Description: Query bias refers to the distortion that occurs when the way a query is formulated influences the results returned by an artificial intelligence (AI) system. This phenomenon is particularly relevant in the context of search engines, recommendation systems, and other AI applications, where the way a question is posed or a term is entered can significantly determine the information obtained. Query bias can arise in various ways, such as the use of loaded terms, the omission of relevant keywords, or the choice of a specific context that limits responses. This bias not only affects the quality of the retrieved information but can also perpetuate stereotypes and inequalities, as the results may reflect and reinforce existing prejudices in the system’s training data. Therefore, it is crucial to be aware of how queries are formulated to mitigate the impact of this bias and ensure that results are as fair and representative as possible.
