Impact of Artificial Intelligence on Employment of People with Disabilities: The Moderating Role of Governance Quality
Anis Omri, Hatem Afi
- 发表年份
- 2025
- 引用次数
- 1
- 访问权限
- 开放获取
摘要
This article investigates the nexus between artificial intelligence (AI) and employment for people with disabilities, emphasizing the moderating role of governance quality across economic, political, and institutional dimensions. Using panel data from 25 developed countries (2010-2022), the study examines both linear (direct) and nonlinear (complex) effects of AI on employment rates, measured by annual patent applications and industrial robots. The findings reveal that AI initially reduces employment, but its effects diminish and eventually reverse beyond critical adoption thresholds. Gendered differences emerge, with men with disabilities experiencing stronger negative impacts due to their higher concentration in automation-prone industries, while women with disabilities face smaller but still significant effects. Economic governance—through effective policies and regulatory frameworks—mitigates AI’s adverse effects on employment by fostering regulatory environments that promote workforce adaptability and inclusion. Institutional governance—including the rule of law and control of corruption—reinforces these efforts by ensuring fair labor policies and legal protections that safeguard employment opportunities for people with disabilities, thereby reducing the risks associated with AI-driven job displacement. However, political governance shows no significant influence. These findings underscore the importance of integrating AI adoption with strong economic and institutional governance frameworks, which are essential for moderating AI’s impact and shaping inclusive workforce opportunities for people with disabilities.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992