Direct Discrimination

Direct discrimination, the unequal treatment of individuals based on protected characteristics, is a significant concern across various domains, from hiring practices to algorithmic decision-making. Current research focuses on developing methods to detect and mitigate this bias, employing techniques like causal inference to identify direct causal links between protected attributes and outcomes, and leveraging natural language processing to analyze textual data for discriminatory language in contexts like job postings. These advancements aim to improve fairness in both human and automated decision-making processes, with implications for legal frameworks, algorithmic accountability, and social equity.