20.14.2. Ethical Use of AI in Hazard Prediction

Try these first

1. 1.

   What is bias in AI?

   Hint

   Think about data representation.

2. 2.

   Why is transparency important?

   Hint

   Focus on understanding and acceptance.

3. 3.

   What is important to avoid in AI datasets?

   • Homogeneity
   • Diversity
   • Consistency

   Hint

   Think about how data represents different groups.

4. 4.

   True or False: Transparency in AI systems is optional.

   • True
   • False

   Hint

   Remember the role of users trusting the system.

5. 5.

   Analyze a situation where a biased AI system led to adverse consequences in hazard prediction. What measures could have been taken to prevent this?

   Hint

   Focus on past examples and key measures like data diversity.

6. 6.

   Propose a framework for implementing accountability in AI hazard prediction systems. What challenges might arise?

   Hint

   Consider the complexity of current systems.