Antony West (Author)

Algorithms are increasingly making decisions that impact our lives, from loan applications and job hiring to criminal justice sentencing. While touted for their efficiency and objectivity, these systems are only as unbiased as the data they are trained on, and the human biases embedded within it. Algorithmic bias occurs when these systems inadvertently perpetuate or even amplify existing societal prejudices, leading to discriminatory outcomes. If historical data reflects systemic inequalities, an algorithm trained on that data will learn and replicate those biases, potentially denying opportunities or imposing harsher judgements on certain demographic groups. Addressing algorithmic bias requires careful data curation, transparent design, and continuous auditing to ensure these powerful tools promote fairness, not perpetuate discrimination. Where do you think algorithmic bias poses the greatest threat in society?