Earlier this month, I had a conversation with some people about the future of work as AI seems to be changing everything. I brought in how Keynes predicted almost 100 years ago that we would develop into a 15-hour work week. Well, that didn’t happen. This new study also gives people a bit of hope that AI won’t replace them, but rather we will all be working with AI. The study predominantly shows that how the latter will happen, seems to differ based on work experience.

Or wait! Maybe hope isn’t the right word. I would love to have even a 20-hour work week.

From the press release:

The study, “Friend or Foe? Teaming Between Artificial Intelligence and Workers with Variation in Experience,” looks at the influence of two major types of human work experience (narrow experience based on the specific task volume and broad experience based on seniority) on the human-AI team dynamics.

“We developed an AI solution for medical chart coding in a publicly traded company and conducted a field study among the knowledge workers,” says Weiguang Wang of the University of Rochester and leading author of the study. “We were surprised by what we found in the study. The different dimensions of work experience have distinct interactions with AI and play unique roles in human-AI teaming.”

“While one might think that less experienced workers should benefit more from the help of AI, we find the opposite — AI benefits workers with greater task-based experience. At the same time, senior workers, despite their greater experience, gain less from AI than their junior colleagues,” says Guodong (Gordon) Gao of Johns Hopkins Carey Business School, and study co-author.

Further investigation reveals that the relatively lower productivity lift from AI is not a result of seniority per se but rather their higher sensitivity to the imperfection of AI, which lowers their trust in AI.

“This finding presents a dilemma: Employees with greater experience are in a better position to leverage AI for productivity, but the senior employees who assume greater responsibilities and care about the organization tend to shy away from AI because they see the risks of relying on AI’s assistance. As a result, they are not effectively leveraging AI,” says Ritu Agarwal of Johns Hopkins Carey Business School, a co-author of the study.

The researchers urge employers to carefully consider different worker experience types and levels when introducing AI into the work. New workers with less task experience are disadvantaged in leveraging AI. Meanwhile, senior workers with more organizational experience may be concerned about the potential risks imposed by AI. Addressing these unique challenges are key to productive human-AI teaming.

Abstract of the study:

As artificial intelligence (AI) applications become more pervasive, it is critical to understand how knowledge workers with different levels and types of experience can team with AI for productivity gains. We focus on the influence of two major types of human work experience (narrow experience based on the specific task volume and broad experience based on seniority) on the human-AI team dynamics. We developed an AI solution for medical chart coding in a publicly traded company and conducted a field study among the knowledge workers. Based on a detailed analysis performed at the medical chart level, we find evidence that AI benefits workers with greater task-based experience, but senior workers gain less from AI than their junior colleagues. Further investigation reveals that the relatively lower productivity lift from AI is not a result of seniority per se but lower trust in AI, likely triggered by the senior workers’ broader job responsibilities. This study provides new empirical insights into the differential roles of worker experience in the collaborative dynamics between AI and knowledge workers, which have important societal and business implications.