Computing Bias

This study guide covers bias in computing, including its definition, how it manifests in technology, and real-world examples like criminal risk assessment tools, facial recognition, and recruiting algorithms. It also details strategies to prevent bias such as using diverse datasets, algorithm review, fairness metrics, and increasing tech diversity. Finally, it provides practice questions and exam tips focusing on identifying, analyzing, and mitigating bias.