---
_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'
...