Making sense of algorithms

Relational perception of contact tracing and risk assessment during Covid-19

Dados Bibliográficos

ID5260985
AutoresChuncheng Liu (0000-0001-5842-7988, University of California San Diego), Ross Graham (0000-0003-4578-7022, University of California San Diego)
Ano2021
Volume8
Fascículo1
Data de publicação2021-01-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoBig Data & Society (JOURNAL)
Identificadores do periódicoISSN: 2053-9517 • E-ISSN: 2053-9517
EditoraSAGE Publications Inc (PUBLISHER)
DOI10.1177/2053951721995218
OpenAlexW3118801830
IdiomaEN
Citações recebidas39
Referências citadas38

Governments and citizens of nearly every nation have been compelled to respond to COVID-19. Many measures have been adopted, including contact tracing and risk assessment algorithms, whereby citizen whereabouts are monitored to trace contact with other infectious individuals in order to generate a risk status via algorithmic evaluation. Based on 38 in-depth interviews, we investigate how people make sense of Health Code ( jiankangma), the Chinese contact tracing and risk assessment algorithmic sociotechnical assemblage. We probe how people accept or resist Health Code by examining their ongoing, dynamic, and relational interactions with it. Participants display a rich variety of attitudes toward privacy and surveillance, ranging from fatalism to the possibility of privacy to trade-offs for surveillance in exchange for public health, which is mediated by the perceived effectiveness of Health Code and changing views on the intentions of institutions who deploy it. We show how perceived competency varies not just on how well the technology works, but on the social and cultural enforcement of various non-technical aspects like quarantine, citizen data inputs, and cell reception. Furthermore, we illustrate how perceptions of Health Code are nested in people's broader interpretations of disease control at the national and global level, and unexpectedly strengthen the Chinese authority's legitimacy. None of the Chinese public, Health Code, or people's perceptions toward Health Code are predetermined, fixed, or categorically consistent, but are co-constitutive and dynamic over time. We conclude with a theorization of a relational perception and methodological reflections to study algorithmic sociotechnical assemblages beyond COVID-19

Contact tracing · Disease · Internet privacy · Political science · Public health · Public relations · Sociology · Sociotechnical system · Computer Science · COVID-19 Digital Contact Tracing · Ethics and Social Impacts of AI · Global Security and Public Health · Medicine · Psychology · Social Psychology · Artificial Intelligence