Glossary
Liability for harm caused by a defective product, and a live question where the product is software or an AI model rather than a physical good.
Liability and AI
from AI & Law
When an AI system causes harm — a flawed medical diagnosis, a discriminatory hiring decision, a self-driving car accident — determining legal liability is complex. Traditional negligence principles require identifying a duty of care and a breach, but where does the fault lie when the decision-making process is opaque? Product liability under the Consumer Protection Act 1987 may apply if AI is treated as a product, but its application to software and AI-as-a-service models is unsettled. The EU's proposed AI Liability Directive would have introduced a presumption of causation where a defendant failed to comply with AI-specific rules, but the Commission withdrew it for lack of agreement, formally in October 2025. Neither the EU nor the UK now has a bespoke AI liability regime, so liability develops through existing principles and case-by-case judicial interpretation on both sides.
Large Language Model (LLM)
An AI system trained on vast text datasets to generate, summarise, and analyse human language — the technology behind tools like ChatGPT and legal AI assistants.
EU AI Act
The European Union's comprehensive regulation classifying AI systems by risk level and imposing corresponding obligations on developers and deployers.
Algorithmic Bias
Systematic errors in AI decision-making that produce unfair outcomes for particular groups, often reflecting biases present in training data.
Explainability
The degree to which the internal logic of an AI model can be understood and communicated to humans — a key requirement for high-risk AI under many regulatory frameworks.
Training Data
The dataset used to teach an AI model to recognise patterns and generate outputs — its quality and composition directly determine the model's capabilities and biases.
Model Risk
The risk of adverse consequences arising from decisions based on AI or statistical models that are incorrect, misused, or inadequately understood.
AI Governance
The internal policies, processes, and controls an organisation puts in place to manage the development, procurement, and use of AI systems responsibly.
Deepfake
Synthetic media — typically video or audio — generated by AI to convincingly depict events that did not occur, raising concerns in fraud, evidence, and defamation.