mlsanityData to 7 Oct 2026

Perceptions of Fairness and Trustworthiness Based on Explanations in Human vs. Automated Decision-Making

arXiv 2109.05792 ↗First posted 13 Sep 2021cs.HC cs.AIcited by 3

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Abstract (arXiv)

Automated decision systems (ADS) have become ubiquitous in many high-stakes domains. Those systems typically involve sophisticated yet opaque artificial intelligence (AI) techniques that seldom allow for full comprehension of their inner workings, particularly for affected individuals. As a result, ADS are prone to deficient oversight and calibration, which can lead to undesirable (e.g., unfair) outcomes. In this work, we conduct an online study with 200 participants to examine people's perceptions of fairness and trustworthiness towards ADS in comparison to a scenario where a human instead of an ADS makes a high-stakes decision -- and we provide thorough identical explanations regarding decisions in both cases. Surprisingly, we find that people perceive ADS as fairer than human decision-makers. Our analyses also suggest that people's AI literacy affects their perceptions, indicating that people with higher AI literacy favor ADS more strongly over human decision-makers, whereas low-AI-literacy people exhibit no significant differences in their perceptions.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 7 of its 57 references that are in the map. First posted on arXiv 13 Sep 2021.

Builds on

7 of 57 references.

References · 7

  1. 2018'It's Reducing a Human Being to a Percentage'; Perceptions of Justice in Algorithmic Decisionscited by 91
  2. 2019Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learningcited by 57
  3. 2020Factors Influencing Perceived Fairness in Algorithmic Decision-Making: Algorithm Outcomes, Development Procedures, and Individual Differencescited by 41
  4. 2021Auditing for Discrimination in Algorithms Delivering Job Adscited by 16
  5. 2021Appropriate Fairness Perceptions? On the Effectiveness of Explanations in Enabling People to Assess the Fairness of Automated Decision Systemscited by 9
  6. 2021A Study on Fairness and Trust Perceptions in Automated Decision Makingcited by 7
  7. 2016The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Goodcited by 4

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Cited by year

Citing papers per year: 2022: 3.

3 papers.

  1. 2022Should I Follow AI-based Advice? Measuring Appropriate Reliance in Human-AI Decision-Makingcited by 28
  2. 2022"There Is Not Enough Information": On the Effects of Explanations on Perceptions of Informational Fairness and Trustworthiness in Automated Decision-Makingcited by 19
  3. 2022A Human-Centric Perspective on Fairness and Transparency in Algorithmic Decision-Makingcited by 1