What are the sources of AI bias?

What are the main sources of bias in AI systems?

The main sources of AI bias include biased training data, algorithmic design choices, and societal biases.

Can you explain how biased training data affects AI?

Biased training data can lead to AI models that reinforce stereotypes or make unfair predictions based on skewed information.

What can be done to mitigate AI bias?

To mitigate AI bias, we can use diverse datasets, implement fairness algorithms, and regularly audit AI systems.

Are there any real-world examples of AI bias?

Yes, examples include biased hiring algorithms and facial recognition systems that misidentify individuals from certain demographics.