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：算法歧视是一种由数据驱动软件基于民族、种族、性别、性取向、宗教、年龄、残疾或其他个人特征不公平对待用户而产生的状况。当前，随着机器学习的日益普及，算法歧视案例在多个领域不断被报道。本研究深入分析了历年发表的相关研究成果，旨在通过探讨该问题的关键特征，支持软件工程研究人员与从业者应对这一挑战。