How do you balance explainability and model performance?
Answer / Nitesh Kumar Chaudhury
Balancing explainability and model performance can be challenging. One approach is to use simpler models that are easier to interpret, although these may not perform as well. Another approach is to add explainability layers to complex models without significantly impacting their performance. Techniques like LIME and SHAP can help in this regard.
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How can fairness in AI improve its societal acceptance?
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