Why Are Human Epistemic Agents Not Displaced in Machine Learning Scientific Inquiries? : A Practice Perspective on ML in Science

dc.contributor.authorStyger, Sahra A.
dc.contributor.authorde Heer Kloots, Marianne
dc.contributor.authorvan der Wal, Oskar
dc.contributor.authorRusso, Federica
dc.date.accessioned2026-01-21T08:15:55Z
dc.date.available2026-01-21T08:15:55Z
dc.date.issued2026
dc.description.abstractThis chapter considers machine learning (ML) practices used in science. Because ML practices enjoy increasing degrees of automation at various stages of the process, the question whether human epistemic agents are displaced arises. We first point out that shifting focus from the ML outputs to the practice of designing and using ML models allows one to appreciate the role of different actors in this process, from the human designers and modelers to the algorithms themselves. We illustrate this point with a description of ML-based practices in neuroscience. We then go further with problematizing the role of human epistemic agents in ML and argue that they are not displaced.
dc.description.versionpublisheddeu
dc.identifier.doi10.1007/978-3-032-03083-2_15
dc.identifier.ppn1949837017
dc.identifier.urihttps://kops.uni-konstanz.de/handle/123456789/75791
dc.language.isoeng
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectHuman epistemic agents
dc.subjectArtificial agents
dc.subjectML practices
dc.subjectNLP
dc.subjectCognitive neuroscience
dc.subjectAlgorithmic bias
dc.subjectHuman displacement
dc.subjectHuman-in-the-loop
dc.subject.ddc100
dc.titleWhy Are Human Epistemic Agents Not Displaced in Machine Learning Scientific Inquiries? : A Practice Perspective on ML in Scienceeng
dc.typeINCOLLECTION
dspace.entity.typePublication
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  title={Why Are Human Epistemic Agents Not Displaced in Machine Learning Scientific Inquiries? : A Practice Perspective on ML in Science},
  year={2026},
  doi={10.1007/978-3-032-03083-2_15},
  number={527},
  isbn={978-3-032-03082-5},
  address={Cham},
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  series={Synthese Library (SYLI)},
  booktitle={Philosophy of Science for Machine Learning : Core Issues and New Perspectives},
  pages={315--337},
  editor={Durán, Juan M. and Pozzi, Giorgia},
  author={Styger, Sahra A. and de Heer Kloots, Marianne and van der Wal, Oskar and Russo, Federica}
}
kops.citation.iso690STYGER, Sahra A., Marianne DE HEER KLOOTS, Oskar VAN DER WAL, Federica RUSSO, 2026. Why Are Human Epistemic Agents Not Displaced in Machine Learning Scientific Inquiries? : A Practice Perspective on ML in Science. In: DURÁN, Juan M., Hrsg., Giorgia POZZI, Hrsg.. Philosophy of Science for Machine Learning : Core Issues and New Perspectives. Cham: Springer, 2026, S. 315-337. Synthese Library (SYLI). 527. ISBN 978-3-032-03082-5. Verfügbar unter: doi: 10.1007/978-3-032-03083-2_15deu
kops.citation.iso690STYGER, Sahra A., Marianne DE HEER KLOOTS, Oskar VAN DER WAL, Federica RUSSO, 2026. Why Are Human Epistemic Agents Not Displaced in Machine Learning Scientific Inquiries? : A Practice Perspective on ML in Science. In: DURÁN, Juan M., ed., Giorgia POZZI, ed.. Philosophy of Science for Machine Learning : Core Issues and New Perspectives. Cham: Springer, 2026, pp. 315-337. Synthese Library (SYLI). 527. ISBN 978-3-032-03082-5. Available under: doi: 10.1007/978-3-032-03083-2_15eng
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kops.sourcefieldDURÁN, Juan M., Hrsg., Giorgia POZZI, Hrsg.. <i>Philosophy of Science for Machine Learning : Core Issues and New Perspectives</i>. Cham: Springer, 2026, S. 315-337. Synthese Library (SYLI). 527. ISBN 978-3-032-03082-5. Verfügbar unter: doi: 10.1007/978-3-032-03083-2_15deu
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kops.sourcefield.plainDURÁN, Juan M., ed., Giorgia POZZI, ed.. Philosophy of Science for Machine Learning : Core Issues and New Perspectives. Cham: Springer, 2026, pp. 315-337. Synthese Library (SYLI). 527. ISBN 978-3-032-03082-5. Available under: doi: 10.1007/978-3-032-03083-2_15eng
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source.titlePhilosophy of Science for Machine Learning : Core Issues and New Perspectives

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