Algorithmic Fairness A Tolerance Perspective

Algorithmic Fairness A Tolerance Perspective By abstracting and synthesizing the concept of tolerance within algorithmic fairness, this review presents researchers with a fresh yet important perspective to mitigate prevalent fairness issues. We introduce a novel taxonomy based on 'tolerance', a term we define as the degree to which variations in fairness outcomes are acceptable, providing a structured approach to understanding the.

Algorithmic Fairness A Tolerance Perspective This article explores algorithmic fairness through the lens of tolerance, focusing on legal, ethical, and personal tolerance levels. the authors provide a comprehensive overview of diverse instances of algorithmic fairness and highlight the distinct degrees of tolerance involved. We introduce a novel taxonomy based on 'tolerance', a term we define as the degree to which variations in fairness outcomes are acceptable, providing a structured approach to understanding the subtleties of fairness within algorithmic decisions. The balance between algorithmic decision making and social equity. by synthesizing these insights, we outline a series of emerging challenges and propose strategic directions for future research and policy making, with the goal of advancing the field towards more equitable algorithmic systems. We introduce a novel taxonomy based on 'tolerance', a term we define as the degree to which variations in fairness outcomes are acceptable, providing a structured approach to understanding the subtleties of fairness within algorithmic decisions.

Pdf Algorithmic Fairness A Tolerance Perspective The balance between algorithmic decision making and social equity. by synthesizing these insights, we outline a series of emerging challenges and propose strategic directions for future research and policy making, with the goal of advancing the field towards more equitable algorithmic systems. We introduce a novel taxonomy based on 'tolerance', a term we define as the degree to which variations in fairness outcomes are acceptable, providing a structured approach to understanding the subtleties of fairness within algorithmic decisions. We introduce a novel taxonomy based on 'tolerance', a term we define as the degree to which variations in fairness outcomes are acceptable, providing a structured approach to understanding the subtleties of fairness within algorithmic decisions. The paper proposes a new perspective on algorithmic fairness, drawing on the legal concept of "tolerance." the authors argue that the degree of tolerance for unfairness in algorithmic decision making can have significant implications for how these systems are deployed and their real world impact. The computer science approach, as outlined by barocas et al. (2023), focuses on imposing fairness constraints directly on algorithmic systems. this typically involves mathematical definitions of fairness such as demographic parity, equal opportunity, or equal odds that algorithms must satisfy. This paper surveys algorithmic fairness, introducing a novel 'tolerance' taxonomy to assess acceptable variations in fairness outcomes. it explores the social implications of discriminatory decisions in diverse industries and proposes strategic directions to enhance social equity in machine learning systems.