Description: The stereotype threat refers to the risk that negative expectations and beliefs about a specific social group influence the performance of an individual belonging to that group, especially in contexts related to technology and machine learning. This phenomenon can manifest in situations where automated decisions, such as those used in hiring systems, academic evaluations, or facial recognition, perpetuate and reinforce negative stereotypes. When an individual is aware that their social group is associated with an unfavorable stereotype, they may experience anxiety and pressure, which in turn can affect their performance and outcomes. This cycle of negative feedback not only impacts the individual but also contributes to the perpetuation of social and economic inequalities. The stereotype threat is a critical topic in AI ethics, as it raises questions about fairness and equity in the design and implementation of technologies that affect diverse populations. Understanding this phenomenon is essential for developing AI systems that are inclusive and do not reproduce existing biases, thus promoting a more equitable environment for all users.
