Artificial intelligence is reshaping society, but its rapid growth brings increasing concerns about algorithmic bias and fairness. This study investigates the root causes of bias in AI systems and examines approaches for developing more equitable machine learning models. By addressing these challenges, the goal is to build AI that supports inclusion, avoids discrimination, and contributes to a more just and responsible technological future.

Facial recognition technology (FRT) is actively reshaping sectors from law enforcement to retail, offering enhanced security while triggering profound privacy concerns. This analysis examines FRT's expanding global impact, addressing its benefits in identification alongside risks of bias and misuse. Achieving this delicate balance requires robust frameworks that protect civil liberties without stifling technological innovation.