Making sense of algorithms: Relational perception of contact tracing and risk assessment during COVID-19. Issue 1 (February 2021)
- Record Type:
- Journal Article
- Title:
- Making sense of algorithms: Relational perception of contact tracing and risk assessment during COVID-19. Issue 1 (February 2021)
- Main Title:
- Making sense of algorithms: Relational perception of contact tracing and risk assessment during COVID-19
- Authors:
- Liu, Chuncheng
Graham, Ross - Abstract:
- 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 HealthGovernments 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. … (more)
- Is Part Of:
- Big data & society. Volume 8:Issue 1(2021)
- Journal:
- Big data & society
- Issue:
- Volume 8:Issue 1(2021)
- Issue Display:
- Volume 8, Issue 1 (2021)
- Year:
- 2021
- Volume:
- 8
- Issue:
- 1
- Issue Sort Value:
- 2021-0008-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-02
- Subjects:
- Sociotechnical assemblage -- algorithm -- contact tracing -- surveillance -- COVID-19
Big data -- Social aspects -- Periodicals
Social sciences -- Research -- Data processing -- Periodicals
Social sciences -- Research -- Methodology -- Periodicals
Data mining -- Periodicals
300.28557 - Journal URLs:
- http://bds.sagepub.com ↗
http://www.uk.sagepub.com/home.nav ↗ - DOI:
- 10.1177/2053951721995218 ↗
- Languages:
- English
- ISSNs:
- 2053-9517
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 15988.xml