---
_id: '61339'
author:
- first_name: Marius
  full_name: Protte, Marius
  id: '44549'
  last_name: Protte
- first_name: Behnud Mir
  full_name: Djawadi, Behnud Mir
  last_name: Djawadi
citation:
  ama: 'Protte M, Djawadi BM. Human vs. Algorithmic Auditors: The Impact of Entity
    Type and Ambiguity on Human Dishonesty. <i>Frontiers in Behavioral Economics</i>.
    2025;4:1645749. doi:<a href="https://doi.org/10.3389/frbhe.2025.1645749">10.3389/frbhe.2025.1645749</a>'
  apa: 'Protte, M., &#38; Djawadi, B. M. (2025). Human vs. Algorithmic Auditors: The
    Impact of Entity Type and Ambiguity on Human Dishonesty. <i>Frontiers in Behavioral
    Economics</i>, <i>4</i>, 1645749. <a href="https://doi.org/10.3389/frbhe.2025.1645749">https://doi.org/10.3389/frbhe.2025.1645749</a>'
  bibtex: '@article{Protte_Djawadi_2025, title={Human vs. Algorithmic Auditors: The
    Impact of Entity Type and Ambiguity on Human Dishonesty}, volume={4}, DOI={<a
    href="https://doi.org/10.3389/frbhe.2025.1645749">10.3389/frbhe.2025.1645749</a>},
    journal={Frontiers in Behavioral Economics}, author={Protte, Marius and Djawadi,
    Behnud Mir}, year={2025}, pages={1645749} }'
  chicago: 'Protte, Marius, and Behnud Mir Djawadi. “Human vs. Algorithmic Auditors:
    The Impact of Entity Type and Ambiguity on Human Dishonesty.” <i>Frontiers in
    Behavioral Economics</i> 4 (2025): 1645749. <a href="https://doi.org/10.3389/frbhe.2025.1645749">https://doi.org/10.3389/frbhe.2025.1645749</a>.'
  ieee: 'M. Protte and B. M. Djawadi, “Human vs. Algorithmic Auditors: The Impact
    of Entity Type and Ambiguity on Human Dishonesty,” <i>Frontiers in Behavioral
    Economics</i>, vol. 4, p. 1645749, 2025, doi: <a href="https://doi.org/10.3389/frbhe.2025.1645749">10.3389/frbhe.2025.1645749</a>.'
  mla: 'Protte, Marius, and Behnud Mir Djawadi. “Human vs. Algorithmic Auditors: The
    Impact of Entity Type and Ambiguity on Human Dishonesty.” <i>Frontiers in Behavioral
    Economics</i>, vol. 4, 2025, p. 1645749, doi:<a href="https://doi.org/10.3389/frbhe.2025.1645749">10.3389/frbhe.2025.1645749</a>.'
  short: M. Protte, B.M. Djawadi, Frontiers in Behavioral Economics 4 (2025) 1645749.
date_created: 2025-09-18T07:52:40Z
date_updated: 2025-09-29T09:31:38Z
doi: 10.3389/frbhe.2025.1645749
intvolume: '         4'
keyword:
- cheating
- human-machine interaction
- ambiguity
- verification process
- algorithm aversion
- algorithm appreciation
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.frontiersin.org/journals/behavioral-economics/articles/10.3389/frbhe.2025.1645749/full
oa: '1'
page: '1645749'
publication: Frontiers in Behavioral Economics
status: public
title: 'Human vs. Algorithmic Auditors: The Impact of Entity Type and Ambiguity on
  Human Dishonesty'
type: journal_article
user_id: '44549'
volume: 4
year: '2025'
...
---
_id: '37312'
abstract:
- lang: eng
  text: Optimal decision making requires appropriate evaluation of advice. Recent
    literature reports that algorithm aversion reduces the effectiveness of predictive
    algorithms. However, it remains unclear how people recover from bad advice given
    by an otherwise good advisor. Previous work has focused on algorithm aversion
    at a single time point. We extend this work by examining successive decisions
    in a time series forecasting task using an online between-subjects experiment
    (N = 87). Our empirical results do not confirm algorithm aversion immediately
    after bad advice. The estimated effect suggests an increasing algorithm appreciation
    over time. Our work extends the current knowledge on algorithm aversion with insights
    into how weight on advice is adjusted over consecutive tasks. Since most forecasting
    tasks are not one-off decisions, this also has implications for practitioners.
author:
- first_name: Dirk
  full_name: Leffrang, Dirk
  id: '51271'
  last_name: Leffrang
  orcid: 0000-0001-9004-2391
- first_name: Kevin
  full_name: Bösch, Kevin
  last_name: Bösch
- first_name: Oliver
  full_name: Müller, Oliver
  id: '72849'
  last_name: Müller
citation:
  ama: 'Leffrang D, Bösch K, Müller O. Do People Recover from Algorithm Aversion?
    An Experimental Study of Algorithm Aversion over Time. In: <i>Hawaii International
    Conference on System Sciences</i>. ; 2023.'
  apa: Leffrang, D., Bösch, K., &#38; Müller, O. (2023). Do People Recover from Algorithm
    Aversion? An Experimental Study of Algorithm Aversion over Time. <i>Hawaii International
    Conference on System Sciences</i>. Hawaii International Conference on System Sciences.
  bibtex: '@inproceedings{Leffrang_Bösch_Müller_2023, title={Do People Recover from
    Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time}, booktitle={Hawaii
    International Conference on System Sciences}, author={Leffrang, Dirk and Bösch,
    Kevin and Müller, Oliver}, year={2023} }'
  chicago: Leffrang, Dirk, Kevin Bösch, and Oliver Müller. “Do People Recover from
    Algorithm Aversion? An Experimental Study of Algorithm Aversion over Time.” In
    <i>Hawaii International Conference on System Sciences</i>, 2023.
  ieee: D. Leffrang, K. Bösch, and O. Müller, “Do People Recover from Algorithm Aversion?
    An Experimental Study of Algorithm Aversion over Time,” presented at the Hawaii
    International Conference on System Sciences, 2023.
  mla: Leffrang, Dirk, et al. “Do People Recover from Algorithm Aversion? An Experimental
    Study of Algorithm Aversion over Time.” <i>Hawaii International Conference on
    System Sciences</i>, 2023.
  short: 'D. Leffrang, K. Bösch, O. Müller, in: Hawaii International Conference on
    System Sciences, 2023.'
conference:
  name: Hawaii International Conference on System Sciences
date_created: 2023-01-18T10:53:51Z
date_updated: 2024-01-10T09:52:59Z
department:
- _id: '196'
keyword:
- Algorithm aversion
- Time series
- Decision making
- Advice taking
- Forecasting
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://scholarspace.manoa.hawaii.edu/items/62b58ddc-895c-48c3-8194-522a1758a26f
oa: '1'
publication: Hawaii International Conference on System Sciences
status: public
title: Do People Recover from Algorithm Aversion? An Experimental Study of Algorithm
  Aversion over Time
type: conference
user_id: '51271'
year: '2023'
...
---
_id: '50118'
abstract:
- lang: eng
  text: Despite the widespread use of machine learning algorithms, their effectiveness
    is limited by a phenomenon known as algorithm aversion. Recent research concluded
    that unobserved variables can cause algorithm aversion. However, the impact of
    an unobserved variable on algorithm aversion remains unclear. Previous studies
    focused on situations where humans had more variables available than algorithms.
    We extend this research by conducting an online experiment with 94 participants,
    systematically varying the number of observable variables to the advisor and the
    advisor type. Surprisingly, our results did not confirm that an unobserved variable
    had a negative effect on advice-taking. Instead, we found a positive impact in
    an algorithm appreciation scenario. This study provides new insights into the
    paradoxical behavior in which people weigh advice more despite having fewer variables,
    as they correct for the advisor's errors. Practitioners should consider this behavior
    when designing algorithms and account for user correction behavior.
author:
- first_name: Dirk
  full_name: Leffrang, Dirk
  id: '51271'
  last_name: Leffrang
  orcid: 0000-0001-9004-2391
citation:
  ama: 'Leffrang D. The Broken Leg of Algorithm Appreciation: An Experimental Study
    on the Effect of Unobserved Variables on Advice Utilization. In: <i>Wirtschaftsinformatik
    Conference</i>. ; 2023.'
  apa: 'Leffrang, D. (2023). The Broken Leg of Algorithm Appreciation: An Experimental
    Study on the Effect of Unobserved Variables on Advice Utilization. <i>Wirtschaftsinformatik
    Conference</i>, <i>19</i>.'
  bibtex: '@inproceedings{Leffrang_2023, title={The Broken Leg of Algorithm Appreciation:
    An Experimental Study on the Effect of Unobserved Variables on Advice Utilization},
    number={19}, booktitle={Wirtschaftsinformatik Conference}, author={Leffrang, Dirk},
    year={2023} }'
  chicago: 'Leffrang, Dirk. “The Broken Leg of Algorithm Appreciation: An Experimental
    Study on the Effect of Unobserved Variables on Advice Utilization.” In <i>Wirtschaftsinformatik
    Conference</i>, 2023.'
  ieee: 'D. Leffrang, “The Broken Leg of Algorithm Appreciation: An Experimental Study
    on the Effect of Unobserved Variables on Advice Utilization,” in <i>Wirtschaftsinformatik
    Conference</i>, Paderborn, 2023, no. 19.'
  mla: 'Leffrang, Dirk. “The Broken Leg of Algorithm Appreciation: An Experimental
    Study on the Effect of Unobserved Variables on Advice Utilization.” <i>Wirtschaftsinformatik
    Conference</i>, no. 19, 2023.'
  short: 'D. Leffrang, in: Wirtschaftsinformatik Conference, 2023.'
conference:
  location: Paderborn
  name: Wirtschaftsinformatik
date_created: 2024-01-03T09:50:06Z
date_updated: 2024-01-10T09:53:24Z
department:
- _id: '196'
issue: '19'
keyword:
- Algorithm aversion
- Data
- Decision-making
- Advice-taking
- Human-Computer Interaction
language:
- iso: eng
main_file_link:
- url: 'https://aisel.aisnet.org/wi2023/19 '
publication: Wirtschaftsinformatik Conference
status: public
title: 'The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect
  of Unobserved Variables on Advice Utilization'
type: conference
user_id: '51271'
year: '2023'
...