The ever-growing use of artificial intelligence systems and the pervasive presence of automation raise several ethical and legal concerns, with fairness at the centre. This monograph explores what fairness is, how it is guaranteed, and how it can be operationalised in algorithmic systems affecting humans. As algorithmic decisions increasingly support or replace human judgment, worries about discrimination in-tensify. Using a multidisciplinary methodology, the work reviews legal, philosophi-cal, and ethical debates and proposes an approach to fairness as a multi-dimensional, multi-layered concept. It analyses EU anti-discrimination law, evalu-ates technical solutions including fairness metrics and synthetic data, and offers in-terpretative guidance on the EU AI Act. Finally, it introduces the Fair-y-TALe meth-odology to assess and mitigate discriminatory harms across the AI lifecycle