We study bias and discrimination in the context of Bumble, an online dating platform in India. Drawing on research in AI fairness and inclusion studies we analyze algorithmic bias and their propensity to reproduce bias. We conducted an experiment to identify and address the presence of bias in the matching algorithms Bumble pushes to its users in the form of profiles for potential dates in the real world. Dating apps like Bumble utilize algorithms that learn from user data to make recommendations. Even if the algorithm does not have intentions or consciousness, it is a system created and maintained by humans. We attribute moral agency of such systems to be compositely derived from algorithmic mediations, the design and utilization of these platforms. Developers, designers, and operators of dating platforms thus have a moral obligation to mitigate biases in the algorithms to create inclusive platforms that affirm diverse social identities.

翻译：我们研究了印度在线约会平台Bumble中的偏见与歧视现象。借鉴人工智能公平性与包容性研究的相关成果，我们分析了算法偏见及其再现偏见的倾向。通过实验，我们识别并探讨了Bumble在向用户推送现实世界潜在约会对象档案时，其匹配算法中存在的偏见问题。诸如Bumble之类的约会应用利用从用户数据中学习的算法进行推荐。即使算法本身不具备意图或意识，它仍是由人类创建和维护的系统。我们认为，此类系统的道德主体性源自算法中介、平台设计与使用的复合作用。因此，约会平台的开发者、设计者及运营者负有道德责任，需减轻算法中的偏见，从而创建能够肯定多元社会身份的包容性平台。