This knowledge check reviews the main ideas from the chapters on **bias**, **fairness**, and **transparency** in AI. You will answer questions about different types of bias, strategies to promote fairness, and the importance of transparency in AI systems.

Which of the following are examples of **algorithmic bias**?  
Select all that apply.

Which strategy is most commonly used to **mitigate bias and improve fairness** in AI decision-making?

What are some benefits of **transparency** in AI systems? Select all that apply.

An accessible introduction to the foundational ethical principles, challenges, and responsibilities in the development and deployment of Artificial Intelligence. This course is designed for beginners in AI and Data Science, focusing on theory and real-world implications.

Explore the core ethical principles, the importance of ethics in AI, and the main challenges faced in the field.

Delve into the concepts of fairness and bias in AI, and the importance of transparency for ethical AI systems.

Examine the responsibilities of AI creators, the importance of privacy, and the role of regulation in responsible AI.

Quiz: Fairness, Bias, and Transparency

1. Which of the following are examples of algorithmic bias?

2. Which strategy is most commonly used to mitigate bias and improve fairness in AI decision-making?

3. What are some benefits of transparency in AI systems? Select all that apply.