International AI governance and standards
AI rules and standards outside the EU and US, and the voluntary frameworks that increasingly function as the baseline a buyer asks you to meet.
Most AI compliance writing is about two jurisdictions. That is a reasonable place to start and a bad place to stop, because the instruments that will first block a launch are often somewhere else entirely: a filing you cannot complete in time in China, a labelling duty in Korea that starts on a fixed date, a certificate a procurement team in Singapore or the Gulf asks for before it will read your security questionnaire. None of those is exotic. They are just written in a different register from the EU AI Act, and several of them do their work without imposing a fine on anybody.
These pages take one instrument each and say what it actually requires, who it binds, from what date, and what it deliberately leaves alone. Where the position is unsettled — a bill in committee, a statute whose implementing regulations have not appeared — the page says so and names the thing to check, because a confident summary of an unsettled question is worse than no page. Assume the overview of the landscape exists; this is the level underneath it.
The FCA and PRA on AI: Existing Rules, No New Rulebook
How the UK financial regulators apply SM&CR accountability, the Consumer Duty and operational resilience to AI instead of writing an AI regime, and what that leaves unresolved.
9 min read
The ICO's AI and Data Protection Guidance: What It Adds
The structure of the ICO's AI guidance, the fairness chapter that generic GDPR advice does not contain, and how the 2025 reform of Article 22 changed the automated-decisions position.
9 min read
The UK's Pro-Innovation Approach: Five Principles, No Statute
What the 2023 white paper actually established — five non-statutory principles applied by existing regulators — and the things it deliberately declined to do.
8 min read
The Online Safety Act When AI Generates the Content
When a generative AI feature brings a service into the Online Safety Act's scope, which duties then apply, and how the intimate image offences reach deepfakes.
9 min read
Canada's AIDA: What It Would Have Required, and Why It Died
The Artificial Intelligence and Data Act died with Bill C-27 when Parliament was prorogued in January 2025 — what it would have imposed, and what governs Canadian AI now.
8 min read
The OPC's AI Guidance Under PIPEDA: Canada's Operative Framework
With AIDA dead, PIPEDA is what governs AI in Canada federally — the OPC's principles for generative AI, the appropriate purposes test, and the meaningful consent standard.
9 min read
Quebec Law 25: The Automated Decision Rights, Section by Section
Section 12.1's notification and explanation rights for exclusively automated decisions, the profiling notice in section 8.1, and how both differ from GDPR Article 22.
9 min read
Japan's AI Guidelines for Business: the Soft-Law Approach
What the METI and MIC guidelines recommend, which of the three business roles you occupy under them, and why Japan chose guidance with no penalty attached.
9 min read
Japan's AI Promotion Act: What It Actually Requires
The 2025 Act creates duties on the state, best-efforts duties on business, and no penalties at all — with disclosure rather than fines as the enforcement mechanism.
9 min read
China's Generative AI Measures: the Registration and Filing Duty
The security assessment and algorithm filing a generative AI service must complete before it can be offered to the public in mainland China, and which services the duty catches.
10 min read
China's Algorithm Registration Requirement, Explained
The CAC's algorithm filing obligation under the 2022 recommendation provisions — which five algorithm types it covers, the ten-working-day deadline, and what gets published.
9 min read
China's Deep Synthesis Provisions: Labelling Synthetic Content
The 2023 provisions require two different kinds of label on synthetic media, restrict removing them, and demand consent before a real person's face or voice is edited.
9 min read
Brazil's PL 2338: the Status of Its AI Bill
A dated account of where Brazil's comprehensive AI bill has actually got to, and why describing its risk tiers as Brazilian law is wrong.
8 min read
Brazil's LGPD and Automated Decision-Making Provisions
Article 20 of the LGPD gives a right to request review of solely automated decisions — but, unlike the GDPR, it does not require the reviewer to be a human being.
9 min read
South Korea's AI Basic Act: Effective January 2026
What Korea's Framework Act asks of high-impact AI operators and generative AI providers, when it applies, and which details the Enforcement Decree still fills in.
10 min read
India's DPDP Act: What It Says (and Doesn't Say) About AI
The Act contains no AI-specific regime; it reaches AI through consent, accuracy and one algorithmic due-diligence duty on Significant Data Fiduciaries.
10 min read
Singapore's Model AI Governance Framework
The structure of Singapore's voluntary framework and its generative AI companion, and the binding PDPA rules underneath that voluntary really does not reach.
9 min read
Australia's Proposed Mandatory AI Guardrails
The ten guardrails proposed in the September 2024 consultation, the three regulatory options canvassed with them, and where the proposal has actually got to.
9 min read
Switzerland's Federal Data Protection Act and AI
How the revised FADP reaches AI through automated individual decisions, impact assessments and transfer rules, in a country with no AI statute.
9 min read
UAE's AI Regulation and Dubai's AI Governance Framework
Which UAE and Dubai AI instruments are binding law, which are strategy, and why the free zones have stricter AI rules than the federal onshore regime.
9 min read
South Africa's POPIA and Automated Decision-Making
Section 71 restricts decisions based solely on automated processing, with two exceptions and a specific duty to disclose the underlying logic — and it protects companies as well as people.
9 min read
ISO/IEC 42001 Certification: What the Audit Actually Checks
The certification audit examines an AI management system against clauses 4 to 10 and Annex A controls — it does not test your model, and the certificate does not say your outputs are safe.
10 min read
What ISO/IEC 42001 Certification Adds Over a Self-Assessment
What an accredited third-party audit against ISO/IEC 42001 gives you that an internal gap assessment cannot, and when each is genuinely enough.
9 min read
The NIST AI RMF's Four Functions, Explained
What Govern, Map, Measure and Manage each ask an organisation to produce, and why the framework is ordered the way it is.
9 min read
The NIST Generative AI Profile: What It Adds to the RMF
The twelve generative-AI risks NIST AI 600-1 names that the base framework does not, and how its suggested actions attach to RMF subcategories.
9 min read
SOC 2 for an AI Vendor: Which Trust Service Criteria Apply
How the five trust services categories map onto the controls an AI vendor has to evidence, and which of them are optional in practice.
10 min read
How ISO/IEC 23894 Feeds Into an ISO 42001 Management System
Why 23894 is risk-management guidance that supplies the method for 42001's requirements, rather than a competing or alternative standard.
8 min read
The IEEE 7000 Series: What These AI Standards Actually Cover
The individual standards in IEEE's 7000 series, what each one's scope is, and what invoking one in a contract commits you to.
8 min read
CEN-CENELEC JTC 21: the EU's Harmonised Standards for the AI Act
What the presumption of conformity in Article 40 of the AI Act actually gives a provider, and where JTC 21's standards stand in producing it.
10 min read
The EU's Text-and-Data-Mining Opt-Out Under Article 4 CDSM
The machine-readable reservation of rights that switches off the commercial text-and-data-mining exception, and what is genuinely unsettled about it.
10 min read
The US Copyright Office's AI Report, Part 2: Copyrightability
What the Copyright Office concluded in January 2025 about human authorship, prompts, and when AI-assisted works can be registered.
9 min read
The US Copyright Office's AI Report, Part 3: Training Data
The fair-use analysis in the Office's May 2025 pre-publication report on generative AI training, and the unusual status the document has carried since.
10 min read
The UK's AI and Copyright Consultation: the Proposed Outcome
The opt-out-based exception the UK government said it preferred, what happened to it in Parliament, and what has actually been decided.
9 min read
Japan's Article 30-4: the Text-and-Data-Mining Copyright Exception
The non-enjoyment purpose test in Article 30-4 of Japan's Copyright Act, and the proviso that stops it being an unconditional permission to train.
9 min read
Getty Images v Stability AI: the UK Case, Status and Rulings
What the English High Court actually decided in the Getty proceedings, which claims were dropped before judgment, and what remains undecided.
9 min read
New York Times v OpenAI: Case Status and Key Rulings
What has actually been decided in the New York Times litigation against OpenAI and Microsoft, and what every ruling so far has left open.
9 min read
Thomson Reuters v Ross Intelligence: What the Ruling Decided
The February 2025 summary judgment holding that Ross's copying of Westlaw headnotes was not fair use, and how far it actually reaches.
9 min read
Other topics
- LLM fundamentals & architecture
- Tokens, tokenization & context windows
- Prompt engineering
- Reasoning models & test-time compute
- Multimodal AI: vision, audio, video
- RAG & retrieval
- Embeddings & vector search
- AI agents & tool use
- Structured output & function calling
- Fine-tuning & post-training
- Local inference errors, string by string
- Running local models day to day
- Testing code that calls an LLM
- Snapshot and property testing for model output
- Regression suites for prompts
- Eval gates in CI
- Flaky tests against a model
- Determinism and the cost of testing
- Contract and streaming tests
- Testing tool calls and retrieval
- Inference, serving & latency
- Rolling out a prompt change
- Testing AI systems in practice
- Forecasting a time series
- Machine learning on tabular data
- Geospatial data and models
- Understanding audio that is not speech
- Understanding video
- Core computer vision tasks
- Machine learning on graphs
- Point clouds and 3D
- Evaluation, benchmarks & LLM-as-judge
- Sensor and IoT data
- Logs and event streams
- Models over biological sequences
- Machine learning on molecules
- Embedding and searching code
- Extracting invoices and purchase orders
- Receipts, statements and tax forms
- Insurance policies and contracts
- Deeds, court filings and patents
- Extracting from medical records
- Observability & LLMOps
- CVs, certificates and identity documents
- Shipping, customs and technical documents
- Meetings, email, chat and filled-in forms
- Building an extraction pipeline
- Business, property and inspection documents
- Contract clauses and insurance claims
- Regulated and compliance documents
- Consumer, travel and closing documents
- Mapping one chat API onto another
- SDK and framework migrations
- Hallucination & failure modes
- Re-embedding and model deprecation
- Cutting over between providers
- Parity gaps, shims and legacy endpoints
- Moving between model versions
- Migrating vector stores and caches
- Mapping capabilities and parameters
- Migrating pipelines and agents
- Contracts, runbooks and rollback
- Auditing a codebase before a cutover
- Compliance and fine-tune migration
- LLM cost engineering
- Routing, cost tracking and multi-tenancy
- What a migration does to your prompts
- AI security & prompt injection
- Privacy, compliance & data residency
- AI governance, policy & society
- Building reliable AI applications
- AI hardware, GPUs & compute
- Open-weight models & local inference
- AI for developers & coding agents
- AI in industry: vertical playbooks
- AGI, superintelligence, alignment & the long future
- Machine learning foundations
- NLP fundamentals & classical tasks
- Data engineering for AI
- Synthetic data & dataset curation
- AI product design & UX
- Search, ranking & recommendation
- Enterprise adoption & change management
- AI careers, skills & teams
- Reading AI research
- AI in science & discovery
- Robotics & embodied AI
- AI economics, markets & business models
- AI myths, hype & media literacy
- Context engineering
- Shipping AI features: patterns & anti-patterns
- Build it: end-to-end AI tutorials
- Python for AI: hands-on recipes
- TypeScript, React and the web
- Frameworks and SDKs
- Errors and troubleshooting
- AI facts, numbers and statistics
- The history of AI
- The maths behind AI
- Architectures beyond the transformer
- Reinforcement learning
- Diffusion and generative media
- Speech, audio and voice engineering
- Benchmarks, one at a time
- AI search visibility
- Infrastructure and operations
- Databases and storage for AI
- Knowledge graphs and structured knowledge
- Classical ML in production
- Regulation, jurisdiction by jurisdiction
- Prompt recipes and pattern library
- AI for people who do not write code
- Writing, media and creative work
- Edge and on-device AI
- Interpretability and model internals
- Field notes
- OpenAI model behaviour
- Claude model behaviour
- Gemini model behaviour
- Llama model behaviour
- Mistral model behaviour
- Qwen model behaviour
- DeepSeek model behaviour
- Cohere model behaviour
- Grok model behaviour
- Small model behaviour
- Hybrid model architectures
- Token cost by language and script
- Transliteration, romanization and script handling
- Locale-correct output
- Multilingual generation quality
- Multilingual pipelines
- The EU AI Act, article by article
- AI under the GDPR and EU data law
- US AI regulation, state and sector
- AI litigation and enforcement
- Running AI workloads on AWS
- Running AI workloads on Google Cloud
- Running AI workloads on Azure
- AI at the edge: Workers, Vercel and Netlify
- Serving models on Kubernetes
- Operating AI infrastructure
- Quantization formats and what they cost
- llama.cpp, flag by flag
- Ollama and the desktop local-model runtimes
- Local models on Apple Silicon
- Hardware for local inference
- Running speech and embedding models locally
- Model files, adapters and conversion
- VRAM arithmetic for local models