paper-with-me

Papers

Fairness Perceptions in Regression-based Predictive Models

2025-05-08 · Mukund Telukunta, Venkata Sriram Siddhardh Nadendla, Morgan Stuart, Casey Canfield

Regression-based predictive analytics used in modern kidney transplantation is known to inherit biases from training data. This leads to social discrimination and inefficient organ utilization, particularly in the context of a few social groups. Despite this concern, there is limited research on fairness in regression and its impact on organ utilization and placement. This paper introduces three novel divergence-based group fairness notions: (i) independence, (ii) separation, and (iii) sufficiency to assess the fairness of regression-based analytics tools. In addition, fairness preferences are investigated from crowd feedback, in order to identify a socially accepted group fairness criterion for evaluating these tools. A total of 85 participants were recruited from the Prolific crowdsourcing platform, and a Mixed-Logit discrete choice model was used to model fairness feedback and estimate social fairness preferences. The findings clearly depict a strong preference towards the separation and sufficiency fairness notions, and that the predictive analytics is deemed fair with respect to gender and race groups, but unfair in terms of age groups.

📄 PDF Abstract BibTeX arXiv:2505.04886

Code (0)

등록된 구현이 없습니다.

Tasks

Fairnessregression

Similar Papers 제목 키워드 기반

The FairCeptron: A Framework for Measuring Human Perceptions of Algorithmic Fairness

2021-02-08 · Georg Ahnert, Ivan Smirnov, Florian Lemmerich, Claudia Wagner 외

Measures of algorithmic fairness often do not account for human perceptions of fairness that can substantially vary between different sociodemographics and stakeholders. The FairCeptron framework is an approach for study…

Decision MakingFairness

Appropriate Fairness Perceptions? On the Effectiveness of Explanations in Enabling People to Assess the Fairness of Automated Decision Systems

2021-08-14 · Jakob Schoeffer, Niklas Kuehl

It is often argued that one goal of explaining automated decision systems (ADS) is to facilitate positive perceptions (e.g., fairness or trustworthiness) of users towards such systems. This viewpoint, however, makes the …

Fairness

Are Fairness Perceptions Shaped by Income Inequality? Evidence from Latin America

2022-02-09 · Leonardo Gasparini, Germán Reyes

A common assumption in the literature is that the level of income inequality shapes individuals' beliefs about whether the income distribution is fair (``fairness views,'' for short). However, individuals do not directly…

Fairness

Public Perceptions of Fairness Metrics Across Borders

2024-03-24 · Yuya Sasaki, Sohei Tokuno, Haruka Maeda, Kazuki Nakajima 외

Which fairness metrics are appropriately applicable in your contexts? There may be instances of discordance regarding the perception of fairness, even when the outcomes comply with established fairness metrics. Several q…

Decision MakingFairnessSurvey

How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness

2018-11-08 · Nripsuta Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic 외

What is the best way to define algorithmic fairness? While many definitions of fairness have been proposed in the computer science literature, there is no clear agreement over a particular definition. In this work, we in…

Fairness