Algorithmic Discrimination

Algorithmic discrimination refers to the use of artificial intelligence (AI) systems that result in differential treatment or impacts on individuals or groups based on characteristics such as race, gender, age, socioeconomic status, or other protected attributes. This phenomenon occurs when AI algorithms inadvertently learn and replicate biases present in the data they are trained on or are designed in ways that disproportionately disadvantage certain populations. Algorithmic discrimination can manifest in various contexts, such as hiring decisions, loan approvals, facial recognition systems, and law enforcement tools, potentially reinforcing existing inequalities and perpetuating systemic bias. Addressing algorithmic discrimination requires careful consideration of fairness, transparency, and accountability in the design, development, and deployment of AI systems.