What is data bias in machine learning?

What is data bias in machine learning?

Data bias in machine learning refers to systematic errors in data that can lead to unfair or inaccurate predictions.

How does data bias affect AI models?

Data bias can cause AI models to make decisions that are skewed or unfair, often reflecting societal biases present in the training data.

Can you give an example of data bias?

Sure! An example is facial recognition software that performs poorly on individuals with darker skin tones due to underrepresentation in the training data.

What can be done to reduce data bias?

To reduce data bias, you can ensure diverse data representation, use bias detection tools, and regularly audit AI models for fairness.