Algorithmic Discrimination

As artificial intelligence becomes woven into the fabric of decision-making, it quietly inherits the very inequalities it was meant to neutralize. Algorithmic discrimination—rooted in biased data, opaque models, and uncritical deployment—represents a new, insidious form of inequality. This chapter examines how AI systems reproduce and sometimes intensify historical injustices, often in ways that are hidden behind the technical sheen of objectivity. By exploring the sociotechnical roots of bias, the chapter highlights the moral imperative to rethink how algorithms are trained, evaluated, and governed. Rather than treating AI as a neutral tool, it calls for a paradigm shift—one that centers ethics, equity, and the lived experiences of marginalized communities. Only by acknowledging the silent exclusions encoded in code can we hope to build AI systems that reflect, rather than distort, our collective ideals of justice.