How can AI bias affect performance evaluations?
AI bias can lead to unfair assessments, impacting employee promotions and job security.
What are some common sources of bias in AI systems?
Common sources include biased training data, algorithmic design choices, and lack of diversity in development teams.
How can organizations mitigate AI bias?
Organizations can mitigate bias by using diverse datasets, regularly auditing algorithms, and involving diverse teams in development.
Are there any legal implications of AI bias in evaluations?
Yes, organizations may face legal challenges if biased evaluations lead to discrimination against protected groups.
What tools can help identify bias in AI systems?
Tools like Fairness Indicators, AI Fairness 360, and What-If Tool can help identify and mitigate bias in AI systems.
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