What is AI bias and how does it occur?
AI bias refers to systematic errors in AI systems that lead to unfair outcomes. It occurs due to biased training data, flawed algorithms, or human prejudices.
Can you give examples of AI bias in real life?
Sure! Examples include biased hiring algorithms that favor certain demographics or facial recognition systems that misidentify people of color.
What are the consequences of AI bias on society?
Consequences include perpetuating inequality, reinforcing stereotypes, and eroding trust in technology, which can impact various sectors like justice and healthcare.
How can we mitigate AI bias?
Mitigating AI bias involves using diverse training data, implementing fairness checks, and involving diverse teams in AI development.
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