Riskification
Riskification refers to the process by which individuals or groups are unfairly or inaccurately categorized as higher-risk based on biased, incomplete, or overly broad data. This concept is particularly relevant in fields such as lending, insurance, hiring, and law enforcement, where automated systems or human judgment may rely on flawed assumptions or discriminatory criteria. The term highlights how systemic biases—whether intentional or unintentional—can distort risk assessments, leading to unequal treatment.
The phenomenon often arises when algorithms or decision-making frameworks are trained on historical data that reflects
Riskification can also stem from oversimplified risk models that ignore contextual factors, such as socioeconomic status
Addressing riskification requires transparency in data sources, regular audits of decision-making systems, and the inclusion of