Description: Systemic bias refers to the tendency of a system or process to produce outcomes that favor certain groups or perspectives, often unintentionally. In the context of artificial intelligence (AI) and other technological systems, this bias can be embedded in algorithms, the data used to train them, or in the design decisions of the systems. This means that while AI is presented as an objective tool, it can perpetuate and amplify existing inequalities if not managed properly. Key characteristics of systemic bias include its inherent nature in systems, its ability to influence critical decisions, and its potential to disproportionately affect marginalized groups. The relevance of this concept is increasingly evident in a world where technology is used in areas such as hiring, criminal justice, and healthcare, where automated decisions can have a significant impact on people’s lives. Therefore, addressing systemic bias is crucial to ensuring that technological applications are fair, equitable, and responsible.
