Intermediate · Safety

Fairness

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. The principle that AI systems should treat individuals and groups equitably.

Technical Definition

The principle that AI systems should treat individuals and groups equitably.

How it works

Different mathematical definitions of fairness — demographic parity, equal opportunity, calibration — can be mutually incompatible. Choosing among them is a value judgment, not a purely technical decision. Fairness is contextual: what's right in lending may differ from healthcare or content ranking.

Related Concepts

• Explainability (XAI) — Techniques making AI decisions understandable to humans, crucial for trust and regulatory compliance.
• AI Safety & Alignment — The field ensuring AI systems behave as intended, remain under human control, and avoid unintended harm.
• Bias (ethical) — Systematic, unfair model behavior that disadvantages particular groups of people.