Slowing Down or Adapting to Technological Progress? Robot Replacement Risks and Policy Preferences
Ziteng Fan, Jing Ning, Alex Jingwei He
- Year
- 2024
- Citations
- 5
- Access
- Open access
Abstract
ABSTRACT The relationship between automation risk and policy preferences is receiving increasing scholarly attention, but the discussion has yielded mixed and even contradicting results. This study aims to reconcile the results and contribute to the literature by exploring the specific conditions under which citizens prefer government interventions to reduce automation risk and their preferences for specific policy options. Using a survey experimental design in the case of robot installation in China, we find that individuals prefer government interventions that address automation risk in dangerous workplaces vs. those in regular workplaces. Individuals appear to prefer social investment policies such as training programs rather than taxation (e.g., robot tax), regulatory policies (e.g., robot quota), and compensatory policies (e.g., unemployment benefits) when exposed to such risks. We explain that citizens support the government in reducing robot replacement risk only when they perceive the beneficiary groups to be deserving of social protection and that the adopted policies can balance technological progress and unemployment risks.
Keywords
Related papers
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