---
_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. Frontiers in Behavioral Economics.
2025;4:1645749. doi:10.3389/frbhe.2025.1645749'
apa: 'Protte, M., & Djawadi, B. M. (2025). Human vs. Algorithmic Auditors: The
Impact of Entity Type and Ambiguity on Human Dishonesty. Frontiers in Behavioral
Economics, 4, 1645749. https://doi.org/10.3389/frbhe.2025.1645749'
bibtex: '@article{Protte_Djawadi_2025, title={Human vs. Algorithmic Auditors: The
Impact of Entity Type and Ambiguity on Human Dishonesty}, volume={4}, DOI={10.3389/frbhe.2025.1645749},
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.” Frontiers in
Behavioral Economics 4 (2025): 1645749. https://doi.org/10.3389/frbhe.2025.1645749.'
ieee: 'M. Protte and B. M. Djawadi, “Human vs. Algorithmic Auditors: The Impact
of Entity Type and Ambiguity on Human Dishonesty,” Frontiers in Behavioral
Economics, vol. 4, p. 1645749, 2025, doi: 10.3389/frbhe.2025.1645749.'
mla: 'Protte, Marius, and Behnud Mir Djawadi. “Human vs. Algorithmic Auditors: The
Impact of Entity Type and Ambiguity on Human Dishonesty.” Frontiers in Behavioral
Economics, vol. 4, 2025, p. 1645749, doi:10.3389/frbhe.2025.1645749.'
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: '63909'
abstract:
- lang: eng
text: IntroductionHuman-machine interactions
become increasingly pervasive in daily life and professional contexts, motivating
research to examine how human behavior changes when individuals interact with
machines rather than other humans. While most of the existing literature focused
on human-machine interactions with algorithmic systems in advisory roles, research
on human behavior in monitoring or verification processes that are conducted by
automated systems remains largely absent. This is surprising given the growing
implementation of algorithmic systems in institutions, particularly in tax enforcement
and financial regulation, to help monitor and identify misreports, or in online
labor platforms widely implementing algorithmic control to ensure that workers
deliver high service quality. Our study examines how human dishonesty changes
when verification of statements that may be untrue is performed by machines vs.
humans, and how ambiguity in the verification process influences dishonest behavior.MethodWe
design an incentivized laboratory experiment using a modified die-roll paradigm
where participants privately observe a random draw and report the result, with
higher reported numbers yielding greater monetary rewards. A probabilistic verification
process introduces risk of identifying a lie and punishment, with treatments varying
by verification entity (human vs. machine) and degree of ambiguity in the verification
process (transparent vs. ambiguous).ResultsOur
results show that under transparent verification rules, cheating magnitude does
not significantly differ between human and machine auditors. However, under ambiguous
conditions, cheating magnitude is significantly higher when machines verify participants'
reports, reducing the prevalence of partial cheating while leading to behavioral
polarization manifested as either complete honesty or maximal overreporting. The
same applies when comparing reports to a machine entity under ambiguous and transparent
verification rules.DiscussionThese
findings emphasize the behavioral implications of algorithmic opacity in verification
contexts. While machines can serve as effective auditors under transparent conditions,
their black box nature combined with ambiguous verification processes may unintentionally
incentivize more severe dishonesty. These insights have practical implications
for designing automated oversight systems in tax audits, compliance, and workplace
monitoring.
article_number: '1645749'
author:
- first_name: Marius
full_name: Protte, Marius
id: '44549'
last_name: Protte
- first_name: Behnud
full_name: Mir Djawadi, Behnud
id: '26032'
last_name: Mir Djawadi
orcid: 0000-0002-6271-5912
citation:
ama: 'Protte M, Mir Djawadi B. Human vs. algorithmic auditors: the impact of entity
type and ambiguity on human dishonesty. Frontiers in Behavioral Economics.
2025;4. doi:10.3389/frbhe.2025.1645749'
apa: 'Protte, M., & Mir Djawadi, B. (2025). Human vs. algorithmic auditors:
the impact of entity type and ambiguity on human dishonesty. Frontiers in Behavioral
Economics, 4, Article 1645749. https://doi.org/10.3389/frbhe.2025.1645749'
bibtex: '@article{Protte_Mir Djawadi_2025, title={Human vs. algorithmic auditors:
the impact of entity type and ambiguity on human dishonesty}, volume={4}, DOI={10.3389/frbhe.2025.1645749},
number={1645749}, journal={Frontiers in Behavioral Economics}, publisher={Frontiers
Media SA}, author={Protte, Marius and Mir Djawadi, Behnud}, year={2025} }'
chicago: 'Protte, Marius, and Behnud Mir Djawadi. “Human vs. Algorithmic Auditors:
The Impact of Entity Type and Ambiguity on Human Dishonesty.” Frontiers in
Behavioral Economics 4 (2025). https://doi.org/10.3389/frbhe.2025.1645749.'
ieee: 'M. Protte and B. Mir Djawadi, “Human vs. algorithmic auditors: the impact
of entity type and ambiguity on human dishonesty,” Frontiers in Behavioral
Economics, vol. 4, Art. no. 1645749, 2025, doi: 10.3389/frbhe.2025.1645749.'
mla: 'Protte, Marius, and Behnud Mir Djawadi. “Human vs. Algorithmic Auditors: The
Impact of Entity Type and Ambiguity on Human Dishonesty.” Frontiers in Behavioral
Economics, vol. 4, 1645749, Frontiers Media SA, 2025, doi:10.3389/frbhe.2025.1645749.'
short: M. Protte, B. Mir Djawadi, Frontiers in Behavioral Economics 4 (2025).
date_created: 2026-02-06T13:50:44Z
date_updated: 2026-03-27T16:07:20Z
department:
- _id: '179'
doi: 10.3389/frbhe.2025.1645749
intvolume: ' 4'
language:
- iso: eng
publication: Frontiers in Behavioral Economics
publication_identifier:
issn:
- 2813-5296
publication_status: published
publisher: Frontiers Media SA
status: public
title: 'Human vs. algorithmic auditors: the impact of entity type and ambiguity on
human dishonesty'
type: journal_article
user_id: '26032'
volume: 4
year: '2025'
...
---
_id: '48387'
author:
- first_name: Anastasia
full_name: Lebedeva, Anastasia
last_name: Lebedeva
- first_name: Marius
full_name: Protte, Marius
id: '44549'
last_name: Protte
- first_name: Dirk
full_name: van Straaten, Dirk
last_name: van Straaten
- first_name: René
full_name: Fahr, René
id: '111'
last_name: Fahr
citation:
ama: 'Lebedeva A, Protte M, van Straaten D, Fahr R. Involvement of domain experts
in the AI training does not affect adherence – An AutoML study. In: Advances
in Information and Communication. Vol 919. Lecture Notes in Networks and Systems.
Springer, Cham; 2024:178–204. doi:https://doi.org/10.1007/978-3-031-53960-2_13'
apa: Lebedeva, A., Protte, M., van Straaten, D., & Fahr, R. (2024). Involvement
of domain experts in the AI training does not affect adherence – An AutoML study.
In Advances in Information and Communication (Vol. 919, pp. 178–204). Springer,
Cham. https://doi.org/10.1007/978-3-031-53960-2_13
bibtex: '@inbook{Lebedeva_Protte_van Straaten_Fahr_2024, series={Lecture Notes in
Networks and Systems}, title={Involvement of domain experts in the AI training
does not affect adherence – An AutoML study}, volume={919}, DOI={https://doi.org/10.1007/978-3-031-53960-2_13},
booktitle={Advances in Information and Communication}, publisher={Springer, Cham},
author={Lebedeva, Anastasia and Protte, Marius and van Straaten, Dirk and Fahr,
René}, year={2024}, pages={178–204}, collection={Lecture Notes in Networks and
Systems} }'
chicago: Lebedeva, Anastasia, Marius Protte, Dirk van Straaten, and René Fahr. “Involvement
of Domain Experts in the AI Training Does Not Affect Adherence – An AutoML Study.”
In Advances in Information and Communication, 919:178–204. Lecture Notes
in Networks and Systems. Springer, Cham, 2024. https://doi.org/10.1007/978-3-031-53960-2_13.
ieee: A. Lebedeva, M. Protte, D. van Straaten, and R. Fahr, “Involvement of domain
experts in the AI training does not affect adherence – An AutoML study,” in Advances
in Information and Communication, vol. 919, Springer, Cham, 2024, pp. 178–204.
mla: Lebedeva, Anastasia, et al. “Involvement of Domain Experts in the AI Training
Does Not Affect Adherence – An AutoML Study.” Advances in Information and Communication,
vol. 919, Springer, Cham, 2024, pp. 178–204, doi:https://doi.org/10.1007/978-3-031-53960-2_13.
short: 'A. Lebedeva, M. Protte, D. van Straaten, R. Fahr, in: Advances in Information
and Communication, Springer, Cham, 2024, pp. 178–204.'
conference:
end_date: 2024-04-05
location: Berlin
name: Future of Information and Communication Conference (FICC)
start_date: 2024-04-04
date_created: 2023-10-23T10:38:00Z
date_updated: 2024-12-09T11:46:02Z
ddc:
- '000'
- '600'
- '330'
department:
- _id: '179'
doi: https://doi.org/10.1007/978-3-031-53960-2_13
file:
- access_level: closed
content_type: application/pdf
creator: mprotte
date_created: 2023-10-23T10:35:22Z
date_updated: 2023-10-23T10:35:22Z
file_id: '48388'
file_name: Lebedeva_Protte_vanStraaten_Fahr_2023_updated.pdf
file_size: 767807
relation: main_file
success: 1
file_date_updated: 2023-10-23T10:35:22Z
has_accepted_license: '1'
intvolume: ' 919'
language:
- iso: eng
page: 178–204
publication: Advances in Information and Communication
publisher: Springer, Cham
series_title: Lecture Notes in Networks and Systems
status: public
title: Involvement of domain experts in the AI training does not affect adherence
– An AutoML study
type: book_chapter
user_id: '44549'
volume: 919
year: '2024'
...
---
_id: '21369'
abstract:
- lang: eng
text: "Successful design of human-in-the-loop control sys- tems requires appropriate
models for human decision makers. Whilst most paradigms adopted in the control
systems literature hide the (limited) decision capability of humans, in behavioral
economics individual decision making and optimization processes are well-known
to be affected by perceptual and behavioral biases. Our goal is to enrich control
engineering with some insights from behavioral economics research through exposing
such biases in control-relevant settings.\r\nThis paper addresses the following
two key questions:\r\n1) How do behavioral biases affect decision making?\r\n2)
What is the role played by feedback in human-in-the-loop control systems?\r\nOur
experimental framework shows how individuals behave when faced with the task of
piloting an UAV under risk and uncertainty, paralleling a real-world decision-making
scenario. Our findings support the notion of humans in Cyberphysical Systems underlying
behavioral biases regardless of – or even because of – receiving immediate outcome
feedback. We observe substantial shares of drone controllers to act inefficiently
through either flying excessively (overconfident) or overly conservatively (underconfident).
Furthermore, we observe human-controllers to self-servingly misinterpret random
sequences through being subject to a “hot hand fallacy”. We advise control engineers
to mind the human component in order not to compromise technological accomplishments
through human issues."
author:
- first_name: Marius
full_name: Protte, Marius
id: '44549'
last_name: Protte
- first_name: René
full_name: Fahr, René
id: '111'
last_name: Fahr
- first_name: Daniel E.
full_name: Quevedo, Daniel E.
last_name: Quevedo
citation:
ama: 'Protte M, Fahr R, Quevedo DE. Behavioral Economics for Human-in-the-loop Control
Systems Design: Overconfidence and the hot hand fallacy. IEEE Control Systems
Magazine. 2020;40(6):57-76. doi:10.1109/MCS.2020.3019723'
apa: 'Protte, M., Fahr, R., & Quevedo, D. E. (2020). Behavioral Economics for
Human-in-the-loop Control Systems Design: Overconfidence and the hot hand fallacy.
IEEE Control Systems Magazine, 40(6), 57–76. https://doi.org/10.1109/MCS.2020.3019723'
bibtex: '@article{Protte_Fahr_Quevedo_2020, title={Behavioral Economics for Human-in-the-loop
Control Systems Design: Overconfidence and the hot hand fallacy}, volume={40},
DOI={10.1109/MCS.2020.3019723},
number={6}, journal={IEEE Control Systems Magazine}, publisher={IEEE}, author={Protte,
Marius and Fahr, René and Quevedo, Daniel E.}, year={2020}, pages={57–76} }'
chicago: 'Protte, Marius, René Fahr, and Daniel E. Quevedo. “Behavioral Economics
for Human-in-the-Loop Control Systems Design: Overconfidence and the Hot Hand
Fallacy.” IEEE Control Systems Magazine 40, no. 6 (2020): 57–76. https://doi.org/10.1109/MCS.2020.3019723.'
ieee: 'M. Protte, R. Fahr, and D. E. Quevedo, “Behavioral Economics for Human-in-the-loop
Control Systems Design: Overconfidence and the hot hand fallacy,” IEEE Control
Systems Magazine, vol. 40, no. 6, pp. 57–76, 2020, doi: 10.1109/MCS.2020.3019723.'
mla: 'Protte, Marius, et al. “Behavioral Economics for Human-in-the-Loop Control
Systems Design: Overconfidence and the Hot Hand Fallacy.” IEEE Control Systems
Magazine, vol. 40, no. 6, IEEE, 2020, pp. 57–76, doi:10.1109/MCS.2020.3019723.'
short: M. Protte, R. Fahr, D.E. Quevedo, IEEE Control Systems Magazine 40 (2020)
57–76.
date_created: 2021-03-03T14:20:10Z
date_updated: 2023-10-23T10:38:19Z
ddc:
- '620'
- '330'
department:
- _id: '179'
doi: 10.1109/MCS.2020.3019723
file:
- access_level: closed
content_type: application/pdf
creator: mprotte
date_created: 2021-03-03T14:21:50Z
date_updated: 2021-03-03T14:21:50Z
file_id: '21370'
file_name: Protte_Fahr_Quevedo.pdf
file_size: 1501292
relation: main_file
success: 1
file_date_updated: 2021-03-03T14:21:50Z
has_accepted_license: '1'
intvolume: ' 40'
issue: '6'
language:
- iso: eng
page: 57 - 76
publication: IEEE Control Systems Magazine
publication_status: published
publisher: IEEE
status: public
title: 'Behavioral Economics for Human-in-the-loop Control Systems Design: Overconfidence
and the hot hand fallacy'
type: journal_article
user_id: '44549'
volume: 40
year: '2020'
...
---
_id: '21371'
author:
- first_name: Marius
full_name: Protte, Marius
id: '44549'
last_name: Protte
citation:
ama: Protte M. The Effect of Organizational Support on Whistleblowing Behavior
- An Experimental Analysis.; 2019.
apa: Protte, M. (2019). The effect of organizational support on whistleblowing
behavior - An experimental analysis.
bibtex: '@book{Protte_2019, title={The effect of organizational support on whistleblowing
behavior - An experimental analysis}, author={Protte, Marius}, year={2019} }'
chicago: Protte, Marius. The Effect of Organizational Support on Whistleblowing
Behavior - An Experimental Analysis, 2019.
ieee: M. Protte, The effect of organizational support on whistleblowing behavior
- An experimental analysis. 2019.
mla: Protte, Marius. The Effect of Organizational Support on Whistleblowing Behavior
- An Experimental Analysis. 2019.
short: M. Protte, The Effect of Organizational Support on Whistleblowing Behavior
- An Experimental Analysis, 2019.
date_created: 2021-03-03T14:33:56Z
date_updated: 2022-01-06T06:54:57Z
language:
- iso: eng
status: public
supervisor:
- first_name: Djawadi
full_name: Behnud Mir, Djawadi
last_name: Behnud Mir
- first_name: Fahr
full_name: René, Fahr
last_name: René
title: The effect of organizational support on whistleblowing behavior - An experimental
analysis
type: mastersthesis
user_id: '44549'
year: '2019'
...