What are the sources of AI biases?

What are the main sources of biases in AI?

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

Can you explain how biased training data affects AI?

Biased training data can lead to AI systems making unfair or inaccurate predictions, reflecting existing prejudices.

What role does algorithmic design play in AI bias?

Algorithmic design can introduce biases if the algorithms prioritize certain features or outcomes over others.

How can we mitigate these biases in AI?

Mitigating biases involves using diverse datasets, regular audits, and inclusive design practices in AI development.