Support for understanding Artificial Intelligence concepts, applications, and ethical issues in preparation for your end-of-year assessment.
Core AI concepts: machine learning, neural networks, generative AI
How AI systems learn from data – and where bias can occur
Real-world applications in healthcare, transport, and communication
Key issues such as algorithmic bias, data privacy, and environmental impact
Ethical debates about AI decision-making, surveillance, and trust
Strategies for answering extended response questions
Work through each week’s focus area and class activities
Complete the micro-tasks, team debates, and short response questions
Use sentence starters and planning templates to structure your writing
Check your understanding with self-review prompts and practice questions
Come back during revision week to polish your extended answers
CS Field Guide – AI & Machine Learning Chapters
Video explainers on how AI works in real life
Interactive tools: neural net visualisers, chatbot demos
Workbook and tasks on Google Classroom
Glossary of AI terms
Practice exam-style questions and structure guides
AI is transforming the world around us — from diagnosing diseases to driving autonomous vehicles. Understanding how AI works, where it’s used, and what risks it brings is essential for digital citizens today. This resource will support you to think critically, write with confidence, and prepare for success in NCEA — and beyond.