AI Fairness

Explanation

Imagine a judge who always favours a certain group of people. That's unfair, right?

AI Fairness aims to prevent AI systems from making decisions that discriminate against individuals or groups based on characteristics like race, gender, or age.

It's about ensuring that AI systems are unbiased and equitable in their outcomes.

This involves carefully examining the data used to train AI models, the algorithms themselves, and the way these systems are deployed.

The goal is to create AI that treats everyone fairly, regardless of their background.

It’s not just about avoiding legal trouble; it’s about building trustworthy AI that benefits everyone.

Examples

Consumer Example

Think about applying for a loan online.

An AI-powered system assesses your creditworthiness. AI fairness would ensure the algorithm doesn't unfairly deny your application because of your postcode or ethnic background.

It's about getting a fair shot, regardless of your personal characteristics.

Business Example

Imagine a company using AI to screen job applicants.

AI fairness would mean ensuring the AI doesn't automatically reject candidates with certain names or educational backgrounds, preventing unconscious bias.

It's about finding the best talent, not just the most familiar profile.

This leads to a more diverse workforce and a better understanding of the market.