Algorithmic discrimination is a condition that arises when data-driven software unfairly treats users based on attributes like ethnicity, race, gender, sexual orientation, religion, age, disability, or other personal characteristics. Nowadays, as machine learning gains popularity, cases of algorithmic discrimination are increasingly being reported in several contexts. This study delves into various studies published over the years reporting algorithmic discrimination. We aim to support software engineering researchers and practitioners in addressing this issue by discussing key characteristics of the problem

翻译：算法歧视是一种现象，指数据驱动的软件基于种族、民族、性别、性取向、宗教、年龄、残疾或其他个人特征，不公平地对待用户。如今，随着机器学习的普及，算法歧视案例在多个领域日益被报道。本研究深入分析了多年来发表的各类相关文献，旨在通过探讨该问题的关键特征，支持软件工程研究人员和实践者应对这一挑战。