Description: Bias in content moderation refers to the influence that both conscious and unconscious prejudices can have on the processes used to filter and manage content on digital platforms. This phenomenon is particularly relevant in the context of artificial intelligence (AI), where algorithms are trained on data that may contain inherent biases. As a result, automated decisions about what content is acceptable or not can reflect and perpetuate those biases, affecting fairness and diversity in the information presented to users. Content moderation is crucial for maintaining a safe and respectful online environment, but if it is affected by bias, it can lead to the censorship of minority voices or the promotion of dominant narratives. This issue raises important ethical questions about the responsibility of platforms in managing their content and the need to develop fairer and more transparent AI systems. Identifying and mitigating bias in content moderation is an ongoing challenge that requires a multidisciplinary approach, involving not only engineers and developers but also experts in ethics, sociology, and human rights.
