What is training data bias in AI?

What is training data bias in AI?

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

How does training data bias affect AI decision-making?

It can lead to unfair or inaccurate outcomes, as the AI may learn and replicate the biases present in the training data.

Can you give an example of training data bias?

Sure! An example is facial recognition systems that perform poorly on individuals from certain ethnic backgrounds due to underrepresentation in the training data.

What can be done to mitigate training data bias?

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