What are some common issues with AI models?

What are some common issues with AI models?

Common issues with AI models include bias, overfitting, lack of transparency, and data quality problems.

Can you explain how bias affects AI models?

Bias in AI models can lead to unfair outcomes, as the model may favor certain groups over others based on skewed training data.

What is overfitting and why is it a problem?

Overfitting occurs when a model learns the training data too well, capturing noise instead of the underlying pattern, which harms its performance on new data.

How can we improve data quality for AI training?

Improving data quality can be achieved by ensuring diverse and representative datasets, cleaning data, and validating sources.

Are there tools to help identify these issues?

Yes, there are various tools like Fairness Indicators, LIME, and SHAP that help identify bias and interpret model predictions.