Algorithmic Bias and Fairness

This review article examines the issues of algorithmic bias and fairness, beginning with a foundational discussion of the concept of algorithms. In recent years, Artificial Intelligence (AI) and Machine Learning (ML) have profoundly transformed technology and consequently, modern society. Critical domains such as education, business, engineering, healthcare, and social systems increasingly rely on AI- and ML-driven decision-making processes, which are in turn governed by complex algorithms. As these algorithmic decisions have far-reaching social, economic, and ethical implications, ensuring their fairness has become a crucial concern. This article aims to explore contemporary perspectives on algorithmic bias, its sources, impacts and the importance of developing fair and accountable algorithmic systems.