Types of Bias in Computing

1. Historical Bias: Occurs when training data reflects past discrimination.

   • Example: Hiring algorithms trained on historical hiring data may favor certain demographics.

2. Representational Bias: Happens when certain groups are underrepresented in datasets.

   • Example: Facial recognition systems may perform poorly for minority groups if they are not well-represented in training data.

3. Algorithmic Bias: Arises from flaws in algorithm design.

   • Example: A search engine ranking algorithm may prioritize certain websites over others unfairly.