Efficiency or Equity? How Public Values Shape Bureaucrats' Willingness to Use Artificial Intelligence to Reduce Administrative Burdens

Abstract

Generative and predictive Artificial Intelligence (AI) has the potential to revolutionize many features of policy implementation, but only if bureaucrats understand and decide to utilize AI. While existing research has examined the public's demand for AI in policy implementation, very little scholarship has examined the views of bureaucrats. In this article, we implement two survey experiments—one on predictive AI and another on generative AI—among government employees to reveal how information about the effects of AI on public values (equity and efficiency) affect bureaucrats' decisions on whether to utilize AI to ease administrative burdens on clients. We find that, regardless of AI type (i.e., predictive vs. generative) and randomly assigned policy contexts with different socially constructed target populations, bureaucrats are less likely to adopt AI when they are presented with information about the potential biases embedded in algorithms and the negative impacts on social equity. On the other hand, we find that highlighting the efficiency gains of utilizing AI has no impact on support for using AI. These findings suggest that concerns over equity may be a key barrier to bureaucrats' decisions on adopting AI in policy implementation.