Artificial Intelligence and Support for Labor Market Policies: Evidence from a Survey Experiment

We study whether alternative narratives about Artificial Intelligence (AI) shape workers' support for strengthening labor market policies and whether these responses differ by workplace AI use. We conduct a four-arm survey experiment on a representative sample of 2,105 Italian employees. Respondents are randomly assigned to a control group or to one of three information treatments framing AI as a technology that may substitute for human labor, complement workers' tasks, or increase the need for reskilling. We then elicit support for five labor market policy instruments, including both passive and active measures. Average treatment effects on policy support are small, but mask substantial heterogeneity by workplace AI use. Among non-users, the substitution narrative increases support for publicly funded training and hiring subsidies, while complementarity increases support for training. Among workplace AI users, both substitution and complementarity reduce support for unemployment insurance and short-time work schemes. Reskilling produces no statistically significant effects in either group. We interpret these heterogeneous effects using evidence that, among users, the substitution narrative increases the probability of expecting household financial losses from public intervention addressing AI's labor market effects, without a detectable change in perceived personal job-loss risk. Overall, workers' responses to the same information differ by workplace AI experience, both in the magnitude and direction of changes in support for specific labor market policies. The findings suggest that support for labor market protection may evolve as AI exposure and perceived vulnerability become more salient.