Matthias Haslberger
Title
Dr.
Last Name
Haslberger
First name
Matthias
Email
matthias.haslberger@unisg.ch
ORCID
6 results
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Item type:Publication, Rage against the machine? Generative AI exposure, subjective risk, and policy preferencesHow does novel technology change public policy demands? Scholars interested in the effect of automation on policy preferences have commonly argued that exposure to automation technology increases subjective risk, which in turn predicts demand for insurance. Generative AI potentially challenges this dynamic. Based on a pre-registered online experiment with a sample of 1041 UK working-age adults we show that direct exposure to generative AI in realistic work tasks does not increase subjective risk but strengthens support for activating social policy. To understand this constellation of attitudes, we argue that exposure to technology may activate sociotropic preferences to support individuals who might be negatively affected by AI. Text analysis shows cautious optimism and thoughtful engagement with the implications of AI for work and social policy. Our findings suggest that the current uncertainty over the relative winners and losers from AI opens a window of opportunity to expand activating social policies.Type:journal articleJournal:Journal of European Public PolicyScopus© Citations 5 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Rage against the machine? Generative AI exposure, subjective risk, and policy preferences(2025-09-12); Scopus© Citations 5 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Rage Against the Machine? AI Use, Threat Perceptions, and Policy PreferencesScholars interested in the effect of automation on policy preferences have commonly argued that (subjective) risk predicts demand for insurance. Generative AI potentially challenges this dynamic. Based on a pre-registered online experiment with a near-representative sample of 1,041 UK working-age adults we show that direct exposure to generative AI does not increase subjective risk and leads to more positive attitudes towards the technology. Despite this, treated respondents show greater support for progressive social policy and place themselves politically further left, indicating that sociotropic preferences trump self-interest. Text analysis of an open-ended question shows thoughtful engagement with the implications of AI. This article provides a first big-picture investigation of the political implications of generative AI and outlines avenues for further research.Type:conference paper - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Rage Against the Machine? AI Use, Threat Perceptions, and Policy Preferences(2024-06-28); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, How Do People Reason about Policy Responses to Generative AI?(2025-11-13); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, No Great Equalizer: Experimental Evidence on Productivity Effects of Generative AI Use in the UK Labor MarketAn emerging consensus holds that generative artificial intelligence (AI) equalizes workers' performance within tasks, reducing productivity differences across workers. Existing research has largely studied productivity within single occupational groups and task structures. Whether this equalizing pattern generalizes to the labor market at large remains unclear. Observed performance equalization within groups of workers is compatible with both increasing and decreasing inequality between groups. To distinguish these outcomes, we conducted a large pre-registered online experiment with a sample of the UK working age population which randomly assigned participants to treatments that encouraged or discouraged the use of ChatGPT and then asked them to complete a set of realistic work tasks. We find that ChatGPT use increased productivity in all tasks, with greater benefits observed in more complex and less ambiguous tasks. However, compression effects between tasks were limited. Moreover, Chat-GPT use did not affect productivity differentials between gender, age, educational or occupational groups.Type:working paperJournal:SSRN Electronic Journal