What are the main challenges of explainable AI?

What are the main challenges of explainable AI?

The main challenges include complexity of models, lack of standardization, and the trade-off between accuracy and interpretability.

Can you explain why model complexity is a challenge?

Model complexity makes it difficult to understand how decisions are made, leading to a lack of trust in AI systems.

What does lack of standardization mean in this context?

Lack of standardization means there are no universally accepted methods for explaining AI decisions, making comparisons difficult.

How does the trade-off between accuracy and interpretability work?

Often, more accurate models are complex and harder to interpret, while simpler models may sacrifice some accuracy for clarity.

What are some potential solutions to these challenges?

Potential solutions include developing better visualization tools, creating standardized metrics for explainability, and using simpler models when possible.