ai-fairness

Vocabulary Word

Definition

AI fairness means making artificial intelligence systems unbiased and fair in their outputs. It's the notion that AI should be carefully designed and managed to eliminate prejudices and maintain justice in the decisions they make.

Examples in Different Contexts

For machine learning models, 'AI fairness' means designing models that equitably represent all groups, avoiding discrimination based on race, gender, or other characteristics. A data scientist might explain, 'We implement fairness measures in our AI models to ensure they perform equally well for diverse populations.'

Practice Scenarios

Design

Scenario:

The user interface seems to be unresponsive for people with visual impairments. How can we make our design more inclusive?

Response:

Absolutely! To prioritize AI fairness, let's start by making our UI more accessible and user-friendly for everyone.

Public-Policy

Scenario:

There's been controversy over data-driven policies. Public concerns are mounting over potential inequality in policy enforcement.

Response:

Indeed. To address these issues, our top priority should be fostering AI fairness in policy-making procedures.