Gianmaria Bottoni

European welfare systems are undergoing a profound transformation driven by the integration of digital technologies, and artificial intelligence into public administration. This shift reflects processes of datafication, through which welfare increasingly operates as a sociotechnical system mediated by algorithms and digital platforms. While these innovations promise greater efficiency, predictive capacity, and resource optimization, they also raise concerns about opacity, surveillance, and inequality in access to social rights. The chapter examines an often-overlooked dimension of welfare digitalization: citizens' perceptions of artificial intelligence. Drawing on comparative data from Eurobarometer, it analyzes how attitudes toward AI vary across European countries. The findings reveal that public perceptions are structured around three main dimensions: technological optimism, concerns about automation-related job risks, and perceived digital skills. The results also highlight significant cross-national differences linked to institutional trust and socio-economic conditions.

Previous research highlights the impact of nonverbal cues and visual layouts on respondents’ interpretations and answers to survey questions (Schwarz et al. in Pub Opin Q 55(4):570–582, 1991; Tourangeau et al. in Pub Opin Q 71(1):91–112, 2007; Toepoel and Dillman in Soc Sci Comput Rev 29(2):193–207, 2011). In this study, we investigate the effect of numerical values on responses to five questions measured using 11-point bipolar scales. These questions asked for evaluations of the general impact of climate change and its effects on different groups. Respondents were randomly assigned to scales ranging from 0 to 10, or from − 5 to + 5. The scales were presented horizontally and had identical verbal endpoints anchored as “extremely negative” and “extremely positive”. The experiment was embedded in a cross-national face-to-face survey conducted in Hungary, Portugal, and Great Britain. Contrary to prior research (Schwarz et al. in Pub Opin Q 55(4):570–582, 1991; O’Muircheartaigh et al. J Off Stat 11:295–308, 1995; Tourangeau et al. in Pub Opin Q 71(1):91–112, 2007), our analyses show an opposite trend: the means tend to be consistently and significantly lower for the − 5/+5 scale. The discrepancy between our findings and previous studies suggests that the interpretations of the 0/10 and − 5/+5 scales could be item specific. The implications of these findings and how they fit with previous work are discussed.

Many scholars have studied the effects of economic conditions on subjective well-being, but scarce attention has been paid to the effect of cultural and social determinants on quality of life. This study aims to analyse the effect of social cohesion considered as a characteristic of a country on subjective quality of life. In addition, we also tested the moderating effect of social cohesion on the relationship between income and placement in society with quality of life. To test our hypotheses we estimated a multilevel regression model. First, we estimated the null model, which showed that almost a quarter of the variance in quality of life is located at country level. Second, we included in the model all the level-1 predictors. This model highlighted that self-evaluated position on the social ladder has a larger positive effect than income on quality of life. In the third step, we added country-level predictors. Controlling for other macro factors—GDP, Life Expectancy, Gini coefficient and Homicide rate—and individual-level variables, we shows that Cohesion exerts a positive effect on subjective quality of life. The model also points out that country’s economic conditions (measured by GDP) do not affect quality of life when we control this relationship for social cohesion. Interestingly, also the within-country economic disparities (measured by Gini coefficient) do not seem to affect quality of life when cohesion is taken into account. Finally, we also shows that the positive effect of income on quality of life is moderated by cohesion. In other words, income is a relatively less important factor in determining quality of life in countries with higher levels of cohesion. In the same way, individuals’ position and perception of their placement on the social ladder affects in a lesser extent their quality of life in those countries that have higher degrees of cohesion.