How does bias affect trust in AI systems?

How does bias affect trust in AI systems?

Bias in AI can lead to unfair outcomes, which erodes user trust. When people see biased results, they may doubt the system's reliability.

Can you give an example of bias in AI?

Sure! A common example is facial recognition technology, which has shown higher error rates for people of color, leading to mistrust.

What can be done to reduce bias in AI?

To reduce bias, developers can use diverse training data, implement fairness algorithms, and regularly audit AI systems for bias.

Is there a way to measure trust in AI?

Yes, trust in AI can be measured through user surveys, performance metrics, and analyzing user interactions with the system.