---
_id: '63611'
abstract:
- lang: eng
  text: When humans interact with artificial intelligence (AI), one desideratum is
    appropriate trust. Typically, appropriate trust encompasses that humans trust
    AI except for instances in which they either explicitly notice AI errors or are
    suspicious that errors could be present. So far, appropriate trust or related
    notions have mainly been investigated by assessing trust and reliance. In this
    contribution, we argue that these assessments are insufficient to measure the
    complex aim of appropriate trust and the related notion of healthy distrust. We
    introduce and test the perspective of covert visual attention as an additional
    indicator for appropriate trust and draw conceptual connections to the notion
    of healthy distrust. To test the validity of our conceptualization, we formalize
    visual attention using the Theory of Visual Attention and measure its properties
    that are potentially relevant to appropriate trust and healthy distrust in an
    image classification task. Based on temporal-order judgment performance, we estimate
    participants' attentional capacity and attentional weight toward correct and incorrect
    mock-up AI classifications. We observe that misclassifications reduce attentional
    capacity compared to correct classifications. However, our results do not indicate
    that this reduction is beneficial for a subsequent judgment of the classifications.
    The attentional weighting is not affected by the classifications' correctness
    but by the difficulty of categorizing the stimuli themselves. We discuss these
    results, their implications, and the limited potential for using visual attention
    as an indicator of appropriate trust and healthy distrust.
article_number: '1694367'
article_type: original
author:
- first_name: Tobias Martin
  full_name: Peters, Tobias Martin
  id: '92810'
  last_name: Peters
  orcid: 0009-0008-5193-6243
- first_name: Kai
  full_name: Biermeier, Kai
  id: '55908'
  last_name: Biermeier
  orcid: 0000-0002-2879-2359
- first_name: Ingrid
  full_name: Scharlau, Ingrid
  id: '451'
  last_name: Scharlau
  orcid: 0000-0003-2364-9489
citation:
  ama: 'Peters TM, Biermeier K, Scharlau I. Assessing healthy distrust in human-AI
    interaction: interpreting changes in visual attention. <i>Frontiers in Psychology</i>.
    2026;16. doi:<a href="https://doi.org/10.3389/fpsyg.2025.1694367">10.3389/fpsyg.2025.1694367</a>'
  apa: 'Peters, T. M., Biermeier, K., &#38; Scharlau, I. (2026). Assessing healthy
    distrust in human-AI interaction: interpreting changes in visual attention. <i>Frontiers
    in Psychology</i>, <i>16</i>, Article 1694367. <a href="https://doi.org/10.3389/fpsyg.2025.1694367">https://doi.org/10.3389/fpsyg.2025.1694367</a>'
  bibtex: '@article{Peters_Biermeier_Scharlau_2026, title={Assessing healthy distrust
    in human-AI interaction: interpreting changes in visual attention}, volume={16},
    DOI={<a href="https://doi.org/10.3389/fpsyg.2025.1694367">10.3389/fpsyg.2025.1694367</a>},
    number={1694367}, journal={Frontiers in Psychology}, publisher={Frontiers Media
    SA}, author={Peters, Tobias Martin and Biermeier, Kai and Scharlau, Ingrid}, year={2026}
    }'
  chicago: 'Peters, Tobias Martin, Kai Biermeier, and Ingrid Scharlau. “Assessing
    Healthy Distrust in Human-AI Interaction: Interpreting Changes in Visual Attention.”
    <i>Frontiers in Psychology</i> 16 (2026). <a href="https://doi.org/10.3389/fpsyg.2025.1694367">https://doi.org/10.3389/fpsyg.2025.1694367</a>.'
  ieee: 'T. M. Peters, K. Biermeier, and I. Scharlau, “Assessing healthy distrust
    in human-AI interaction: interpreting changes in visual attention,” <i>Frontiers
    in Psychology</i>, vol. 16, Art. no. 1694367, 2026, doi: <a href="https://doi.org/10.3389/fpsyg.2025.1694367">10.3389/fpsyg.2025.1694367</a>.'
  mla: 'Peters, Tobias Martin, et al. “Assessing Healthy Distrust in Human-AI Interaction:
    Interpreting Changes in Visual Attention.” <i>Frontiers in Psychology</i>, vol.
    16, 1694367, Frontiers Media SA, 2026, doi:<a href="https://doi.org/10.3389/fpsyg.2025.1694367">10.3389/fpsyg.2025.1694367</a>.'
  short: T.M. Peters, K. Biermeier, I. Scharlau, Frontiers in Psychology 16 (2026).
date_created: 2026-01-14T14:21:59Z
date_updated: 2026-01-14T14:29:03Z
department:
- _id: '424'
- _id: '660'
doi: 10.3389/fpsyg.2025.1694367
intvolume: '        16'
keyword:
- appropriate trust
- healthy distrust
- visual attention
- Theory of Visual Attention
- human-AI interaction
- Bayesian cognitive model
- image classification
language:
- iso: eng
project:
- _id: '124'
  name: 'TRR 318 ; TP C01: Gesundes Misstrauen in Erklärungen'
publication: Frontiers in Psychology
publication_identifier:
  issn:
  - 1664-1078
publication_status: published
publisher: Frontiers Media SA
status: public
title: 'Assessing healthy distrust in human-AI interaction: interpreting changes in
  visual attention'
type: journal_article
user_id: '92810'
volume: 16
year: '2026'
...
---
_id: '51343'
abstract:
- lang: eng
  text: This paper presents preliminary work on the formalization of three prominent
    cognitive biases in the diagnostic reasoning process over epileptic seizures,
    psychogenic seizures and syncopes. Diagnostic reasoning is understood as iterative
    exploration of medical evidence. This exploration is represented as a partially
    observable Markov decision process where the state (i.e., the correct diagnosis)
    is uncertain. Observation likelihoods and belief updates are computed using a
    Bayesian network which defines the interrelation between medical risk factors,
    diagnoses and potential findings. The decision problem is solved via partially
    observable upper confidence bounds for trees in Monte-Carlo planning. We compute
    a biased diagnostic exploration policy by altering the generated state transition,
    observation and reward during look ahead simulations. The resulting diagnostic
    policies reproduce reasoning errors which have only been described informally
    in the medical literature. We plan to use this formal representation in the future
    to inversely detect and classify biased reasoning in actual diagnostic trajectories
    obtained from physicians.
author:
- first_name: Dominik
  full_name: Battefeld, Dominik
  id: '91864'
  last_name: Battefeld
  orcid: 0000-0002-5480-0594
- first_name: Stefan
  full_name: Kopp, Stefan
  last_name: Kopp
citation:
  ama: 'Battefeld D, Kopp S. Formalizing cognitive biases in medical diagnostic reasoning.
    In: <i>Proceedings of the 8th Workshop on Formal and Cognitive Reasoning</i>.
    ; 2022.'
  apa: Battefeld, D., &#38; Kopp, S. (2022). Formalizing cognitive biases in medical
    diagnostic reasoning. <i>Proceedings of the 8th Workshop on Formal and Cognitive
    Reasoning</i>. 8th Workshop on Formal and Cognitive Reasoning (FCR), Trier.
  bibtex: '@inproceedings{Battefeld_Kopp_2022, title={Formalizing cognitive biases
    in medical diagnostic reasoning}, booktitle={Proceedings of the 8th Workshop on
    Formal and Cognitive Reasoning}, author={Battefeld, Dominik and Kopp, Stefan},
    year={2022} }'
  chicago: Battefeld, Dominik, and Stefan Kopp. “Formalizing Cognitive Biases in Medical
    Diagnostic Reasoning.” In <i>Proceedings of the 8th Workshop on Formal and Cognitive
    Reasoning</i>, 2022.
  ieee: D. Battefeld and S. Kopp, “Formalizing cognitive biases in medical diagnostic
    reasoning,” presented at the 8th Workshop on Formal and Cognitive Reasoning (FCR),
    Trier, 2022.
  mla: Battefeld, Dominik, and Stefan Kopp. “Formalizing Cognitive Biases in Medical
    Diagnostic Reasoning.” <i>Proceedings of the 8th Workshop on Formal and Cognitive
    Reasoning</i>, 2022.
  short: 'D. Battefeld, S. Kopp, in: Proceedings of the 8th Workshop on Formal and
    Cognitive Reasoning, 2022.'
conference:
  end_date: 2022-09-23
  location: Trier
  name: 8th Workshop on Formal and Cognitive Reasoning (FCR)
  start_date: '2022-09-19 '
date_created: 2024-02-14T09:06:04Z
date_updated: 2024-10-31T10:00:01Z
ddc:
- '000'
department:
- _id: '660'
file:
- access_level: closed
  content_type: application/pdf
  creator: doba2
  date_created: 2024-10-31T09:59:46Z
  date_updated: 2024-10-31T09:59:46Z
  file_id: '56846'
  file_name: paper8.pdf
  file_size: 261528
  relation: main_file
  success: 1
file_date_updated: 2024-10-31T09:59:46Z
has_accepted_license: '1'
keyword:
- Diagnostic reasoning
- Cognitive bias
- Cognitive model
- POMDP
- Bayesian network
- Epilepsy
- CDSS
language:
- iso: eng
project:
- _id: '128'
  name: 'TRR 318 - C5: TRR 318 - Subproject C5'
publication: Proceedings of the 8th Workshop on Formal and Cognitive Reasoning
quality_controlled: '1'
status: public
title: Formalizing cognitive biases in medical diagnostic reasoning
type: conference
user_id: '91864'
year: '2022'
...