Slowing Down or Adapting to Technological Progress? Robot Replacement Risks and Policy Preferences

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.