Unraveling the Impact of Work Experience on Human-AI Teaming

New insights are emerging from a groundbreaking study in Management Science that sheds light on the relationship between work experience and the effectiveness of employees collaborating with artificial intelligence (AI). The research, titled “Friend or Foe? Teaming Between Artificial Intelligence and Workers with Variation in Experience,” explores how two distinct types of work experience, namely narrow experience and broad experience, influence the dynamics of human-AI collaboration. Weiguang Wang, a researcher from the University of Rochester and the leading author of the study, explains, “Our field study focused on developing an AI solution for medical chart coding within a publicly traded company. The unexpected findings challenged conventional assumptions and highlighted the essential role of different dimensions of work experience in human-AI collaboration.”

Contrary to popular belief, the study reveals that AI disproportionately benefits workers with greater task-based experience, rather than those with less experience. Guodong (Gordon) Gao, a co-author of the study from Johns Hopkins Carey Business School, explains, “Our initial assumption was that less experienced workers would derive more significant advantages from AI support. However, we found that senior workers, despite their extensive experience, received fewer benefits from AI compared to their junior counterparts.” This discovery prompted further investigation into the factors underlying this phenomenon.

The researchers found that the diminished productivity gains experienced by senior workers were not solely attributed to their seniority but rather to their heightened sensitivity to the imperfections of AI, which consequently eroded their trust in the technology. Ritu Agarwal, another co-author from Johns Hopkins Carey Business School, explains, “This dilemma arises when employees with substantial experience possess the potential to leverage AI effectively but have reservations due to the perceived risks associated with relying on AI. As a result, they fail to harness the full potential of AI.”

Navigating the Challenges

The study highlights the importance of carefully considering the different types and levels of worker experience when implementing AI in the workplace. New employees with limited task experience may face challenges in leveraging AI effectively, placing them at a disadvantage. On the other hand, more experienced senior employees, who bear additional responsibilities and exhibit greater organizational awareness, may harbor concerns about the potential risks posed by AI. Ritu Agarwal emphasizes the significance of addressing these unique challenges to foster productive human-AI collaboration.

The research presents a fresh perspective on the interplay between work experience and the efficacy of human-AI teaming. Contrary to expectations, it reveals that workers with greater task-based experience benefit the most from AI support. However, senior employees, despite their extensive experience, are less inclined to embrace AI due to their risk perception and lower trust in the technology. To optimize human-AI collaboration, organizations should pay close attention to individual differences in work experience and tailor AI implementation strategies accordingly. By doing so, they can unlock the full potential of AI while empowering employees at all levels to leverage the technology effectively, thereby fostering a productive and harmonious collaboration between humans and AI.