# AI vocabulary and the law by market

Published contents
Contents1 Scope2 Normative references3 Terms and definitions4 Abbreviated terms5 AI conceptsClause 3, terms
3.1 Terms related to AI3.1.1 AI agent3.1.2 AI component3.1.3 artificial intelligence3.1.4 artificial intelligence system3.1.5 autonomy3.1.6 application specific integrated circuit3.1.7 automatic3.1.8 cognitive computing3.1.9 continuous learning3.1.10 connectionism3.1.11 data mining3.1.12 declarative knowledge3.1.13 expert system3.1.14 general AI3.1.15 genetic algorithm3.1.16 heteronomy3.1.17 inference3.1.18 internet of things3.1.19 IoT device3.1.20 IoT system3.1.21 knowledge3.1.22 life cycle3.1.23 model3.1.24 narrow AI3.1.25 performance3.1.26 planning3.1.27 prediction3.1.28 procedural knowledge3.1.29 robot3.1.30 robotics3.1.31 semantic computing3.1.32 soft computing3.1.33 symbolic AI3.1.34 subsymbolic AI3.1.35 task3.2 Terms related to data3.2.1 data annotation3.2.2 data quality checking3.2.3 data augmentation3.2.4 data sampling3.2.5 dataset3.2.6 exploratory data analysis3.2.7 ground truth3.2.8 imputation3.2.9 input data3.2.10 label3.2.11 personally identifiable information3.2.12 production data3.2.13 sample3.2.14 test data3.2.15 validation data3.3 Terms related to machine learning3.3.1 Bayesian network3.3.2 decision tree3.3.3 human-machine teaming3.3.4 hyperparameter3.3.5 machine learning3.3.6 machine learning algorithm3.3.7 machine learning model3.3.8 parameter3.3.9 reinforcement learning3.3.10 retraining3.3.11 semi-supervised machine learning3.3.12 supervised machine learning3.3.13 support vector machine3.3.14 trained model3.3.15 training3.3.16 training data3.3.17 unsupervised machine learning3.4 Terms related to neural networks3.4.1 activation function3.4.2 convolutional neural network3.4.3 convolution3.4.4 deep learning3.4.5 exploding gradient3.4.6 feed forward neural network3.4.7 long short-term memory3.4.8 neural network3.4.9 neuron3.4.10 recurrent neural network3.5 Terms related to trustworthiness3.5.1 accountable3.5.2 accountability3.5.3 availability3.5.4 bias3.5.5 control3.5.6 controllability3.5.7 explainability3.5.8 predictability3.5.9 reliability3.5.10 resilience3.5.11 risk3.5.12 robustness3.5.13 stakeholder3.5.14 transparency3.5.15 transparency3.5.16 trustworthiness3.5.17 verification3.5.18 validation3.6 Terms related to natural language processing3.6.1 automatic summarization3.6.2 dialogue management3.6.3 emotion recognition3.6.4 information retrieval3.6.5 machine translation3.6.6 named entity recognition3.6.7 natural language3.6.8 natural language generation3.6.9 natural language processing3.6.10 natural language processing3.6.11 natural language understanding3.6.12 optical character recognition3.6.13 part-of-speech tagging3.6.14 question answering3.6.15 relationship extraction3.6.16 sentiment analysis3.6.17 speech recognition3.6.18 speech synthesis3.7 Terms related to computer vision3.7.1 computer vision3.7.2 face recognition3.7.3 image3.7.4 image recognitionClause 5, concepts
5.1 General5.2 From strong and weak AI to general and narrow AI5.3 Agent5.4 Knowledge5.5 Cognition and cognitive computing5.6 Semantic computing5.7 Soft computing5.8 Genetic algorithms5.9 Symbolic and subsymbolic approaches for AI5.10 Data5.11 Machine learning concepts

Home / Rules by market

# Where the vocabulary meets the law

ISO/IEC 22989 is a voluntary terminology standard. It creates no legal duty on its own. The duties come from the law and regulation of each market, and those instruments borrow AI vocabulary in their own way. This page names the instruments that matter to the buyer in four markets and says plainly which texts we quote and which we only name.

How to read this page. A named instrument is not a quoted instrument. We do not hold the text of the laws below, so we name the obligation and the source, and we do not state a clause or a penalty as if we had read it. Check the current official text before you rely on it.

## United States

The federal position is guidance rather than a single AI statute. The NIST AI Risk Management Framework is the reference most US AI governance programmes use, and it shares the vocabulary of trustworthiness, risk and life cycle with ISO/IEC 22989. Sector regulators and state privacy laws add duties on data, notice and automated decisions. The vocabulary work is voluntary; the privacy duties are not.

## European Union

The EU Artificial Intelligence Act, Regulation (EU) 2024/1689, is the primary instrument. It defines AI system and sets obligations by risk category, with duties for providers and deployers. A firm that uses the ISO vocabulary in its AI Act evidence should map the two, because the regulation has its own definitions and its own scope tests. The ISO standard does not replace the regulation.

## United Kingdom

The UK has no single AI act. The approach is a pro-innovation framework applied by existing regulators, with the Information Commissioner's Office leading on data protection and AI guidance. A UK firm can use ISO/IEC 22989 as a shared vocabulary, but its legal duties come from data protection law and the sector regulator, not from the standard.

## Australia

The Australian government publishes voluntary AI ethics principles and guidance for organisations, and the Privacy Act 1988 sets the binding duties on personal information. The standard is useful as a vocabulary; it is not an Australian legal instrument and does not create a duty.

## What this means for the register

Keep two columns in the kit: the standard entry and the legal instrument that uses the same idea. They are not the same claim. The standard tells you what a word means; the law tells you what you must do. A register that blurs them will fail the first legal review.

Last updated: 2026-10-21

Source: https://iso-22989-revision-checker.theartofservice.com/rules/