Users' Experiences of Algorithm-Mediated Public Services: Folk Theories, Trust, and Strategies in the Global South

Lopez, Claudia; Davidoff, Alexandra; Luco, Francisca; Humeres, Monica; Correa, Teresa

Abstract

Despite the increasing prevalence of algorithm-mediated public services, there continues to be a limited understanding of citizens' perspectives on this matter, particularly in the Global South. This study explores citizens' experiences as users and affected stakeholders of algorithm-supported decision-making. From a qualitative perspective, we conducted and analyzed face-to-face interviews (N = 27) in Santiago, Chile. From the standpoint of folk theories as behavior guides, we identified that people tend to associate AI and algorithms with expanding the State's monitoring, organizing, and decision-making capacity. At the same time, they express a prevailing sense of trust, but with certain boundaries. This trust is influenced by factors, such as a belief in AI's future promise, a need for human mediation, and limitations related to structural inequalities. These findings underscore the responsibility placed on technology developers and public policymakers, emphasizing the importance of adopting an intersectional and position-based approach to AI design.

Más información

Título según WOS: Users' Experiences of Algorithm-Mediated Public Services: Folk Theories, Trust, and Strategies in the Global South
Título según SCOPUS: ID SCOPUS_ID:85194727931 Not found in local SCOPUS DB
Título de la Revista: INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
Fecha de publicación: 2024
DOI:

10.1080/10447318.2024.2356910

Notas: ISI, SCOPUS