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.

Can you give me an example of data bias?

Sure! An example is when a facial recognition system is trained mostly on images of light-skinned individuals, leading to poor performance on darker-skinned individuals.

How can we mitigate data bias?

Mitigating data bias can involve diversifying training data, using bias detection tools, and regularly auditing models for fairness.

What are the consequences of ignoring data bias?

Ignoring data bias can result in discriminatory outcomes, loss of trust in AI systems, and potential legal repercussions.