Navigating Bias in Algorithmic Decision-Making

This chapter examines the intricate biases present in automated loan-making and other algorithmic systems, stressing the importance of addressing historical inequities. It advocates for integrating social sciences and ethics into engineering education to foster responsible technology development. The discussion further explores the need for accountability and collaboration between algorithms and human users to ensure fairness and positive societal outcomes.