Trust‐Affording Action: Citizens’ Everyday Relations With Algorithmized Public Services

Finland is considered a society of high trust. Finnish citizens’ trust in public administration and institutions is clearly above the OECD average, and there is broad consensus on the virtues of maintaining high societal trust. As high‐trust public institutions are now turning to new efficiency‐promising AI technologies, it is important to ask: “How are these [technologies] then capable of upholding that trust?” This question is a direct quote from our fieldwork following Finnish citizens’ everyday trust‐building with new AI‐infused services. Based on a trust‐focused reading of our qualitative data, we propose an approach to trust that affords greater empirical nuance than alternative conceptions, which we see as limited for following the evolving dynamics of citizens’ trust in new technologies. The approach we are developing situates trust within a processual conception of action and highlights the need to also grasp the “quieter”—embodied, habitualized, and intuitive—forms of trust as part of its living dynamic. We then apply this approach to examine the adoption of the Finnish Covid‐19 tracing application and citizens’ perceptions of algorithmically infused services provided by Finland’s social insurance institution. We highlight creative tactics that citizens use to establish trust: the agent heuristic, the case heuristic, the social heuristic, and the interaction heuristic. Our research contributes to a nuanced understanding of trust and its situated dynamics from the citizen perspective, a focus we consider crucial at a time of unprecedented excitement around the transformation of high‐trust institutions through algorithmic technologies.