32.11.1. Explainable AI (XAI) in Engineering

Try these first

1. 1.

   What does XAI stand for?

   Hint

   Think about AI and how we can explain it.

2. 2.

   Name one challenge of XAI.

   Hint

   What makes explaining AI models difficult?

3. 3.

   What does XAI aim to achieve?

   • Make AI models fully autonomous
   • Improve transparency of AI decisions
   • Increase AI complexity

   Hint

   Think about why users need transparency in AI.

4. 4.

   True or False: SHAP is a method used to enhance AI's accuracy.

   • True
   • False

   Hint

   Consider what SHAP does imply about explanations.

5. 5.

   Given a dataset on maximum load tolerances, use SHAP to interpret how different factors impact AI predictions.

   Hint

   Focus on interpreting why specific features are more critical than others.

6. 6.

   Critically analyze a case study where XAI improved trust in an engineering project. Identify key factors that led to this improvement.

   Hint

   Consider which attributes made the AI's performance understandable.