---
_id: '62031'
abstract:
- lang: eng
  text: 'The field of fair AI aims to counter biased algorithms through computational
    modelling. However, it faces increasing criticism for perpetuating the use of
    overly technical and reductionist methods. As a result, novel approaches appear
    in the field to address more socially-oriented and interdisciplinary (SOI) perspectives
    on fair AI. In this paper, we take this dynamic as the starting point to study
    the tension between computer science (CS) and SOI research. By drawing on STS
    and CSCW theory, we position fair AI research as a matter of ''organizational
    alignment'': what makes research ''doable'' is the successful alignment of three
    levels of work organization (the social world, the laboratory, and the experiment).
    Based on qualitative interviews with CS researchers, we analyze the tasks, resources,
    and actors required for doable research in the case of fair AI. We find that CS
    researchers engage with SOI research to some extent, but organizational conditions,
    articulation work, and ambiguities of the social world constrain the doability
    of SOI research for them. Based on our findings, we identify and discuss problems
    for aligning CS and SOI as fair AI continues to evolve.'
author:
- first_name: Miriam
  full_name: Fahimi, Miriam
  id: '118059'
  last_name: Fahimi
  orcid: 0000-0002-0619-3160
- first_name: Mayra
  full_name: Russo, Mayra
  last_name: Russo
- first_name: Kristen M.
  full_name: Scott, Kristen M.
  last_name: Scott
- first_name: Maria-Esther
  full_name: Vidal, Maria-Esther
  last_name: Vidal
- first_name: Bettina
  full_name: Berendt, Bettina
  last_name: Berendt
- first_name: Katharina
  full_name: Kinder-Kurlanda, Katharina
  last_name: Kinder-Kurlanda
citation:
  ama: Fahimi M, Russo M, Scott KM, Vidal M-E, Berendt B, Kinder-Kurlanda K. Articulation
    Work and Tinkering for Fairness in Machine Learning. <i>Proceedings of the ACM
    on Human-Computer Interaction</i>. 2024;8(CSCW2):1-23. doi:<a href="https://doi.org/10.1145/3686973">10.1145/3686973</a>
  apa: Fahimi, M., Russo, M., Scott, K. M., Vidal, M.-E., Berendt, B., &#38; Kinder-Kurlanda,
    K. (2024). Articulation Work and Tinkering for Fairness in Machine Learning. <i>Proceedings
    of the ACM on Human-Computer Interaction</i>, <i>8</i>(CSCW2), 1–23. <a href="https://doi.org/10.1145/3686973">https://doi.org/10.1145/3686973</a>
  bibtex: '@article{Fahimi_Russo_Scott_Vidal_Berendt_Kinder-Kurlanda_2024, title={Articulation
    Work and Tinkering for Fairness in Machine Learning}, volume={8}, DOI={<a href="https://doi.org/10.1145/3686973">10.1145/3686973</a>},
    number={CSCW2}, journal={Proceedings of the ACM on Human-Computer Interaction},
    publisher={Association for Computing Machinery (ACM)}, author={Fahimi, Miriam
    and Russo, Mayra and Scott, Kristen M. and Vidal, Maria-Esther and Berendt, Bettina
    and Kinder-Kurlanda, Katharina}, year={2024}, pages={1–23} }'
  chicago: 'Fahimi, Miriam, Mayra Russo, Kristen M. Scott, Maria-Esther Vidal, Bettina
    Berendt, and Katharina Kinder-Kurlanda. “Articulation Work and Tinkering for Fairness
    in Machine Learning.” <i>Proceedings of the ACM on Human-Computer Interaction</i>
    8, no. CSCW2 (2024): 1–23. <a href="https://doi.org/10.1145/3686973">https://doi.org/10.1145/3686973</a>.'
  ieee: 'M. Fahimi, M. Russo, K. M. Scott, M.-E. Vidal, B. Berendt, and K. Kinder-Kurlanda,
    “Articulation Work and Tinkering for Fairness in Machine Learning,” <i>Proceedings
    of the ACM on Human-Computer Interaction</i>, vol. 8, no. CSCW2, pp. 1–23, 2024,
    doi: <a href="https://doi.org/10.1145/3686973">10.1145/3686973</a>.'
  mla: Fahimi, Miriam, et al. “Articulation Work and Tinkering for Fairness in Machine
    Learning.” <i>Proceedings of the ACM on Human-Computer Interaction</i>, vol. 8,
    no. CSCW2, Association for Computing Machinery (ACM), 2024, pp. 1–23, doi:<a href="https://doi.org/10.1145/3686973">10.1145/3686973</a>.
  short: M. Fahimi, M. Russo, K.M. Scott, M.-E. Vidal, B. Berendt, K. Kinder-Kurlanda,
    Proceedings of the ACM on Human-Computer Interaction 8 (2024) 1–23.
date_created: 2025-10-31T15:10:31Z
date_updated: 2025-11-18T09:56:04Z
doi: 10.1145/3686973
extern: '1'
intvolume: '         8'
issue: CSCW2
language:
- iso: eng
page: 1-23
publication: Proceedings of the ACM on Human-Computer Interaction
publication_identifier:
  issn:
  - 2573-0142
publication_status: published
publisher: Association for Computing Machinery (ACM)
status: public
title: Articulation Work and Tinkering for Fairness in Machine Learning
type: journal_article
user_id: '118059'
volume: 8
year: '2024'
...