This study analyzes how automation risk in the digital transition affects social policy preferences and how this relationship is moderated by the generosity of social insurance systems across countries. Unlike previous studies that focused on subjecti...
This study analyzes how automation risk in the digital transition affects social policy preferences and how this relationship is moderated by the generosity of social insurance systems across countries. Unlike previous studies that focused on subjective risk perception or single-country cases, this research employs the objective automation risk indicator of Routine Task Intensity (RTI) to conduct cross-national comparative analysis. Specifically, we combined data from 18 OECD countries using the RTM (Risk That Matter) survey, CWEP (Comparative Welfare Entitlement Project), and RTI index. The dependent variables include preferences for robot tax, job creation policies, social protection, basic income, education/retraining, and digital infrastructure investment policies. Results show that workers in occupations with higher RTI generally showed stronger preferences for most social policies. However, this relationship was moderated by national social insurance generosity levels. Notably, significant interaction effects were found in preferences for job creation and digital infrastructure investment policies. In countries with low social insurance generosity, RTI increase led to decreased preference for job creation policies but increased preference for digital infrastructure investment. The opposite pattern was observed in countries with high social insurance generosity. These findings suggest that policy responses to digital transformation require differentiated approaches considering each country's institutional context. Particularly in countries with weak social insurance, establishing basic income security systems should precede structural reforms or human capital investment policies.