Module 7 · Level I · Foundations

Limitations and staying safe

Hallucination, bias, knowledge cutoffs, privacy, deepfakes and AI-powered scams: what AI gets wrong, and how to protect yourself.

6 lessons · about 1 hour

The module in 50 secondsCaptions on · sound optional

What’s inside

  1. 01
    Why fluent isn't the same as true

    What AI 'hallucinations' are, why language models produce them, and why invented sources are the most dangerous kind. · 10 min

  2. 02
    Bias and fairness

    Where bias in AI comes from, how it shows up in text and images, and what you can do about it as an everyday user. · 10 min

  3. 03
    Knowledge cutoffs and live search

    Why an AI model's knowledge stops at a point in time, how web search changes that, and how to tell which one you're getting. · 9 min

  4. 04
    Privacy and training settings

    What happens to what you type, whether it's used to train AI, and the settings that give you more control in each tool. · 10 min

  5. 05
    Deepfakes and voice cloning

    How AI can fake a face or a voice, why spotting fakes by eye is getting harder, and the habits that protect you anyway. · 10 min

  6. 06
    AI-powered scams, and when not to use AI at all

    How AI makes old scams more convincing, the UK routes for reporting them, and the situations where AI is the wrong tool. · 11 min

Where this sits on your path depends on your assessment. Some people skip this module outright; others start here. The free placement assessment decides, and the first lesson of every module is free to read. Find your level →

Also at Level I

1What AI actually is
AI, machine learning, deep learning and generative AI, untangled: what each term means, what it doesn't, and why the hype and the fear both miss.2A short history of AI
From Turing and the 1956 Dartmouth workshop through two AI winters, deep learning and the transformer to ChatGPT and agents: how we got here, and what it predicts.3How machines learn
Data, training and prediction; supervised, unsupervised and reinforcement learning, explained with everyday examples and no maths.4Types and styles of AI
Narrow and general, predictive and generative, rules and learning: the different styles of AI and where you already meet each one.