close
Co-funded by the European Union. Views and opinions expressed are however those of the author or authors only and do not necessarily reflect those of the European Union or the Foundation for the Development of the Education System. Neither the European Union nor the entity providing the grant can be held responsible for them.

Module 1 – Fairness and Bias in AI

1. What does 'bias' mean in the context of AI?(Required)
2. Which of the following is an example of training data bias?(Required)
3. According to the five simple rules in Module 1, what should you do before using AI on important information?(Required)
4. What is 'selection bias' in AI?(Required)
5. Rule 4 of the five rules says that humans should always supervise AI. Why is this especially important?(Required)
6. What is 'post-deployment bias' or feedback loop bias?(Required)
7. According to the Amazon AI hiring case study, what mistake did the AI system make?(Required)
8. How can you reduce bias when writing prompts for an AI image or text generator?(Required)
menu