What does “Bias” mean?

Systematic unfairness in model outputs caused by skewed data, assumptions, or modeling choices.

Very large and complex datasets that require scalable storage and processing techniques.

When benchmark test examples or close variants are present in training data, inflating reported performance.

A field focused on reducing harmful behavior, failures, and misuse risks in AI systems.

How clearly an AI system's logic, data sources, and limitations are documented and understandable.

The broad field of building systems that perform tasks requiring pattern recognition, reasoning, language, or decision-making.