What is training data bias in AI?

What is training data bias in AI?

Training data bias refers to the systematic favoritism in the data used to train AI models, leading to skewed results.

Can you give me an example of training data bias?

Sure! An example is facial recognition software that performs better on lighter-skinned individuals due to a lack of diverse training data.

How does this bias affect AI decision-making?

This bias can lead to unfair outcomes, such as discrimination in hiring processes or law enforcement, impacting marginalized groups.

What can be done to reduce training data bias?

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