What are some strategies to improve fairness in AI systems?
To improve fairness in AI, we can implement diverse training data, conduct bias audits, and involve diverse teams in development.
How can diverse training data help?
Diverse training data helps ensure that the AI learns from a wide range of perspectives, reducing bias and improving outcomes for all groups.
What role do bias audits play?
Bias audits identify and measure biases in AI models, allowing developers to address issues before deployment.
Can involving diverse teams really make a difference?
Yes, diverse teams bring different viewpoints and experiences, which can lead to more equitable AI solutions.
What are some tools for conducting bias audits?
Some popular tools include IBM's AI Fairness 360, Google's What-If Tool, and Microsoft's Fairlearn.
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