Algorithms can reflect and amplify societal biases, leading to unfair outcomes. This article examines the challenge of algorithmic bias and approaches to address it.

We'll explore how bias can enter AI systems through training data, design choices, and implementation, as well as techniques for detecting and mitigating these issues.

Creating fair and equitable AI systems requires ongoing vigilance and a multidisciplinary approach.