Two scholars from the University of Kansas have introduced a groundbreaking framework for understanding workplace communication in the digital age. Their theory, called Socio-Technical Exchange (STE), aims to better capture how employees interact with the increasingly complex technologies that dominate modern work environments.
The research, published in the Human-Machine Communications Journal, was conducted by Cameron Piercy, Associate Professor of Communication Studies, and Reaia Turner-Leatherman, a McNair Scholar and graduate student at Kansas State University. They surveyed nearly two dozen professionals across different industries to explore how workers form beliefs about the tools they rely on every day.
Traditionally, workplace interaction has been explained through Social Exchange Theory (SET), a model dating back to the 1960s. SET argues that people build relationships based on rewards versus costs—collaborating with those who add value while avoiding those who drain resources. According to Piercy, this framework is limited when applied to human-technology interactions because machines do not engage in reciprocity the way humans do.
Instead, the new Socio-Technical Exchange model reflects how workers perceive machines as collaborators. Employees develop what the authors call “machine heuristics”—beliefs about the strengths and weaknesses of specific technologies. For instance, a machine might be considered objective and consistent, but ill-suited for nuanced decision-making. Over time, through repeated use, people form stable cognitive patterns about which tasks machines excel at and which require human judgment.
The study highlights that workers still value human uniqueness, especially when expertise and critical thinking are required. Humans were seen as more reliable when complex decisions had to be made. On the other hand, machines were often preferred for simple tasks or situations where employees felt embarrassed to ask a colleague for help. As one participant noted, “It’s easier to ask a machine a ‘dumb’ question without judgment.”
This distinction suggests that workplace collaboration is evolving into a hybrid model, where humans and machines share complementary roles. The concept of STE reflects this balance, acknowledging that while machines cannot replicate empathy or judgment, they can provide efficiency, discretion, and objectivity in ways human coworkers cannot.
Importantly, the study was conducted in 2022—before the explosive adoption of AI tools like ChatGPT. Yet even then, the findings indicated that humans already felt a form of interdependence with technology. With AI now embedded in everyday workflows, the STE framework may prove even more relevant for understanding how workers navigate digital environments.
Conclusion
The Socio-Technical Exchange Theory represents a major step forward in understanding how people collaborate with machines. By going beyond outdated communication models, it recognizes that workplace technology is not just a passive tool but an active partner shaping productivity, trust, and decision-making. As AI and automation continue to expand, this framework could become vital for designing workplaces where humans and machines work side by side effectively.
