coordinate to improve performance. Our research explores how human–AI interactions affect relational coordination and operational performance. Competing views suggest that AI may augment or substitute for human capabilities. To examine conflicting views, we build on affordance theory, which suggests that the interactions between people and technology provide (i.e., afford) multiple potential actions, which could stimulate or diminish human interactions. Given the importance of human interactions during times of increasing technology use, we focus on relational coordination with its explicit emphasis on human relationships built on mutual respect and shared goals in fostering coordination. We introduce and find evidence of the concepts of convergent and divergent affordances to explain how AI affordances can result in similar or different outcomes. We perform multiple progressive, behavioral experiments in a virtual factory setting where participants work in teams with three functional roles, including operations, demand, and quality. We randomly assign individuals to one of three treatment groups that differ in the number of teammates that receive recommendations from an analytical AI based on machine learning. Through quantitative, qualitative, replication, recording, and multiphase methods, we find that human–AI interactions can stimulate relational coordination between individuals and improve team performance. We propose a theoretical framework, the ACT cycle, that explains how people interact with AI and with one another based on discussion, trust, and use of AI. Through recording and observing teams, we find evidence of various paths of interaction in that framework. We also find that discussion of AI can stimulate relational coordination, particularly in early phases of team interactions. The results provide theoretical and practical insights into how AI can stimulate relational benefits of human–technology interactions.