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Related Questions
- What are some common types of bias that can occur in recommendation systems and how can explainable AI techniques help identify them?
- How do techniques like feature attribution and model interpretability help to explain the decision-making process of recommendation systems?
- Can you provide examples of how explainable AI techniques have been used to improve fairness in real-world recommendation systems?
- What is the role of transparency and accountability in ensuring fairness in recommendation systems, and how can explainable AI techniques contribute to these goals?
- How do explainable AI techniques help to address issues of bias in recommendation systems, such as confirmation bias and availability heuristic?
- Can you discuss the trade-offs between accuracy and fairness in recommendation systems, and how explainable AI techniques can help balance these competing objectives?
- What are some best practices for implementing explainable AI techniques in recommendation systems to improve fairness and transparency?
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