---
_id: '59716'
abstract:
- lang: eng
  text: Against the background of the increasing importance of digitization in health
    care, the paper examines how medical practitioners who are involved in the development
    of digital health technologies legitimate and criticize the implementation and
    use of digital health technologies. Adopting an institutional logics perspective,
    the study is based on qualitative interviews with persons working at the interface
    of medicine and digital technologies development in Switzerland. The findings
    indicate that the developers believe that digital health technologies could harmonize
    current conflicts between an increasing economization of the health care system
    and professional–ethical demands. At the same time, however, they show that digital
    technologies can undermine the demand for medical autonomy, a central element
    of the medical ethos. </jats:p>
author:
- first_name: Sarah
  full_name: Lenz, Sarah
  last_name: Lenz
citation:
  ama: 'Lenz S. “More like a support tool”: Ambivalences around digital health from
    medical developers’ perspective. <i>Big Data &#38;amp; Society</i>. 2021;8(1).
    doi:<a href="https://doi.org/10.1177/2053951721996733">10.1177/2053951721996733</a>'
  apa: 'Lenz, S. (2021). “More like a support tool”: Ambivalences around digital health
    from medical developers’ perspective. <i>Big Data &#38;amp; Society</i>, <i>8</i>(1).
    <a href="https://doi.org/10.1177/2053951721996733">https://doi.org/10.1177/2053951721996733</a>'
  bibtex: '@article{Lenz_2021, title={“More like a support tool”: Ambivalences around
    digital health from medical developers’ perspective}, volume={8}, DOI={<a href="https://doi.org/10.1177/2053951721996733">10.1177/2053951721996733</a>},
    number={1}, journal={Big Data &#38;amp; Society}, publisher={SAGE Publications},
    author={Lenz, Sarah}, year={2021} }'
  chicago: 'Lenz, Sarah. “‘More like a Support Tool’: Ambivalences around Digital
    Health from Medical Developers’ Perspective.” <i>Big Data &#38;amp; Society</i>
    8, no. 1 (2021). <a href="https://doi.org/10.1177/2053951721996733">https://doi.org/10.1177/2053951721996733</a>.'
  ieee: 'S. Lenz, “‘More like a support tool’: Ambivalences around digital health
    from medical developers’ perspective,” <i>Big Data &#38;amp; Society</i>, vol.
    8, no. 1, 2021, doi: <a href="https://doi.org/10.1177/2053951721996733">10.1177/2053951721996733</a>.'
  mla: 'Lenz, Sarah. “‘More like a Support Tool’: Ambivalences around Digital Health
    from Medical Developers’ Perspective.” <i>Big Data &#38;amp; Society</i>, vol.
    8, no. 1, SAGE Publications, 2021, doi:<a href="https://doi.org/10.1177/2053951721996733">10.1177/2053951721996733</a>.'
  short: S. Lenz, Big Data &#38;amp; Society 8 (2021).
date_created: 2025-04-29T12:51:21Z
date_updated: 2025-04-29T12:57:42Z
doi: 10.1177/2053951721996733
intvolume: '         8'
issue: '1'
language:
- iso: eng
publication: Big Data &amp; Society
publication_identifier:
  issn:
  - 2053-9517
  - 2053-9517
publication_status: published
publisher: SAGE Publications
status: public
title: '“More like a support tool”: Ambivalences around digital health from medical
  developers’ perspective'
type: journal_article
user_id: '116246'
volume: 8
year: '2021'
...
---
_id: '28148'
abstract:
- lang: eng
  text: '<jats:p> The potential for biases being built into algorithms has been known
    for some time (e.g., Friedman and Nissenbaum, 1996), yet literature has only recently
    demonstrated the ways algorithmic profiling can result in social sorting and harm
    marginalised groups (e.g., Browne, 2015; Eubanks, 2018; Noble, 2018). We contend
    that with increased algorithmic complexity, biases will become more sophisticated
    and difficult to identify, control for, or contest. Our argument has four steps:
    first, we show how harnessing algorithms means that data gathered at a particular
    place and time relating to specific persons, can be used to build group models
    applied in different contexts to different persons. Thus, privacy and data protection
    rights, with their focus on individuals (Coll, 2014; Parsons, 2015), do not protect
    from the discriminatory potential of algorithmic profiling. Second, we explore
    the idea that anti-discrimination regulation may be more promising, but acknowledge
    limitations. Third, we argue that in order to harness anti-discrimination regulation,
    it needs to confront emergent forms of discrimination or risk creating new invisibilities,
    including invisibility from existing safeguards. Finally, we outline suggestions
    to address emergent forms of discrimination and exclusionary invisibilities via
    intersectional and post-colonial analysis. </jats:p>'
article_number: '205395171989580'
author:
- first_name: Monique
  full_name: Mann, Monique
  last_name: Mann
- first_name: Tobias
  full_name: Matzner, Tobias
  id: '65695'
  last_name: Matzner
citation:
  ama: 'Mann M, Matzner T. Challenging algorithmic profiling: The limits of data protection
    and anti-discrimination in responding to emergent discrimination. <i>Big Data
    &#38; Society</i>. 2019;6(2). doi:<a href="https://doi.org/10.1177/2053951719895805">https://doi.org/10.1177/2053951719895805</a>'
  apa: 'Mann, M., &#38; Matzner, T. (2019). Challenging algorithmic profiling: The
    limits of data protection and anti-discrimination in responding to emergent discrimination.
    <i>Big Data &#38; Society</i>, <i>6</i>(2), Article 205395171989580. <a href="https://doi.org/10.1177/2053951719895805">https://doi.org/10.1177/2053951719895805</a>'
  bibtex: '@article{Mann_Matzner_2019, title={Challenging algorithmic profiling: The
    limits of data protection and anti-discrimination in responding to emergent discrimination},
    volume={6}, DOI={<a href="https://doi.org/10.1177/2053951719895805">https://doi.org/10.1177/2053951719895805</a>},
    number={2205395171989580}, journal={Big Data &#38; Society}, author={Mann, Monique
    and Matzner, Tobias}, year={2019} }'
  chicago: 'Mann, Monique, and Tobias Matzner. “Challenging Algorithmic Profiling:
    The Limits of Data Protection and Anti-Discrimination in Responding to Emergent
    Discrimination.” <i>Big Data &#38; Society</i> 6, no. 2 (2019). <a href="https://doi.org/10.1177/2053951719895805">https://doi.org/10.1177/2053951719895805</a>.'
  ieee: 'M. Mann and T. Matzner, “Challenging algorithmic profiling: The limits of
    data protection and anti-discrimination in responding to emergent discrimination,”
    <i>Big Data &#38; Society</i>, vol. 6, no. 2, Art. no. 205395171989580, 2019,
    doi: <a href="https://doi.org/10.1177/2053951719895805">https://doi.org/10.1177/2053951719895805</a>.'
  mla: 'Mann, Monique, and Tobias Matzner. “Challenging Algorithmic Profiling: The
    Limits of Data Protection and Anti-Discrimination in Responding to Emergent Discrimination.”
    <i>Big Data &#38; Society</i>, vol. 6, no. 2, 205395171989580, 2019, doi:<a href="https://doi.org/10.1177/2053951719895805">https://doi.org/10.1177/2053951719895805</a>.'
  short: M. Mann, T. Matzner, Big Data &#38; Society 6 (2019).
date_created: 2021-11-30T16:25:46Z
date_updated: 2023-03-17T10:30:05Z
department:
- _id: '757'
doi: https://doi.org/10.1177/2053951719895805
intvolume: '         6'
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.1177/2053951719895805
oa: '1'
publication: Big Data & Society
publication_identifier:
  issn:
  - 2053-9517
  - 2053-9517
publication_status: published
status: public
title: 'Challenging algorithmic profiling: The limits of data protection and anti-discrimination
  in responding to emergent discrimination'
type: journal_article
user_id: '49063'
volume: 6
year: '2019'
...