Abstract
Over the past years, there has been an increasing concern regarding the risk of bias and discrimination in algorithmic systems, which received significant attention amongst the research communities. To ensure the system's fairness, various methods and techniques have been developed to assess and mitigate potential biases. Such methods, also known as "Formal Fairness", look at various aspects of the system's advanced reasoning mechanism and outcomes, with techniques ranging from local explanations (at feature level) to visual explanations (saliency maps). Another aspect, equally important, represents the perception of the users regarding the system's fairness. Despite a decision system being provably "Fair", if the users find it difficult to understand how the decisions were made, they will refrain from trusting, accepting, and ultimately using the system altogether. This raised the issue of "Perceived Fairness"which looks at means to reassure users of a system's trustworthiness. In that sense, providing users with some form of explanation on why and how certain outcomes resulted, is highly relevant, especially nowadays as the reasoning mechanisms increase in complexity and computational power. Recent studies suggest a plethora of explanation types. The current work aims to review the recent progress in explaining systems' reasoning and outcome, categorize and present it as a reference for the state-of-the-art fairness-related explanations review.
Original language | English |
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Title of host publication | UMAP 2021 - Adjunct Publication of the 29th ACM Conference on User Modeling, Adaptation and Personalization |
Publisher | Association for Computing Machinery, Inc |
Pages | 421-431 |
Number of pages | 11 |
ISBN (Electronic) | 9781450383677 |
DOIs | |
State | Published - 21 Jun 2021 |
Event | 29th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2021 - Virtual, Online, Netherlands Duration: 21 Jun 2021 → 25 Jun 2021 |
Publication series
Name | UMAP 2021 - Adjunct Publication of the 29th ACM Conference on User Modeling, Adaptation and Personalization |
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Conference
Conference | 29th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2021 |
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Country/Territory | Netherlands |
City | Virtual, Online |
Period | 21/06/21 → 25/06/21 |
Bibliographical note
Publisher Copyright:© 2021 ACM.
Keywords
- Explainability
- Perceived fairness
- algorithmic transparency
ASJC Scopus subject areas
- Software