What is AI bias in training datasets?

What is AI bias in training datasets?

AI bias in training datasets refers to the presence of prejudiced or unbalanced data that can lead to unfair outcomes in AI models.

How does this bias affect AI decision-making?

Bias in training datasets can cause AI systems to make decisions that reflect societal inequalities, leading to discrimination.

Can you give an example of AI bias in real life?

Sure! One example is facial recognition technology, which has been shown to misidentify individuals from certain demographic groups more frequently.

What can be done to reduce AI bias?

To reduce AI bias, we can use diverse datasets, implement bias detection tools, and continuously monitor AI systems for fairness.