Cognitive Impacts of AI on Administration

• In Event: AI in the Public Sector: Cross-National Evidence on Bureaucracy, Procurement, and Organizational Change

Abstract

There is a lack of empirical research systematically investigating how and why employees adopt artificial intelligence (AI) in specific organizational contexts, including different types of organizations and positions. This study focuses on AI as a decision-making agent operating within organizational administration, with a specific emphasis on the case of ‘basic AI’ as a form of supervised machine learning that involves greater characteristics of control. I review existing literature on organizational innovation adoption, drawing insights from classic works in administration, information processing, and organizational sensemaking to develop an integrated theoretical and analytical lens. For empirical testing, I utilize survey experiment data collected from National Taiwan University (N=1,200), consisting of responses from employees working in both public and private organizations. The experiment includes a decision exercise in which all participants were involved, allowing for pre- and post-perception measurements. The treatment group experienced AI intervention during the decision exercise, while the control group did not. To analyze the data, I employ difference-in-differences (D-i-D) analyses. The results indicate that employees of public organizations who experienced AI intervention during the decision exercise are more likely than others to agree with the utilization of AI for conducting organizational operations. After all, the findings underscore that institutional environments and organizational mechanisms can significantly moderate individual-level human-AI interactions.

Author

• Kyoung-cheol (Casey) Kim, University of Central Florida
  Presenting Author