What are common biases found in AI training data?

What are common biases found in AI training data?

Common biases in AI training data include gender bias, racial bias, and confirmation bias, which can affect outcomes.

Can you give examples of how these biases manifest in AI systems?

Sure! For instance, facial recognition systems may misidentify individuals from certain racial groups due to biased training data.

How can we mitigate these biases in AI?

Mitigating biases can involve diversifying training datasets, implementing fairness algorithms, and continuous monitoring.

Are there any regulations regarding bias in AI?

Yes, various countries are developing regulations to ensure fairness and accountability in AI systems.