The library
Every module stands on its own and is open to every reader. Search the library, or narrow it by topic and level, and each module page suggests what is worth reading first.
New to AI? Start with What AI is, and what it is not, the first module on the Beginner path.
Modules
20 modules
What AI is, and what it is not
The difference between rules written by people and patterns learned from examples, what “model” means, and where AI already sits in legal work.
Topics: AI basicsRegulation
How a machine learns from examples
How a computer program learns from marked examples, how developers test it on examples it has not seen, why it is sometimes confidently wrong, and why the examples shape what it learns.
Topics: AI basicsTraining and data
Neural networks without the mathematics
How a neural network weighs each number it reads, with every weight pictured as a dial that training sets, and why the trained result is one large file of numbers.
Topics: AI basicsInside a model
How a chatbot writes an answer
Text cut into pieces, the next piece predicted one at a time, why the answer reads as confident whatever its accuracy, and how the hidden instructions and searched documents a chatbot adds shape its answer.
Topics: AI basicsLanguage models and chatbots
Does AI reason?
What happens when an AI model writes out its working before answering, where writing out steps helps and where it fails, and why models invent authorities, with a worked example from the Divisional Court.
Topics: Language models and chatbotsLiability and professional duty
Using an AI assistant well
Writing a clear request, working in steps, keeping sources apart from the assistant’s own reasoning, checking every source, and what memory and saved instructions mean for client confidentiality.
Topics: Using AI in practiceLiability and professional duty
Where AI meets the law: a map
The points at which copyright, data protection, the AI Act and liability attach to an AI product, stage by stage, each question with its primary source and the Advanced module that treats it.
Topics: CopyrightData protectionRegulationLiability and professional duty
What a model is
The small amount of mathematics the course uses, what a trained model physically consists of, and how weights, biases and layers turn input numbers into an output.
Topics: Inside a model
How a model learns
How training measures a model’s errors and corrects them, why models generalise and memorise at once, and how the computing power used in training became a regulatory yardstick.
Topics: Training and dataRegulation
Words as numbers
How text is cut into short pieces called tokens, why the cutting causes odd failures, and how each piece becomes a point on a map of meanings.
Topics: Inside a model
The transformer
How a chatbot links words, stores facts and writes its answer word by word, and why long documents cost more and can be read less reliably.
Topics: Inside a modelData protection
From predictor to assistant
How a text predictor becomes an assistant: pretraining, scaling laws, post-training, reasoning models, mixtures of experts and distillation.
Topics: Language models and chatbotsTraining and data
Sampling, hallucination and memorisation
How a model chooses each word, why it invents things, and what the research shows about models reproducing their training data.
Topics: Language models and chatbotsCopyright
The system around the model
System prompts, retrieval, tools and agents, the payment protocols built for agents, and why prompt injection is so hard to fix.
Topics: Agents and systemsUsing AI in practice
Open weights, images and provenance
Fine-tuning, the licences for downloadable models and the AI Act’s open-source exemption, how image and voice generators work, and the techniques and EU duties for marking machine-made content.
Topics: CopyrightTesting and transparency
Looking inside and testing
What research can see inside a model so far, the duties to explain automated decisions under the GDPR, the UK GDPR and the AI Act, why benchmark scores mislead, and the safety frameworks behind releasing powerful models to vetted users first.
Topics: Testing and transparencyData protection
Training data and copyright
How UK, EU and German law treats the copies made to train a model, the model and its output, through the leading cases in London, Hamburg and Munich, a reference before the Court of Justice and the EU opt-out from the general exception for text and data mining, which is the automated analysis of works.
Topics: CopyrightTraining and data
Personal data in models
Whether a trained model holds personal data, the lawful basis for training and the enforcement so far in the EU and the UK, why erasure and correction are hard, and what the GDPR and the UK GDPR say about automated decisions.
Topics: Data protectionTraining and data
Regulating the technology
The EU AI Act and the timetable set by its recent amendments, what it treats as an AI system, a general-purpose model and a high-risk use, the new Product Liability Directive, and the UK’s regulator-led approach.
Topics: RegulationLiability and professional duty
Liability, agents and professional duty
Who answers for a chatbot’s wrong answer under English and EU law, including the new Product Liability Directive, how contract and agency law meet AI agents, what financial regulators expect, and the duties courts and regulators now place on lawyers who use AI.
Topics: Liability and professional dutyAgents and systems
Guided paths
Each level is also an optional route through the library, in an order where each module builds on the one before. Readers who switch on progress tracking see how far along each path they are.
Switched on, it keeps a short record of the modules you open and the quizzes you finish in this browser’s own storage, and the record stays on this device.
Beginner path
For readers without a technical background, written without mathematics and with every term explained where it first appears.
Intermediate path
For readers who want the mechanics: the arithmetic inside a model, how training sets its numbers and how a language model writes.
Advanced path
For readers who advise on AI: the systems built around models, how they are tested, and the law of the European Union and the United Kingdom that applies to them.