Er norsk offentlig sektor klar for KI-revolusjonen?
Sluttkonferanse for fAIrgov-prosjektet Tid:12. juni, 2025 kl.09.00-12.00. Sted: Lillesalen, Kulturhuset i Bergen
Utviklingen innen kunstig intelligens har skutt fart de senere årene. Teknologien har blitt sammenliknet med elektrisitet når det gjelder mulighetene den har til å forandre samfunnet. Hva bør norsk offentlig sektor gjøre for å utnytte potensialet i kunstig intelligens, og hvilke utfordringer står vi overfor? Konferansen retter et spesielt fokus mot politiske aspekter ved bruk av KI i offentlig sektor, og spør hvordan tilliten til myndighetene best ivaretas. Er innbyggerne i Norge klar for å bli saksbehandlet av en offentlig sektor som bruker kunstig intelligens? Hvor stor er støtten i befolkningen, og kan bruken gå ut over legitimiteten til institusjonene?
Forskere og sentrale offentlige institusjoner legger fram sine perspektiver og møter til debatt.
Møtet ble tatt opp, og kan sees her
Program
Konferansier: Troy Saghaug Broderstad, UiT
09.00-09.30: Dørene åpner, kaffe og mingling
09.30-09.45: Hele prosjektet ønsker velkommen og Camilla Stoltenberg åpner dagen
09.45-10.05: Case: Kunstig intelligens i Skatteetaten / Nina Serdarevic
10.05-10.25: Case: Kunstig intelligens i NAV / Robindra Prabhu
10.25-10.45: Pause
10.45-11.05: Støtter befolkningen bruk av kunstig intelligens? / Mikael Poul Johannesson, NORCE
11.05-11.50: Panelsamtale: Hva skal til for at norsk offentlig sektor skal bli klar for KI-revolusjonen? / Camilla Stoltenberg, Annette Fagerhaug Stephansen, Sveinung Arnesen, Nina Serdarevic, Robindra Prabhu
11.50-12.00: Avslutning / Sveinung Arnesen, prosjektleder fAIrgov
12.00-14.00: Lunsj med mingling og forskningskroker
Målgruppe
Konferansen egner seg for forskere, politikere, offentlig ansatte og alle andre som har interesse for kunstig intelligens og offentlig sektor.
Mer om prosjektet (engelsk)
Public Fairness Perceptions of Algorithmic Governance (fAIrgov)
Short description: Algorithms based on artificial intelligence are increasingly being used by governments to make decisions that impact citizens’ lives. While significant attention has been devoted to theoretical discussions on fairness, accountability, transparency and trust, less is known about citizens’ perspectives. The fAIrgov project has since 2018 tracked the views of citizens, poiticians, and public servants in Norway on matters such as knowledge about AI and support for using AI in the public sector.
Key preliminary findings are that knowledge of AI has increased over the years among citizens, and with it also support for using it. Significant concerns are however also expressed, and these concerns are unevenly distributed along party lines and socioeconomic demographics.
Host institution: NORCE – The Norwegian Research Centre. Partner institutions: Stanford University University of Bergen
Funder: Research Council of Norway (project no. 314411)
Researchers: Sveinung Arnesen (Principal Investigator), Mikael Poul Johannesson, Troy Saghaug Broderstad, Henrik Litleré Bentsen, Jon Kåre Skiple, Gjøri Marie Haugen, Anne Marthe Borgen, James S. Fishkin, Alice Siu
Data generating infrastructures: Coordinated Online Panels for Research on Democracy and Governance (KODEM), Stanford Online Deliberation Platform
Research
Knowledge and support for AI in the public sector: a deliberative poll experiment
Abstract: We are on the verge of a revolution in public sector decision-making processes, where computers will take over many of the governance tasks previously assigned to human bureaucrats. Governance decisions based on algorithmic information processing are increasing in numbers and scope, contributing to decisions that impact the lives of individual citizens. While significant attention in the recent few years has been devoted to normative discussions on fairness, accountability, and transparency related to algorithmic decision-making based on artificial intelligence, less is known about citizens’ considered views on this issue. To put society in-the-loop, a Deliberative Poll was thus carried out on the topic of using artificial intelligence in the public sector, as a form of in-depth public consultation. The three use cases that were selected for deliberation were refugee reallocation, a welfare-to-work program, and parole. A key finding was that after having acquired more knowledge about the concrete use cases, participants were overall more supportive of using artificial intelligence in the decision processes. The event was set up with a pretest/post-test control group experimental design, and as such, the results offer experimental evidence to extant observational studies showing positive associations between knowledge and support for using artificial intelligence.
Suggested citation: Arnesen, S., Broderstad, T.S., Fishkin, J.S. et al. Knowledge and support for AI in the public sector: a deliberative poll experiment. AI & Soc (2024). https://doi.org/10.1007/s00146-024-02104-w
Differences between Citizens, Elected Representatives and Public Administrators Attitudes Towards AI in the Public Sector
Abstract: This study compares attitudes toward Artificial Intelligence (AI) use in the public sector among elected representatives, public administrators, and citizens. Elected representatives enact policies that facilitate AI integration in decision-making, while public administrators implement these policies, often with greater insight into how AI affects their roles. Citizens, on the other hand, are directly impacted by these decisions and hold elected officials accountable for their AI governance. Given the increasing use of AI in public administration, understanding how attitudes differ across these groups is important: Misalignment could lead to overstepping in algorithmic governance that may erode trust in public institutions over time. We surveyed a representative panel of citizens (N=4206), elected representatives (N=1898), and public administrators (N=2979) in Norway. We assessed their knowledge about AI, whether they believe AI will improve or worsen public services, and their support for using AI in resettling refugees. Our findings show public administrators are most optimistic about AI improving public services, have the highest self-reported knowledge, and are most supportive of using AI in refugee resettlement. Elected representatives are more positive than citizens but less so than public administrators. Citizens are the most sceptical of, reporting the lowest levels of AI knowledge. These results highlight significant differences and have important implications for algorithmic governance.
Keywords: Artificial intelligence, Congruence, Bureaucrats
Suggested Citation: Broderstad, Troy S. and Arnesen, Sveinung and Johannesson, Mikael Poul, Differences between Citizens, Elected Representatives and Public Administrators Attitudes Towards AI in the Public Sector (February 06, 2025). Available at SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5126671
Who Deliberate? Participation and Recruitment in Deliberative Mini-Publics
What characterize citizens who choose to participate in deliberative mini-publics? Using population registry data from Norway, we compare socio-demographic attributes among participants and non-participants in two Deliberative Polls conducted in 2021 and 2022, the latter on the topic of using AI in the public sector. We find that most citizens decline invitations to take part, whereas those who do participate are fairly representative of the population even without targeted recruitment strategies such as using quotas or stratified sampling. Some social groups that have shown low participation in elections-such as younger cohorts and immigrants-are well represented in the deliberative mini-publics without needing any extra recruiting efforts, showing that it indeed is possible to combine the democratic principles of equal opportunities and representative deliberative mini-publics. Following up with conjoint experimental data, we find that increasing the monetary incentives increase willingness to participate, as do events where citizens are invited based on random selection rather than pure self-selection. Finally, willingness to participate increases when participants are not required to publicly reveal their attitudes on the topics under consideration. The study contributes both to the study of representation in deliberation as well as to practical knowledge about recruitment and participation in deliberative mini-publics.
Keywords: Deliberative mini-publics, Representativeness, Participation, Recruitment, Conjoint analysis, Population registry data
Suggested Citation: Arnesen, Sveinung and Skiple, Jon Kåre, Who Deliberate? Participation and Recruitment in Deliberative Mini-Publics (February 10, 2025). Available at SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5130755
How government uses of artificial intelligence affect the perceived warmth and competence of civil servants
This article tests the argument that the reliance on AI systems affects people’s affective ties to government employees using AI systems. Drawing on social cognition theory, it examines how AI use influences the perceived warmth of public servants and the acceptability of decision-making. It distinguishes between two settings in the education system that differ regarding how directly citizens are affected by AI use, a teacher using AI to help assess students and a public servant allocating funds among schools. The analysis is based on a pre-registered vignette experiment and a sample of 4,569 participants from Norway. It finds that AI use decreases both the perceived warmth and competence of public servants, that these evaluations negatively bear on the overall acceptability of decision-making, and that the effect of AI use is stronger for public servants more directly interacting with citizens. The findings have important implications for the legitimacy of public organizations.
Keywords: decision-making; artificial intelligence; social cognition; warmth; experiment; education
Suggested citation: König, P., & Arnesen, S. (2025, May 3). How government uses of artificial intelligence affect the perceived warmth and competence of civil servants. https://doi.org/10.31235/osf.io/732ez_v1
How Using Artificial Intelligence in Public Administration Shifts Citizens’ Expectations of Street-Level Bureaucracy
This paper examines the impact of Artificial Intelligence (AI) on citizens’ expectations of street-level bureaucrats. Using survey experiments fielded in The Norwegian Citizen Panel, we assess how AI’s role as a decision-support tool affects the importance citizens place on various bureaucratic traits. Our findings suggest that when street-level bureaucrats use AI, citizens will sometimes want bureaucrats that are more similar to themselves, and also tend to consider bureaucrats’ technical expertise as less important. This suggests that as AI takes on more of the technical judgments that is part of bureaucratic decision-making, citizens place greater importance on the human elements of bureaucracy, such as shared experiences and empathy. This research highlights the growing need to understand how the use of AI will shift citizens’ expectations of public institutions.
Keywords: AI; Street-level bureaucracy; Representative Bureaucracy
Suggested citation: Johannesson, M. P., & Arnesen, S. (2025, June 11). How Using Artificial Intelligence in Public Administration Shifts Citizens’ Expectations of Street-Level Bureaucracy. https://doi.org/10.31235/osf.io/8r36s_v1