AI Ethics and Responsible Use: Beginner

Twenty-two pages that build judgement, not a list of rules. Each page works through short, invented scenarios with one reusable pattern: the situation, who is affected, benefits and harms, the options (including not using AI), the evidence and unknowns, a decision with conditions, who is accountable and when to review it. You practise on printed scenarios and in a chat assistant you already use. You never write code.

You begin with everyday questions about who benefits and who could be harmed, then core principles and how frameworks, standards, law and company policy differ. The next pages cover where bias comes from and what fairness trade-offs look like, trust and automation bias, deepfakes and disclosure, and privacy, consent and data rights. After that come copyright and creative work, honesty in learning and at work, safety, sensitive topics and high-stakes decisions with human oversight and appeals, then transparency, accountability, simple team policies, environment, labour and inclusion, and how to find the rules that apply to you.

Contested questions are shown as the strongest arguments on several sides, with views from different regions, and you practise deciding and explaining. A practice lab and a capstone, your own responsible-AI decision file, finish the tutorial. This tutorial is educational and is not legal advice: laws differ by country, sector and date, so you learn how to find and check the rules that apply to you. Every page is available in English and Bangla.