Algorithmic Bias
When a system produces systematically different outcomes for different groups, without justification.
Algorithmic bias emerges from skewed training data, proxy variables that stand in for protected attributes, and choices about what to optimise. It rarely requires anyone to intend it. Because it is systematic rather than random, it scales — which is exactly what makes it worse than an individual’s bias.
In practice: A postcode feature quietly encoding ethnicity and driving loan decisions.