| 1. |
- Kaun, Anne, 1983-, et al.
(författare)
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Automating public administration : Citizens’ attitudes towards automated decision-making across Estonia, Sweden, and Germany
- 2024
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Ingår i: Information, Communication and Society. - : Taylor & Francis. - 1369-118X .- 1468-4462. ; 27:2, s. 314-332
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Tidskriftsartikel (refereegranskat)abstract
- Although algorithms are increasingly used for enabling the automation of tasks in public administration of welfare states, the citizens’ knowledge of, experiences with and attitudes towards automated decision-making (ADM) in public administration are still less known. This article strives to reveal the perspectives of citizens who are increasingly exposed to ADM systems, relying on a comparative analysis of a representative survey conducted in Estonia, Germany, and Sweden. The findings show that there are important differences between the three countries when it comes to awareness, trust, and perceived suitability of ADM in public administration, which map onto historical differences in welfare provisions or so-called welfare regimes.
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| 2. |
- Kaun, Anne, 1983-, et al.
(författare)
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Automation scenarios : citizen attitudes towards automated decision-making in the public sector
- 2024
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Ingår i: Information, Communication and Society. - : Routledge. - 1369-118X .- 1468-4462.
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Tidskriftsartikel (refereegranskat)abstract
- This article explores citizen attitudes towards automated decision-making (ADM) in the public sector, addressing concerns related to social justice and transparency. ADM, used in diverse public services, such as benefit application processing, welfare fraud detection and tax calculation, has sparked public interest and scepticism. To shed light on this complex issue and make ADM more accessible for citizens, we presented three domain-specific scenarios in a population-representative survey in Estonia (n = 1,500), Germany (n = 2,001) and Sweden (n = 1,000). These scenarios involved job seeker categorisation, child welfare risk assessment and predictive policing through facial recognition. Drawing from this survey and adopting an exploratory approach, we analyse attitudes across responses to these scenarios and conduct a regression analysis, integrating individual variables such as age, gender, education, awareness, enthusiasm and trust in ADM systems. Our findings reveal differences in citizens' attitudes based on welfare regimes and individual characteristics. This citizen-focused approach underscores the significance of involving citizens in the governance of ADM in the digital welfare state, transcending the traditional regulatory and stakeholder-centric perspectives.
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| 3. |
- Masso, Anu, et al.
(författare)
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Basic values in artificial intelligence : comparative factor analysis in Estonia, Germany, and Sweden
- 2023
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Ingår i: AI & Society. - 0951-5666 .- 1435-5655.
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Tidskriftsartikel (refereegranskat)abstract
- Increasing attention is paid to ethical issues and values when designing and deploying artificial intelligence (AI). However, we do not know how those values are embedded in artificial artefacts or how relevant they are to the population exposed to and interacting with AI applications. Based on literature engaging with ethical principles and moral values in AI, we designed an original survey instrument, including 15 value components, to estimate the importance of these values to people in the general population. The article is based on representative surveys conducted in Estonia, Germany, and Sweden (n = 4501), which have varying experiences with implementing AI. The factor analysis showed four underlying dimensions of values embedded in the design and use of AI: (1) protection of personal interests to ensure social benefit, (2) general monitoring to ensure universal solidarity, (3) ensuring social diversity and social sustainability, and (4) efficiency. We found that value types can be ordered along the two dimensions of resources and change. The comparison between countries revealed that some dimensions, like social diversity and sustainability evaluations, are more universally valued among individuals, countries, and domains. Based on our analysis, we suggest a need and a framework for developing basic values in AI.
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| 4. |
- Masso, Anu, et al.
(författare)
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Citizens’ perspectives on platformisation of police work : a scenario and story-based exploration in Estonia and Sweden
- 2024
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Ingår i: Information, Communication and Society. - : Routledge. - 1369-118X .- 1468-4462. ; , s. 1-19
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Tidskriftsartikel (refereegranskat)abstract
- The integration of automated decision-making systems has transformed police work and our understanding of security and surveillance. Despite a growing theoretical literature on shifts in policing due to widespread analytical platform adoption, the public's understanding and perception of these changes are largely unexplored. This study aims to bridge this gap by empirically examining citizens’ perspectives on the new dynamics of police work in two societies with varying levels of experience with automation in the public sector: Estonia and Sweden. By combining data from a representative, scenario-based quantitative survey conducted among the general population (n = 2500) and qualitative storytelling techniques implemented in classroom settings with students (n = 23) who take classes with a focus on critical data studies, this research seeks to investigate people’s imaginaries, concerns, and expectations regarding predictive policing. The findings shed light on the observation that, in the era of data, the police are not solely perceived as an institution ensuring security or as a source of citizen apprehension related to surveillance. Rather, the transformations in police work are understood as ‘distant technologies’, wherein individuals, be they, citizens, or police officers, are increasingly removed from the direct application of these technologies. This article uncovers that when citizens possess low levels of trust in the police, the implementation of automation can further exacerbate the disconnect between citizens and the state. Furthermore, this research proposes an innovative approach to studying automated systems by combining scenario-based and storytelling methods, thereby making a valuable contribution to methodologies employed in the study of data.
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