WORKING PAPERS AND WORK IN PROGRESS
My research agenda currently focuses on the political consequences of technological change and Artificial Intelligence.
Work in progress
Support for government regulation of new technologies: Evidence from 5 EU countries
With Alex Kuo
The acceleration of the fourth industrial revolution in 2023 has led experts and technological elites to demand government intervention to direct the path of technological development. This paper presents the case for policies that regulate and tax new technologies and studies citizen support for such policies. Based on recent work, we argue that attitudes towards regulation are shaped by core narratives about technology. The main narrative against regulation argues that it is detrimental to economic growth. The main narrative in favor of this policy emphasizes the potential harms of technology to some workers or communities. In order to examine how these core narratives affect public opinion, we develop new survey questions about six policies (e.g. taxes on algorithms and robots) and experimentally manipulate the narratives provided to citizens. We embed our experiments in large, representative samples from 5 EU countries (France, Germany, Italy, Poland, and Sweden) in which we also measure a theoretically motivated battery of objective and subjective technological risks, including risk of substitution by artificial intelligence (AI). We find that: a) there is considerable support for technology regulation; b) support is significantly reduced by arguing that regulation and taxation harms the economy; c) support is modestly increased by appealing to the distributional consequences of technological disruption; d) objective indicators of technology risk do not moderate treatment effects. We conclude by discussing the implications of our results in light of growing concern about AI.
Draft available on request
Who Wants the Knowledge Economy?
With Alex Kuo, Silja Häusermann and Reto Bürgisser
Slides available on request.
Policy Responses to Digitalization-Related Risks
With Nicolas Bicchi and Alexander Kuo
What policies do individuals prefer in response to the labor market risks related to the ongoing processes of digitalization and automation? To what extent does being exposed to different forms of “technological risk” condition such preferences? In this paper, we advance existing research on this topic by distinguishing between among three main dimensions of technological risks (general concern about negative technological impacts, concern about tasks in one’s job being automated, and stress about learning new technology “technostress”), as well as and preferences for three types of policies related to these risks (compensation, retraining, and protectionist policies intended to slow down or prevent technological change). Using new survey evidence from Spain, we find little evidence that technological risks matter for preferences for compensation or retraining, but they do condition support for protectionist policies. We conclude with implications for politics in the current context of rapid digitalization.
Published as a working paper by the EU Science Hub. Under review
Using ChatGPT to Measure Policy Positions from Political Text
With Gaël Le Mens
Working paper available on request
Other Working papers
Historical Family Types and Female Political Representation: Persistence and Change
With Dídac Queralt and Ana Tur-Prats
We argue that different historical family configurations shaped the gendered division of labor within the household, gender norms, and female political representation in the long run. Our main evidence draws from geographic variation in historical family types in Spain and municipality-level electoral data from 1978 to 2015 and earlier democratic spells. We find that areas where the stem family was prevalent-meaning that multiple generations of women lived together and shared domestic work-show higher female political representation than areas with nuclear-family tradition. Still, history is not destiny, and the impact of historical legacies can fade. In our mechanisms analyses, we demonstrate that the introduction of party-list gender quotas balanced off the main effect, although they did not erase underlying differences between regions in gender attitudes and female paid employment. Our research contributes to the study of historical persistence by assessing what institutions can and cannot do to combat patriarchal prejudice.
Working paper here. Revised version under review
CURRENT FUNDED RESEARCH PROJECTS
How technological change shapes politics: Voters, elections and policies (TECHNO) as PI of the Spanish team
Team: Henning Finseraas, Alex Kuo, Silja Häusermann, Thomas Kurer
Research grant NORFACE September 2020 - August 2023
Transforming European Work and Social Protection (TRANSEUROWORKS) as PI of the Spanish team
Awarded by the European Commission, H2020 program
November 2022 - October 2026
Citizen Attitudes toward Artificial Intelligence (CATAI) as PI
Awarded by the Spanish Ministry of Science and Innovation
January 2023 - December 2026
My research agenda currently focuses on the political consequences of technological change and Artificial Intelligence.
Work in progress
Support for government regulation of new technologies: Evidence from 5 EU countries
With Alex Kuo
The acceleration of the fourth industrial revolution in 2023 has led experts and technological elites to demand government intervention to direct the path of technological development. This paper presents the case for policies that regulate and tax new technologies and studies citizen support for such policies. Based on recent work, we argue that attitudes towards regulation are shaped by core narratives about technology. The main narrative against regulation argues that it is detrimental to economic growth. The main narrative in favor of this policy emphasizes the potential harms of technology to some workers or communities. In order to examine how these core narratives affect public opinion, we develop new survey questions about six policies (e.g. taxes on algorithms and robots) and experimentally manipulate the narratives provided to citizens. We embed our experiments in large, representative samples from 5 EU countries (France, Germany, Italy, Poland, and Sweden) in which we also measure a theoretically motivated battery of objective and subjective technological risks, including risk of substitution by artificial intelligence (AI). We find that: a) there is considerable support for technology regulation; b) support is significantly reduced by arguing that regulation and taxation harms the economy; c) support is modestly increased by appealing to the distributional consequences of technological disruption; d) objective indicators of technology risk do not moderate treatment effects. We conclude by discussing the implications of our results in light of growing concern about AI.
Draft available on request
Who Wants the Knowledge Economy?
With Alex Kuo, Silja Häusermann and Reto Bürgisser
Slides available on request.
Policy Responses to Digitalization-Related Risks
With Nicolas Bicchi and Alexander Kuo
What policies do individuals prefer in response to the labor market risks related to the ongoing processes of digitalization and automation? To what extent does being exposed to different forms of “technological risk” condition such preferences? In this paper, we advance existing research on this topic by distinguishing between among three main dimensions of technological risks (general concern about negative technological impacts, concern about tasks in one’s job being automated, and stress about learning new technology “technostress”), as well as and preferences for three types of policies related to these risks (compensation, retraining, and protectionist policies intended to slow down or prevent technological change). Using new survey evidence from Spain, we find little evidence that technological risks matter for preferences for compensation or retraining, but they do condition support for protectionist policies. We conclude with implications for politics in the current context of rapid digitalization.
Published as a working paper by the EU Science Hub. Under review
Using ChatGPT to Measure Policy Positions from Political Text
With Gaël Le Mens
Working paper available on request
Other Working papers
Historical Family Types and Female Political Representation: Persistence and Change
With Dídac Queralt and Ana Tur-Prats
We argue that different historical family configurations shaped the gendered division of labor within the household, gender norms, and female political representation in the long run. Our main evidence draws from geographic variation in historical family types in Spain and municipality-level electoral data from 1978 to 2015 and earlier democratic spells. We find that areas where the stem family was prevalent-meaning that multiple generations of women lived together and shared domestic work-show higher female political representation than areas with nuclear-family tradition. Still, history is not destiny, and the impact of historical legacies can fade. In our mechanisms analyses, we demonstrate that the introduction of party-list gender quotas balanced off the main effect, although they did not erase underlying differences between regions in gender attitudes and female paid employment. Our research contributes to the study of historical persistence by assessing what institutions can and cannot do to combat patriarchal prejudice.
Working paper here. Revised version under review
CURRENT FUNDED RESEARCH PROJECTS
How technological change shapes politics: Voters, elections and policies (TECHNO) as PI of the Spanish team
Team: Henning Finseraas, Alex Kuo, Silja Häusermann, Thomas Kurer
Research grant NORFACE September 2020 - August 2023
Transforming European Work and Social Protection (TRANSEUROWORKS) as PI of the Spanish team
Awarded by the European Commission, H2020 program
November 2022 - October 2026
Citizen Attitudes toward Artificial Intelligence (CATAI) as PI
Awarded by the Spanish Ministry of Science and Innovation
January 2023 - December 2026
