Study Guides

Unit Summary

This unit introduces pupils to the emerging field of data science. They will explore what AI systems are and the different categories of AI. The concept of machine learning and how models are driven by data will be explored. They will also consider the ethical and wider implications of AI systems.

Lesson Summary

You will learn to analyse the social and ethical implications of AI technologies.

Key Notes

• The introduction of AI systems has brought benefits, but it also raises important social and ethical issues.
• Social implications of AI include job displacement, inequality of access, and privacy concerns over how data is used.
• AI can unintentionally amplify existing bias if it is trained on biased data.
• The transparency of AI systems is crucial so that users can understand how decisions are made.

Vocabulary To Learn

• bias: when something is unfair towards or against something or someone
• privacy: the right to keep personal data safe and control who can see or use it
• transparency: being clear about how AI works and explains its decisions

Common Mistakes To Avoid

• AI systems improve access to digital technologies.

3 Quick Questions (With Answers)

More Lessons In This Unit

• Approaches to training machine learning models Study Guide
• Classification Study Guide
• Data driven models Study Guide
• Introduction to AI Study Guide
• Machine learning Study Guide
• Machine learning engines Study Guide
• Predictive vs generative AI Study Guide