ABSTRACT
Recent research has examined various aspects of the government’s use of artificial intelligence (AI), including its implications for accountability as well as the policy and management recommendations proposed to address some related concerns. However, two important gaps remain and need further empirical exploration. First, it is unclear why accountability in AI-based system use is viewed as such a critical issue. Second, it is uncertain to what extent existing policy and management recommendations from academia are reflected in government policies. This study aims to bridge these gaps by empirically investigating how the public sector addresses accountability in the use of AI-based systems. Based on an analysis of policy documents related to AI-based systems from 32 U.S. states, our findings show why accountability matters, who is being held accountable to whom, by what standards, and with what consequences from a practical perspective. Furthermore, we identify several research-practice gaps that merit further exploration.
ABSTRACT (CHINESE)
近期研究已探討政府應用人工智慧的多個面向，包括其對課責性之影響及政策與管理建議。然而，現有文獻仍存在兩個重要實證缺口有待釐清。首先，課責性為何會被視為使用人工智慧系統時的關鍵議題，仍不甚清楚。其次，學界所提出的政策與管理建議，在多大程度上實際反映於政府政策之中亦尚不明確。為彌補上述缺口，本研究透過實證方式探討公部門在使用人工智慧系統時如何處理課責性問題。本文分析了美國三十二個州所提出與人工智慧相關之政策文件，從實務界角度說明課責性為何重要、誰該對誰負責、依循何種標準，以及未履行責任時會產生何種後果。此外，我們也提出數個值得進一步探究的研究與實務落差。