Author(s): Aradhya Srivastava

Abstract: Artificial Intelligence (AI) holds transformative potential across various sectors, yet its integration has revealed critical issues of bias and discrimination. This article explores the multifaceted nature of bias in AI systems, including historical, algorithmic, and selection biases. It examines the profound implications of AI bias on economic disparities, social inequality, and public trust. The article emphasizes the need for a comprehensive approach to addressing bias, including diverse data collection, bias detection and correction, algorithmic transparency, ethical AI design, and regulatory measures. It also highlights successful initiatives and organizations working towards fair AI practices. By underscoring the urgency of tackling AI bias, the article advocates for collaborative efforts to ensure AI technologies promote fairness and inclusivity.