What is machine learning bias?

What is machine learning bias?

Machine learning bias refers to systematic errors in algorithms that lead to unfair outcomes, often due to biased training data.

Can you give me an example of machine learning bias?

Sure! An example is facial recognition software that performs poorly on individuals with darker skin tones due to a lack of diverse training data.

How can we mitigate machine learning bias?

Mitigating bias can involve using diverse datasets, implementing fairness algorithms, and regularly auditing models for bias.

What are the consequences of ignoring machine learning bias?

Ignoring bias can lead to discrimination, loss of trust in AI systems, and potentially harmful decisions in critical areas like hiring or law enforcement.