Cited by 18Ethics and Social Impacts of AIFeminist Epistemology and Gender StudiesArtificial Intelligence in Healthcare and Education

Conversational Artificial Intelligence and the Potential for Epistemic Injustice

Open access
De Proost, Michiel, Pozzi, Giorgia·2023·The American Journal of Bioethics

Abstract

In their article, Sedlakova and Trachsel (2023) propose a holistic, ethical, and epistemic analysis of conversational artificial intelligence (CAI) in psychotherapeutic settings. They mainly descri...

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1080/15265161.2023.2191020

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The only work with a focus on the epistemic injustice of generative AI is by De Proost and Pozzi (2023), which looks at the potential of conversational AI for hermeneutical ignorance.

    “To the best of our knowledge, the only work with a focus on the epistemic injustice of generative AI is by De Proost and Pozzi (2023), which looks at the potential of conversational AI for hermeneutical ignorance.”

    From Epistemic Injustice in Generative AI (2024) · cites this paper as De Proost and Pozzi 2023

    In “Conversational Artificial Intelligence and the Potential for Epistemic Injustice” (page unavailable), the authors examine how conversational AI in psychotherapy could cause testimonial and hermeneutical injustice, including patients being unable to make sense of experiences the system cannot recognize. The copy does not identify the systems as generative AI or use the term “hermeneutical ignorance”; its stated focus is hermeneutical injustice in a specific therapeutic setting. The claim that this is the only such work is the citing authors’ own qualification, not a finding attributed to the source. (LLM, conf=0.83)

    Experimental — accuracy not yet measured
  • De Proost and Pozzi's study presents two significant limitations: its analysis is confined to textual dialogue interactions, and it does not cover multimodal systems.

    “However, this study presents two significant limitations.First, its analysis is confined to textual dialogue interactions.”

    From Epistemic Injustice in Generative AI (2024) · cites this paper as De Proost and Pozzi 2023

    In “Conversational Artificial Intelligence and the Potential for Epistemic Injustice” (page unavailable), the authors say they examine testimonial and hermeneutical injustice in conversational AI used in psychotherapy. The copy does not establish that those interactions are exclusively textual or identify the omission of multimodal systems as a limitation; searches for text-only and multimodal interactions found no such passage. (LLM, conf=0.75)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 7

  1. Kidd, I. J., and H. Carel. 2017. Epistemic injustice and illness. Journal of applied philosophy 34 (2):172-190.
  2. Kidd, I. J., Spencer, L., and H. Carel. 2022. Epistemic injustice in psychiatric research and practice. Philosophical Psychology: 1-29. doi:10.1080/09515089.2022.2156333. · DOI
  3. Mason, R. 2021. Hermeneutical Injustice. In The Routledge Handbook of Social and Political Philosophy of Language, eds. J. Khoo and R. K. Sterken. New York: Routledge.
  4. Pozzi, G. 2023a. Automated opioid risk scores: a case for machine learning-induced epistemic injustice in healthcare. Ethics and Information Technology 25 (1):3. doi:10.1007/s10676-023- 09676-z. · DOI
  5. Pozzi, G. 2023b. Testimonial injustice in medical machine learning. Journal of Medical Ethics. Doi: 10.1136/jme-2022-108630. · DOI · Paper page
  6. Sanati, A., and M. Kyratsous. 2015. Epistemic injustice in assessment of delusions. Journal of Evaluation in Clinical Practice 21 (3):479-485.
  7. Sedlakova, J., and M. Trachsel. 2022. Conversational artificial intelligence in psychotherapy: a new therapeutic tool or agent?. The American Journal of Bioethics: 1-10. doi: 10.1080/15265161.2022.2048739. · DOI

Cited by

Sorted by citations

Authors
De Proost, M., & Pozzi, G.
Affiliations
  • Ghent University
  • Delft University of Technology (NL)
Corresponding author
Pozzi, Giorgia
Venue
The American Journal of Bioethics
Published
2023-05-02
Volume
23
Issue
5
Pages
51-53
ISSN
  • 1526-5161 (ISSN-L)
  • 1536-0075
OpenAlex
W4367671225
Cited by
18
References
3
Citations by year
2026: 10 · 2025: 6 · 2024: 1 · 2022: 1
Type
journal article
Language
en
Open access
Licence
other-oa
Locations
  • The American Journal of Bioethics (publishedVersion)
  • PubMed (publishedVersion)
  • Ghent University Academic Bibliography (Ghent University) (submittedVersion, other-oa)
  • Research Repository (Delft University of Technology) (submittedVersion)
Funders
  • European Research Council
  • Research Infrastructures
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Social Sciences › Sociology and Political Science › Feminist Epistemology and Gender Studies
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
conversational AI, epistemic injustice, psychotherapy, AI ethics, therapeutic relationship, trust in AI
MeSH terms
Artificial Intelligence, Communication, Humans, Psychotherapy, Social Justice

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review