Governance, Policy & Law

Laws, standards, treaties, summits and industry frameworks. 130 entries live here, and 191 from other domains touch it.

Essential

AI copyright litigationThe many lawsuits in which authors, artists, news organizations, record labels and others accuse AI companies of copying their work without permission to build or run AI models.
AI governanceThe rules, institutions and habits that shape how AI is built and used — from laws and treaties to technical standards and a company's own review processes.
AI regulationLaws and binding government rules about artificial intelligence: what AI may be used for, what checks its makers must run, and what penalties apply when they break the rules.
AI Safety InstituteA government agency that tests the most advanced AI models for dangerous abilities and studies how to make them safe. Britain and the United States set up the first ones in 2023.
AI Safety SummitA series of international meetings of governments, AI companies and researchers, begun in England in 2023, to agree on how to handle the risks and benefits of the most advanced AI.
America's AI Action PlanThe Trump administration's 2025 strategy for winning a global AI race: cutting regulation, building data centers and power plants quickly, and exporting American AI technology to allies.
EU AI ActThe European Union's law on artificial intelligence, the first broad AI law anywhere: it bans some uses, sets strict checks for risky ones and puts duties on the makers of the biggest AI models.
export controls on AI chipsGovernment rules that limit which countries and companies may buy the most advanced AI chips and the machines used to make them. The United States uses them mainly to slow China's progress in AI.
fair use and AI trainingThe unsettled US legal question of whether AI companies may copy books, articles, pictures and music to train their models without permission, under the rule that allows some unlicensed uses of copyrighted work.
frontier AIThe most capable general-purpose AI systems of the moment — those at or beyond the leading edge — which governments single out for extra safety attention.
general-purpose AI modelThe EU's legal name for the large, adaptable AI models behind chatbots and similar tools: models that can turn their hand to many different jobs and be built into many other products.
high-risk AI systemUnder EU law, an AI system used where mistakes could seriously hurt people's safety or rights — in hiring, schooling, loans, policing, borders or products like medical devices — and which must therefore pass strict checks.
lethal autonomous weapons systemA weapon that, after a person sets it going, picks out and attacks targets — including people — on its own, with no human deciding each strike. Critics call them killer robots.
StargateA giant venture announced in 2025 by OpenAI, SoftBank and Oracle to build data centers in the United States for training and running AI, with a pledged $500 billion.

All other entries

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AI auditAn independent check of an AI system, or of the company using it, against agreed standards — for example, testing whether a hiring tool treats women and men fairly.
AI authorshipThe question of whether a work or invention produced by AI can be protected by copyright or patent, and if so who counts as its author or inventor: the AI, the person using it, or no one.
AI Basic ActSouth Korea's main AI law, in force since January 2026, which sets safety and transparency duties for AI used in sensitive areas and for AI-generated content.
AI Diffusion RuleA 2025 US rule, cancelled before it took effect, that would have sorted the world's countries into three groups with different limits on how many advanced AI chips they could buy.
AI liabilityWho has to pay or answer in court when an AI system causes harm — the company that built it, the business that used it or the person who relied on it — and under which laws.
AI OfficeThe European Commission's team that oversees the EU AI Act, especially the rules for the largest AI models, and coordinates how the law is applied across Europe.
AI PactA voluntary European Commission scheme in which companies pledge to start following the EU AI Act's main ideas early, before the rules legally apply to them.
AI preemptionThe push in the United States for a single national AI law that would override the states' own AI laws, and the fight over whether that is wise or even lawful.
AI Promotion ActJapan's 2025 national AI law, which sets up a government AI headquarters and strategy to encourage AI development and use, relying on cooperation and guidance rather than fines.
AI red linesLimits on AI that would be forbidden worldwide no matter what — for example AI that copies itself without permission or controls nuclear weapons — which campaigners want governments to agree on.
AI regulatory sandboxA supervised testing ground where companies can try out new AI with regulators watching and advising, before the product faces the full weight of the rules.
AI Safety LevelAnthropic's numbered scale, modeled on laboratory biosafety levels, for matching how dangerous an AI model could be with how strong the protections around it must be.
AI whistleblower protectionsLegal and company safeguards that protect employees of AI companies who report safety dangers or legal violations — to regulators or inside the company — from being fired, sued or otherwise punished.
AI-generated content labelingMarking text, images, audio or video as made by AI — with a visible notice, hidden data in the file, or both — so that people and platforms can tell synthetic content from real.
algorithm filingChina's requirement that companies register certain algorithms — such as recommendation feeds and chatbots — with the internet regulator, describing what they do and how their risks are controlled.
algorithmic accountabilityThe idea that the people and organizations behind automated decision systems must be able to explain and justify those systems' effects, answer for the harm they cause, and fix it.
algorithmic impact assessmentA structured review, done before and during the use of an automated system, of whom it could affect and how — such as unfair treatment or privacy harms — and what will be done about it.
automated decision-makingWhen a computer system, rather than a person, makes or effectively makes a decision about someone — such as approving credit, screening job applicants or flagging possible welfare fraud.
automated employment decision toolSoftware that scores, ranks or screens job candidates or employees. New York City requires employers using such tools to have them checked for bias every year and to tell applicants.
Bartz v. AnthropicA US lawsuit by book authors against the AI company Anthropic that ended in a record $1.5 billion settlement, after a judge ruled that training on purchased books was legal but keeping pirated copies was not.
biometric categorisationUsing AI to sort people into groups — by age, sex, ethnicity and the like — from their faces, voices or other body features. The EU bans using it to guess sensitive traits such as religion or sexuality.
biometric dataInformation about your body or behavior — your face, fingerprints, voice, eyes or the way you walk — measured by technology and used to recognize who you are or to guess things about you.
Bletchley DeclarationA short statement signed by 28 countries and the European Union at the first global AI safety summit, held in England in 2023, agreeing that the most advanced AI could cause serious harm.
Blueprint for an AI Bill of RightsA 2022 White House document listing five protections Americans should have when automated systems affect their lives — safety, fairness, privacy, explanation and a human alternative. It was guidance, not law.
Brussels effectThe way European Union rules end up shaping products and laws worldwide, because global companies often find it simpler to follow the strictest big market's rules everywhere.
capability thresholdA level of dangerous ability — such as meaningfully helping someone make a biological weapon — that, once an AI model reaches it, obliges its developer to add stronger safeguards or hold the model back.
catastrophic riskThe risk that AI could cause disaster on a massive scale — many deaths or enormous damage — through weapons, cyberattacks or systems escaping human control. Several laws now define it precisely.
Center for AI Standards and InnovationThe US government's AI testing and standards center, part of the National Institute of Standards and Technology. It evaluates advanced AI models, American and foreign, for national-security risks and works with companies on voluntary testing.
CERN for AIA proposed publicly funded, international AI laboratory modeled on CERN, the European particle-physics center, where countries would pool money, computers and scientists to do AI research together.
CHIPS and Science ActA 2022 US law that put tens of billions of dollars into building computer-chip factories and chip research in the United States, to reduce dependence on chips made in Asia.
Collingridge dilemmaThe trap that a new technology is easiest to control when little is known about its harms, but by the time the harms are clear it is too widespread to change easily.
Colorado AI ActA Colorado law, first passed in 2024, governing AI used to make important decisions about people, such as hiring, lending and housing. In 2026 it was rewritten as a narrower law that starts in 2027.
compute governanceUsing control over the computer chips and data centers that AI depends on — who can buy them, where they go, how they are used — as a way to oversee powerful AI.
compute thresholdA legal cutoff based on how much computation was used to train an AI model. Models trained with more than that amount face extra rules, on the theory that bigger training runs produce more capable models.
conformity assessmentThe check, done by the maker or by an approved outside body, that a high-risk AI system meets the EU's legal requirements before it can be sold or used.
Cyberspace Administration of ChinaChina's top internet authority, in charge of online censorship as well as regulation, which also writes and enforces most of the country's AI rules, such as the registration of chatbots and recommendation algorithms.
data protectionLaws and practices that control how organizations collect, use, store and share information about people, and that give people rights over it, such as seeing it or having it deleted.
deep synthesisThe Chinese legal term for AI that creates or alters text, images, voices, video or virtual scenes — the technology behind deepfakes — and for the rules that govern it.
Digital OmnibusA European Union package, proposed in 2025, that simplified and delayed parts of its digital rules — above all pushing back the strictest requirements of the EU AI Act by more than a year.
digital replicaA realistic computer-made copy of a real person's voice or appearance — such as an AI clone of a singer's voice or a digital stand-in for an actor — that can say or do things the person never did.
Digital Services ActThe EU law that sets rules for online platforms and search engines — how they handle illegal content, explain their recommendation algorithms and manage the risks their services create for society.
dual-use foundation modelA US legal term for a general-purpose AI model that serves everyday uses but is capable enough that it could help someone build weapons, mount cyberattacks or evade human control.
emotion recognition systemAI that tries to work out how people feel or what they intend from their faces, voices or bodies. The EU bans it at work and in schools and tightly regulates it elsewhere.
Ethics Guidelines for Trustworthy AIGuidelines written for the European Commission by an expert group in 2019, listing seven requirements AI should meet to be trustworthy; they paved the way for the EU AI Act.
European Artificial Intelligence BoardA committee of representatives from every EU country that helps apply the EU AI Act consistently across Europe and advises the European Commission.
Executive Order 14110A sweeping 2023 order by US President Joe Biden that told federal agencies how to manage AI risks and required makers of the largest AI models to report their safety tests to the government. It was revoked in 2025.
Executive Order 14434A September 2026 order by US President Donald Trump telling federal agencies to say 'super intelligence' (SI) instead of 'artificial intelligence' (AI) in official documents and communications.
export control directiveA US government order, used against AI models in June 2026, telling a company to stop foreigners from using some of its AI models for national-security reasons.
Framework Convention on Artificial IntelligenceThe first binding international treaty on AI, drawn up by the Council of Europe, in which countries promise that AI used by governments and businesses will respect human rights, democracy and the rule of law.
Frontier AI Safety CommitmentsPromises made in 2024 by major AI companies to publish safety plans for their most advanced models, including the danger points at which they would stop if the risks could not be controlled.
Frontier Model ForumAn industry group set up in 2023 by leading AI companies to share safety research and best practices for the most advanced AI models.
Frontier Safety FrameworkGoogle DeepMind's published plan for spotting when its AI models approach dangerous abilities and applying stronger security and safeguards before that happens.
fundamental rights impact assessmentA check that certain organizations must make before using a high-risk AI system, writing down whose rights it could affect, how, and what they will do to prevent harm.
G7 Hiroshima AI ProcessAn effort begun by the G7 group of wealthy democracies in Japan in 2023 that sets voluntary rules for companies building the most advanced AI, which now report publicly on how they follow them.
General Data Protection RegulationThe European Union's main privacy law, in force since 2018, which controls how personal information is collected and used — including to train and run AI systems.
General-Purpose AI Code of PracticeA voluntary rulebook, published by the EU in 2025, that makers of large AI models can sign to show they follow the EU AI Act's rules on transparency, copyright and safety.
general-purpose AI model with systemic riskThe EU's label for the very largest and most capable AI models, whose failure or misuse could cause harm across society, so their makers must test them for dangers and report serious incidents.
Genesis MissionA US government program launched in 2025 to speed up science with AI, using the national laboratories' supercomputers and data to build AI tools for research.
Global Dialogue on AI GovernanceA yearly United Nations meeting, launched in 2025, where all countries — joined by companies, researchers and civil society — discuss how to cooperate on governing AI.
Global Digital CompactA 2024 agreement among United Nations member countries setting shared goals for the digital world — closing digital divides, protecting rights online, governing data and AI — and creating new UN bodies on AI.
Global Partnership on Artificial IntelligenceAn international group of countries, launched in 2020 and now run together with the OECD, that brings governments and experts together to put trustworthy AI into practice.
harmonised standardsOfficial European technical standards, written at the EU's request, that companies can follow to show their AI systems meet the law, instead of proving it from scratch.
High-level Advisory Body on Artificial IntelligenceA group of experts set up by the UN Secretary-General in 2023 to advise on governing AI worldwide; its 2024 report led to the UN's AI science panel and global dialogue.
human oversightKeeping people able to watch, understand, question and, if necessary, stop or overrule an AI system, rather than letting it act unchecked.
IAEA for AIThe idea of an international agency for the most advanced AI, modeled on the UN's nuclear watchdog, which inspects countries' nuclear programs to keep them safe and peaceful.
if-then commitmentA promise by an AI developer of the form: if our model can do a particular dangerous thing, then we will have these protections in place — or we will stop.
Independent International Scientific Panel on AIA group of 40 independent experts set up by the United Nations in 2025 to give every country a shared, science-based picture of what AI can do, its risks and its benefits.
intended purposeThe use a maker says its AI system is meant for. In EU law, the rules that apply to a system depend largely on this declared purpose.
Interim Measures for the Management of Generative AI ServicesChina's 2023 rules for chatbots and other AI that generate text, images, audio or video for the public, requiring lawful training data, content controls, labeling and, for many services, government approval before launch.
International AI Safety ReportA large scientific review, led by the computer scientist Yoshua Bengio and backed by more than 30 countries, summing up what is known about what advanced AI can do and how it could go wrong.
international humanitarian lawThe rules of international law that limit how wars may be fought, protecting civilians, the wounded and prisoners. They apply to every weapon, including ones that use AI.
ISO/IEC 22989An international standard that fixes agreed meanings for basic AI words — such as AI system, machine learning and trustworthiness — so that other standards, contracts and laws can use the same vocabulary.
ISO/IEC 23894An international guidance standard that explains how organizations can apply ordinary risk-management practice to the particular risks of AI systems.
ISO/IEC 42001An international standard for how an organization should run its AI work responsibly — policies, risk checks, roles and records — which outside auditors can certify, much as ISO 9001 does for quality.
ISO/IEC JTC 1/SC 42The international committee that writes the main worldwide technical standards on artificial intelligence, run jointly by the standards bodies ISO and IEC.
know-your-customer for computeRules that would make cloud companies check who their customers are before renting them enough computing power to train a large AI model, much as banks must verify who opens an account.
marginal riskHow much extra danger an AI model adds compared with what people could already do without it — for instance with search engines, textbooks or models that are already freely available.
market surveillance authorityThe government body in each EU country that checks AI systems on the market, investigates complaints, and can order unsafe or unlawful AI to be fixed or withdrawn.
model risk managementThe rules banks and other firms follow to make sure the mathematical models and AI systems they rely on are built correctly, checked independently and used only for what they are fit for.
National AI Research ResourceA US program to give university researchers, students and small companies shared access to the costly computers, data and AI models that are otherwise mostly available to big technology firms.
New York Times v. OpenAIA major lawsuit, filed in 2023, in which The New York Times accuses OpenAI and Microsoft of copying millions of its articles to train ChatGPT and of letting the chatbot reproduce its journalism.
NIST AI Risk Management FrameworkA free, voluntary guide from the US government's standards agency that helps organizations spot, measure and reduce the risks of the AI systems they build or use.
NO FAKES ActA proposed US law that would let people control AI-made copies of their voice and face, and would require websites to take down unauthorized fakes once notified.
notified bodyAn independent testing and certification organization, approved by an EU government, that checks whether certain risky products — including some AI systems — meet the law before they can be sold.
OECD AI PrinciplesGuidelines for trustworthy AI that governments agreed through the OECD in 2019, the first such standard agreed between governments; many later laws and agreements borrowed from them.
on-chip governance mechanismsFeatures built into AI chips that could check or enforce rules about how they are used — for example, proving which country a chip is in, or refusing to run without a valid license.
post-market monitoringThe duty of an AI system's maker to keep watching how it performs after release, gathering evidence from real use so that problems are found and fixed.
Preparedness FrameworkOpenAI's published process for testing its AI models for catastrophic risks — such as help with biological weapons or cyberattacks — and deciding what safeguards are needed before release.
Product Liability DirectiveThe EU law that lets people claim compensation, without proving anyone was careless, when a defective product injures them — rewritten in 2024 so that software and AI count as products.
prohibited AI practicesUses of AI that the EU bans outright as too harmful — such as manipulating people, social scoring, and most live facial recognition by police in public places.
provider and deployerThe two main roles in EU AI law: the provider is whoever makes an AI system and puts it out under its own name; the deployer is whoever uses it for work or official purposes.
RAISE ActA New York law requiring the largest AI developers to publish how they manage catastrophic risks and to report serious safety incidents quickly to a new state office. It takes effect in 2027.
remote biometric identificationUsing AI to recognize people at a distance — usually by matching faces in camera footage against a database — without their taking part. The EU strictly limits live police use of it in public places.
responsible scaling policyA public rulebook in which an AI company promises to test each new model for dangerous abilities and to add stronger safeguards, or slow down, as its models become more capable.
right of publicityA person's legal power to decide whether businesses may use their name, face, voice or other recognizable traits to sell things, and to be paid when they do. AI's skill at copying voices and faces makes it more important.
right to explanationThe idea that a person affected by a decision made or shaped by an algorithm — a refused loan, a rejected job application — is entitled to a meaningful account of why.
risk-based approachA way of regulating AI in which the strictness of the rules depends on how much harm a use could cause: bans for the worst uses, heavy checks for risky ones, little or nothing for the rest.
RobodebtAn Australian government program that used an automated calculation to accuse hundreds of thousands of welfare recipients of owing money, often wrongly. An official inquiry later found it unfair and illegal.
SB 1047A 2024 California bill that would have required makers of the biggest AI models to adopt safety plans and take care to prevent catastrophes. It passed the legislature, but the governor vetoed it.
SB 243A 2025 California law requiring AI companion chatbots to tell users they are not human, respond safely when people talk about suicide, and protect minors, including with regular reminders to take a break.
SB 53A 2025 California law requiring developers of the most powerful AI models to publish their safety plans, report serious safety incidents to the state and protect employees who raise alarms.
Section 230A 1996 US law that generally protects websites and apps from being sued over what their users post, and lets them remove content in good faith. Whether it protects what AI chatbots themselves say is unsettled.
serious incidentUnder EU AI law, an AI failure that kills or badly injures someone, disrupts vital services, violates fundamental rights or seriously damages property — which the maker must report to authorities quickly.
social scoringRating people on how they behave or what they are like, then using the score to treat them worse in unrelated parts of their lives — a practice the EU has banned for AI.
sovereign AIA country's ability to build and run AI on its own terms, so that the computers, models and know-how it relies on cannot be withheld or dictated by foreign companies or governments.
Statement on SuperintelligenceA 2025 public statement, signed by scientists, celebrities and politicians, calling for a ban on building superintelligent AI until it is shown to be safe and the public supports it.
substantial modificationA change to an AI system after release that is big enough, under EU law, to require a fresh check — and that can make whoever made the change legally responsible as its maker.
TAKE IT DOWN ActA 2025 US federal law that forces websites to remove intimate images of a person posted without consent, including AI-made fakes, within 48 hours of the victim's request, and makes posting them a crime.
Texas Responsible Artificial Intelligence Governance ActA Texas law, in force since 2026, that bans a short list of harmful uses of AI — such as pushing people toward self-harm or making sexual deepfakes of children — and sets rules for government use of AI.
text and data mining exceptionA rule in many countries' copyright laws that lets people use computers to copy and analyze large amounts of text, images or data without asking permission — sometimes only for research, sometimes unless owners opt out.
third-party AI evaluationTesting of an AI system by someone other than the company that made it — a government institute, a nonprofit lab or independent researchers — to check what it can do and how risky it is.
transparency obligationsEU rules requiring that people be told when they are dealing with AI: chatbots must say they are bots, AI-made content must be marked, and deepfakes must be labeled.
UNESCO Recommendation on the Ethics of AIA worldwide set of ethical principles for AI that all of UNESCO's member countries agreed in 2021, covering human rights, fairness, privacy, the environment, gender equality and education.
windfall clauseA proposed promise by AI companies to give away a large share of any enormous profits they make if their AI transforms the economy, so that the gains are widely shared.
woke AIA politically charged label, used mainly by US conservatives, for AI systems seen as building progressive views into their answers. Since 2025 it also names a US rule on which AI the government may buy.
World AI Cooperation OrganizationAn international organization for cooperation on AI, based in Shanghai, set up in 2026 by an agreement among 29 countries on China's initiative.

Also relevant

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advanced driver-assistance systemCar features that help the driver but do not replace them, such as automatic emergency braking, lane-keeping help, adaptive cruise control and blind-spot warnings.
advanced packagingWays of joining several chips very closely inside one package — side by side on a silicon base or stacked on top of each other — so they act almost like one bigger chip.
agent identityThe ways of proving which AI agent is acting, for whom and with what permissions — so websites, companies and other agents can tell trustworthy agents from impostors and hold someone responsible.
agentic AIAI built to pursue goals on its own — planning, taking actions and adjusting along the way — instead of only responding to one prompt at a time. 'Agentic' describes how much of this independence a system has.
Agentic AI FoundationA nonprofit group under the Linux Foundation that looks after shared, open technical standards for AI agents, such as the Model Context Protocol, so that no single company controls them.
agentic commerceShopping and payments carried out by AI agents for people — finding products, comparing offers and completing purchases — within limits the person has approved.
AI acceleratorAny chip built or tuned to speed up AI — graphics chips, Google's TPUs, phone 'neural engines' and many startup designs. Such chips do the heavy math of training and running models.
AI arms raceA competition among countries or companies to build the most powerful AI first, in which fear of falling behind pushes everyone to move faster and cut corners on safety.
AI as normal technologyThe view that AI, however important, will change society gradually, like electricity or the internet, through slow adoption by people and institutions, rather than as a sudden, uncontrollable superintelligence.
AI bug bountyA program in which an AI company pays outside researchers for reporting flaws in its AI systems — security holes, ways around safety rules, or biased behavior — so that they can be fixed.
AI colonialismThe criticism that the AI industry repeats patterns of colonial empires, taking data, labor, land and resources from poorer places and peoples while profits and control stay with a few rich companies and countries.
AI data centerA building or campus packed with AI chips, power equipment and cooling, built to train and run AI models. The biggest use as much electricity as a city.
AI ethicsThe study of what is right and wrong in how AI is built and used: who it may harm, who is responsible when it fails, and which values it should respect.
AI factoryA data center built to turn electricity and data into AI models and AI answers at industrial scale; in Europe, also a public supercomputing hub that helps companies and researchers build AI.
AI for goodUsing AI to tackle social and environmental problems, such as disease, poverty, disasters or climate change, rather than only to make a profit.
AI incidentA real-world case in which an AI system, through a flaw, a breakdown or the way someone used it, ends up hurting people, property or rights, as in an injury, a wrongful arrest or a privacy breach.
AI literacyKnowing enough about AI to use it sensibly and judge it critically: what it can and cannot do, how it goes wrong, and how it affects people.
AI modelThe trained core of an AI: a large file of learned numbers plus the recipe for using them, which turns an input such as a question or a photo into an output.
AI Now InstituteA research and advocacy group that examines who is harmed by AI and argues that the deeper problem is the power of a few big technology companies, which it wants curbed by law.
AI pauseA proposed halt, temporary or indefinite, on building AI systems more powerful than today's, to give safety research and regulation time to catch up.
AI personhoodThe idea of treating an AI system as a 'person' in law or ethics, with rights or duties of its own — for example, to own property, to be sued, or not to be deleted.
AI riskThe ways AI could cause harm: people misusing it on purpose, systems behaving in ways nobody intended, and slower effects on jobs, power and society that no single person causes.
AI safetyThe effort to keep AI from doing serious harm, whether because it pursues aims its makers never intended, is turned to bad uses or simply malfunctions — a concern that grows as systems become more capable.
AI securityProtecting AI systems — their data, models and surrounding software — from being attacked, stolen or tricked, and dealing with the ways AI itself can be used to attack others.
AI supercomputerA huge network of AI chips — often tens or hundreds of thousands — wired together in a data center to train the largest AI models.
AI surveillanceUsing AI to watch, identify, track or profile people on a scale no team of humans could manage, for example by scanning camera feeds or analyzing phone and online data.
AI systemA complete piece of technology that uses AI to do something, such as screening loan applications, driving a car or chatting with customers, including the AI model and the software around it.
AI transparencyOpenness about AI: telling people when they are dealing with one, how a system was built and tested, and why it reached a particular decision.
AI washingFalsely claiming that a product or company uses AI, or exaggerating how much it does, to look more advanced and attract customers or investors.
AI watermarkingHiding an invisible signal in AI-generated text, images, audio or video so that software can later tell the content was made by AI — like a banknote's watermark, but undetectable to the eye.
AI-enabled coupA seizure of power by a small group that uses advanced AI to bypass the soldiers, officials and workers whose cooperation power grabs normally need.
AI-enabled cyberattackA computer attack in which criminals or spies use AI to help — writing convincing scam messages, finding weak spots, producing malicious code, or even running much of the hacking by itself.
algorithmic managementWhen software, rather than a human manager, assigns work, sets pay, tracks performance and even disciplines or fires workers, as in ride-hailing, delivery and warehouse jobs.
algorithmic recourseGiving a person who received an unfavorable automated decision a realistic set of actions they could take to get a better result next time, such as paying down a particular debt.
alignment taxThe price of caution in AI: whatever performance, money or time a developer sacrifices to make a system safe and aligned, compared with an otherwise identical system built with no such care.
ALPAC reportA 1966 US government report that concluded machine translation was slower, worse and costlier than human translators. It ended most American funding for the field for many years.
artificial intelligenceComputer systems that do things we would normally credit to a thinking mind, such as holding a conversation, reading an X-ray or planning a route, and the field of research that builds them.
Leopold AschenbrennerA German-born former OpenAI researcher whose 2024 essay series 'Situational Awareness' predicted human-level AI around 2027 and a government-led race to build superintelligence.
Asilomar AI PrinciplesA list of 23 guidelines for safe and beneficial AI drawn up at a 2017 conference in California and signed by thousands of researchers and public figures.
ASMLA Dutch maker of the giant machines that print circuit patterns onto chips. It alone can build the extreme-ultraviolet models on which today's most advanced chips, including AI chips, depend.
autonomous vehicleA vehicle, usually a car, truck or shuttle, that can drive itself, sensing the road, deciding what to do and steering, braking and accelerating with no human driving.
autonomyHow much an AI system can act on its own without a person approving each step, from merely making suggestions to carrying out long tasks with no supervision at all.
biosecurityProtecting people from the deliberate or careless spread of dangerous germs and toxins; in AI, making sure AI tools do not make it easier to create or release biological weapons.
black boxA system whose inner workings are hidden or too complex to understand: we can see what goes in and what comes out, but not why it gave a particular answer.
Books3A collection of nearly 200,000 pirated e-books, assembled in 2020 and used to train several AI language models, which became central to lawsuits by authors over AI training.
C2PAAn industry group, and the technical standard it publishes, for attaching tamper-evident records of origin and editing history to digital photos, video, audio and documents.
capabilitySomething an AI system is able to do, such as writing working code or solving math problems, and how well. Measuring capabilities is how researchers track progress and spot dangerous skills.
CBRN riskThe danger that AI could help someone make or use chemical, biological, radiological or nuclear weapons — for example, by explaining hard technical steps an attacker could not work out alone.
Center for AI SafetyA San Francisco nonprofit that studies how advanced AI could lead to disaster and how to prevent it. In 2023 it gathered signatures for a one-sentence warning that AI could threaten human extinction.
Center for Security and Emerging TechnologyA Georgetown University think tank in Washington, D.C., whose researchers advise the US government on AI and national security, paying special attention to China and to the chip supply chain.
Centre for the Governance of AIA research organization, based in Britain, that studies how governments and companies should handle the dangers of advanced AI and the large economic and political changes it could cause.
Clearview AIA US company that collected billions of photos from the internet without permission to build a face-search tool for police, the best-known example of controversial facial recognition.
Common CrawlA nonprofit's free archive of the public web, begun in 2008 and now refreshed with snapshots of billions of pages every month or two. Most large language models learned much of what they know from text taken from it.
COMPASCommercial software used in parts of the US justice system to rate how likely someone is to commit another crime; a 2016 news investigation asking whether it was unfair to Black defendants made it famous.
computeThe raw computing power used to train and run AI, usually measured by how many specialized chips are used and for how long. With data and algorithms, it is a main driver of AI progress.
concentration of powerThe worry that AI will put enormous economic, political or military power in the hands of a few companies, governments or individuals, beyond the reach of ordinary checks and balances.
Content CredentialsA tamper-evident 'nutrition label' attached to a photo, video or document recording where it came from — which camera or AI tool made it and how it was edited — that anyone can inspect.
content moderationChecking what people post, or what an AI produces, and removing, limiting or labeling whatever breaks the rules or the law — done by people, by AI, or by both together.
contextual integrityA way of thinking about privacy: information is not simply public or private; what matters is whether it flows in ways that fit the expectations of the setting where it was shared.
counterfactual explanationAn explanation that tells someone the smallest change that would have produced a different outcome — for example, that the application would have been accepted if it had listed two more years of work experience.
Kate CrawfordAn Australian scholar who studies the social, political and environmental costs of AI, co-founded the AI Now Institute, and wrote 'Atlas of AI'.
dark patternA trick in the design of an app, website or chatbot that nudges you into doing something you didn't mean to, like signing up for a subscription that is hard to cancel.
DARPAThe US military's research-funding agency, which paid for much of the early development of artificial intelligence and the internet and runs prize competitions such as driverless-car races.
DARPA Grand ChallengeA series of US government-sponsored races for driverless vehicles held in 2004, 2005 and 2007. No robot finished the first race; within three years, cars were navigating mock city traffic.
data attributionWorking out which training examples were responsible for a particular behavior or answer of an AI model — useful for explaining, debugging and crediting the data behind it.
data licensingThe legal permissions that say who may use a dataset or a body of content, for what purposes and on what terms — including whether it may be used to train AI.
data provenanceThe documented history of a piece of data: where it came from, who created and changed it, under what permissions, and how it was processed before reaching an AI system.
data qualityHow well a set of data does its job: whether it is accurate, complete, up to date, consistent and representative — and, for AI training, informative enough to teach useful skills.
datasheet for datasetsA standard document that travels with a dataset, describing why it was made, what is in it, how it was collected and labeled, and what it should and should not be used for.
decisive strategic advantageA lead in technology and power so large that whoever holds it, whether a country, a company or an AI, could impose its will on the whole world.
DeepSeek momentThe shock of January 2025, when a little-known Chinese company released a free AI model nearly as good as the best American ones at a fraction of the reported cost, briefly wiping hundreds of billions off chip stocks.
defense in depthProtecting against AI risks with several independent layers of safeguards, so that if one fails — say, the model's own training — another, such as a filter or human review, still catches the problem.
differential technological developmentA strategy of speeding up technologies that make us safer and slowing down risky ones, so that protections arrive before the dangers they guard against.
digital divideThe gap between people, places or countries that have good access to digital technology, and the skills to use it, and those that do not; AI may widen it.
disparate impactWhen a rule or system that treats everyone alike on paper still lands much harder on one group, such as women or older workers; the law can forbid this even if no one intended it.
droneAn aircraft that carries no one aboard to fly it: a person steers it from the ground, or its own software does. Small camera-carrying quadcopters are the most familiar kind.
dual-useDescribes technology or knowledge that can be used both to help and to harm: the same AI that finds software bugs for defenders can find them for attackers.
effective computeA way of measuring AI progress that counts better methods as if they were extra computing power: if a new technique lets a model match one trained with twice the computing, it counts as doubling effective compute.
equal opportunityA fairness test that asks whether people who truly deserve a yes (who would repay the loan or succeed in the job) get one at the same rate in every group.
ethics washingUsing talk of ethics, such as principles, advisory boards or pledges, to look responsible and head off regulation, without actually changing what a company does.
excessive agencyGiving an AI system more power than its job needs — too many tools, too-broad permissions or too little human sign-off — so that a mistake or a trick can do real damage.
existential riskA danger that could end humanity, or shut it out of a good future forever. Some experts count advanced AI among the largest such risks; others think this worry is overblown.
explainabilityHow well the reasons behind an AI system's outputs can be put into terms that people can understand, check and, if needed, challenge.
explainable AIThe field and set of methods that let people understand why an AI system produced a particular output — for example, which factors led it to reject a loan application.
extreme ultraviolet lithographyThe chip-printing technique used for the most advanced chips, which draws circuit patterns with ultra-short-wavelength light. A single Dutch company, ASML, makes all the machines, each costing well over $100 million.
facial recognitionTechnology that identifies or checks who someone is by comparing a picture of their face with stored photos, used by phones, passport gates and police databases.
Fifth Generation Computer Systems projectJapan's government-backed effort, from 1982 to 1992, to build a new kind of computer that reasons with logic using many processors at once. It fell short, but it alarmed other countries into launching AI programs of their own.
FLOPA single arithmetic step, such as multiplying or adding two numbers. Counting them measures how much computing went into an AI model, and laws use such counts to decide which models face extra rules.
foundation modelA very large AI model, built once at great cost from vast amounts of text, images or code gathered mostly from the internet, that many products then reuse as their starting point, from chatbots to coding tools.
frontier labOne of the handful of companies building the most advanced AI models of the moment, spending billions of dollars on computing power to train them.
frontier modelOne of the most capable AI models in existence at a given time, built by a handful of leading labs at great cost, and the main target of AI safety rules.
Future of Life InstituteAn advocacy group that warns about the dangers of advanced AI and other powerful technologies, funds research and lobbies governments. It organized the 2023 open letter calling for a pause on giant AI experiments.
game theoryThe mathematics of strategic decisions, where each player's best move depends on what the others do. It is used to study competition and cooperation among people, firms, nations and AI agents.
general-purpose AIAI that can do a wide range of different tasks, like writing, coding, translating and analyzing images, rather than the one job it was built for. Today's chatbots are the main example.
global catastrophic riskA risk of disaster big enough to badly damage human civilization worldwide, such as killing a large share of humanity, even if humanity eventually recovers.
guaranteed safe AIA proposed approach to AI safety in which systems come with mathematical proofs or checkable guarantees that they will not cause certain harms, instead of relying on testing alone.
guardrailsSafety checks built around an AI system — filters on what goes in and comes out, and limits on what it may do — to keep it from producing harmful or off-topic content or leaking data.
H100Nvidia's flagship AI chip of 2022–2024, so scarce and sought-after during the generative-AI boom that it became a unit of measure for AI computing power.
Dan HendrycksAn American AI-safety researcher who created widely used AI tests such as MMLU and Humanity's Last Exam, and who runs the Center for AI Safety.
HuaweiA Chinese technology giant, known for telecom equipment and phones, that designs China's leading homegrown AI chips despite US trade restrictions.
human-in-the-loopDescribes AI systems in which a person checks, corrects or approves the machine's work at key points, rather than letting it act entirely on its own.
influence operationAn organized, often secret campaign to sway public opinion — fake accounts posting propaganda, for instance — which AI can make cheaper by writing posts, translating them and inventing fake personas.
intelligence curseThe worry that once AI can do most jobs, governments and companies will no longer need ordinary people and so will stop looking after them, like oil-rich states that neglect their citizens.
internal deploymentWhen an AI company uses its own newest, unreleased AI systems inside the company — for example to write code or do research — before or instead of offering them to the public.
k-anonymityA rule for anonymizing tables of personal data: blur details such as age and postcode until every person matches at least k others, so no one can be singled out.
kill switchA way to quickly shut down an AI system, or halt its development, if it starts behaving dangerously — anything from an off button to a company's promise to stop.
Daniel KokotajloAn American AI forecaster and former OpenAI researcher who led 'AI 2027', a detailed scenario of a race to superintelligence, and campaigns for transparency at AI companies.
levels of autonomyLadders that grade how independently an AI system acts — from a tool a person fully controls, through suggesting and asking for approval, up to acting on its own while people merely watch.
levels of driving automationA six-step scale, from Level 0 to Level 5, describing how much of the driving a car's automation does and how much the human must still watch the road and be ready to take over.
liar's dividendThe advantage dishonest people gain once everyone knows fakes are easy to make: they can wave away real evidence against them by claiming it was made by AI.
Lighthill reportA 1973 review written for a British government research council that judged AI research to have fallen far short of its promises. It led to deep cuts in AI funding in the United Kingdom.
loss of controlA situation in which people can no longer oversee, correct or switch off an AI system, and have no reliable way of getting that power back.
machine unlearningErasing specific things a trained AI model has learned, such as dangerous lab techniques, a copyrighted novel or one person's records, far more cheaply than training the model all over again.
Magnifica HumanitasPope Leo XIV's 2026 letter to the Catholic Church and the world about artificial intelligence, arguing that AI must serve human dignity and the common good.
misusePeople deliberately using AI to cause harm — for scams, harassment, propaganda, hacking or weapons — as opposed to harm from AI making mistakes or pursuing goals of its own.
MITRE ATLASA free online reference from the US nonprofit MITRE that maps, step by step, how attackers go after AI systems, with examples drawn from real attacks and security tests.
model cardA short document published with an AI model explaining what it is for, how it was trained and tested, how well it works for different groups of people, and its known limits.
model extractionCopying an AI model without permission by asking it huge numbers of questions and using the answers to build a look-alike, or to work out hidden details of how it was made.
model fingerprintingWays to recognize a particular AI model — to prove that a copy was taken from it, or to tell which model is behind a product — from its internal makeup or its behavior.
model licenseThe legal terms under which an AI model may be downloaded and used — for example, whether businesses may use it, whether changes may be shared, and which uses are banned.
model specificationA public document in which an AI company spells out how its models are supposed to behave — what they should do, refuse and prioritize, and whom to obey when instructions conflict.
model weight securityProtecting the files that make up a trained AI model — its learned numbers — from being stolen or leaked, because whoever holds them can run, copy or alter the model.
MolochA name, borrowed from an ancient god of sacrifice, for situations where competition forces everyone to act against their shared interests — as when AI companies feel pushed to race ahead despite the risks.
moral crumple zoneWhen a largely automated system goes wrong and the human who was supposed to supervise it gets blamed, even though they had little real say; named after the car part that soaks up a crash.
multipolar scenarioA possible future in which many powerful AIs, companies or countries coexist and compete, with none able to dominate the rest.
Mutual Assured AI MalfunctionA proposed deterrence strategy in which any country racing for overwhelming AI dominance would expect rivals to sabotage its AI projects, so none tries, much as with nuclear deterrence.
Nash equilibriumA stable standoff in a game: each player's choice is already their best answer to what the others are doing, so nobody gains by changing course alone — though the result need not be good for anyone.
non-consensual intimate imagerySexual or nude images of a real person that are shared, or made, without their consent — including fakes created with AI that show someone undressed or in sexual scenes.
nudification appAn app or AI tool that takes an ordinary photo of a real person and fakes a nude or sexual image of them, almost always without their consent.
Open Letter on Artificial IntelligenceA 2015 open letter, signed by Stephen Hawking, Elon Musk and many leading AI researchers, urging that AI research aim not only at making systems more capable but also at making them safe and beneficial.
Open Source InitiativeA nonprofit group that decides what counts as 'open source' software and, in 2024, published a definition of what makes an AI system genuinely open source.
OpenAI leadership crisis (2023)The five days in November 2023 when OpenAI's board fired chief executive Sam Altman, nearly all staff threatened to quit, and he returned with a new board.
open-source AIAI released, ideally with its code and details of its training data and not just the finished model, so that anyone may use, inspect, alter, share and even rebuild it. How open is open enough is debated.
open-weight modelAn AI model whose trained internal numbers are published for anyone to download and run on their own computers, even if the data and code used to make it stay private.
operational design domainThe specific conditions an automated vehicle or robot is designed to work in, such as particular roads, speeds, weather and times of day, outside of which it must not operate on its own.
opt-outA way for creators, websites or individuals to say 'do not use my work or data to train AI' — instead of being asked for permission first, which would be opt-in.
OWASP Top 10 for LLM ApplicationsA widely used checklist, written by volunteer security experts, of the ten most serious security risks in software built on AI language models, with advice on preventing each one.
Partnership on AIA forum, set up by big technology companies in 2016 and later joined by universities, charities and news organizations, that drafts voluntary guidelines for building and using AI responsibly.
Pause Giant AI ExperimentsA 2023 open letter, signed by tens of thousands of people including prominent technologists, that asked AI labs to halt the training of any AI more capable than GPT-4 for at least half a year.
PauseAIA volunteer protest movement, begun in 2023, that pickets AI companies and lobbies governments for a worldwide treaty halting work on AI more advanced than today's best until it is proven safe.
personally identifiable informationInformation that can identify a specific person, such as a name, address, phone number or ID number — or several facts that together point to one person.
personhood credentialA digital pass that lets you prove online that you are a real human, not an AI or a bot, without having to reveal who you are.
pivotal actA single decisive action, usually imagined as carried out with an early powerful AI, that would stop anyone else from building dangerous AI and so change the world's long-term course.
policyAn AI agent's strategy: the rule it follows to pick an action in each situation. Training in reinforcement learning means improving this rule until it earns high rewards.
pre-deployment testingChecking a new AI model for dangerous abilities and bad behavior before it is released to the public, sometimes with outside experts or government testers given early access.
predictive AIAI used to forecast outcomes about people or events, such as who will repay a loan, which patient may get sicker or which machine will fail, in order to guide decisions.
predictive policingUsing computer programs to forecast where crimes are likely to happen, or who is likely to be involved, so that police can decide where to patrol or whom to watch.
privacyYour ability to control who knows what about you. AI raises new privacy questions because it learns from huge amounts of personal data and can infer things about people they never shared.
privacy budgetThe total amount of privacy risk a data holder agrees to spend; each analysis or release uses up part of it, and once it is gone, no more answers can be given safely.
privacy-preserving machine learningThe family of techniques for training and using AI models while keeping the underlying personal or confidential data hidden — from adding careful noise to computing on encrypted data.
process nodeThe label for a generation of chip-making technology, like '3 nanometer'. Smaller numbers mean newer, denser chips, but the number no longer measures any actual part of the chip.
Project GlasswingAn Anthropic program, launched in 2026, that gave a hacking-capable AI model only to organizations defending important software instead of releasing it to everyone.
proprietary modelAn AI model kept private by the company that made it; outsiders can use it only through the company's apps or paid online services and can never download it.
protected attributeA personal trait, such as race, sex, religion, age or disability, that the law says must not be used to treat people unfairly.
proxy discriminationDiscrimination that happens when a system cannot see a trait like race directly but relies on something closely linked to it, such as a postcode, and so treats groups unequally anyway.
RAND CorporationAn American research organization, long funded mainly by the US government, where early AI programs were written and which now advises governments on AI and security.
remote attestationA way for a computer to prove to someone far away exactly what software it is running, using a signature built into its hardware, so they can decide whether to trust it.
responsibility gapThe problem that when an AI system that learns or acts on its own causes harm, it may be unclear whether anyone (its makers, users or operators) can fairly be held responsible.
responsible AIAn umbrella name for the practices organizations use to keep their AI systems fair, safe, private and accountable, from the first design meeting to everyday use.
reverse acquihireA deal in which a big tech company hires a start-up's founders and top staff and pays to license its technology, without buying the company itself.
robotaxiA taxi with no human driver: you summon it with a phone app, and a self-driving car picks you up and drives you to your destination.
robots.txtA small public file in which a website posts its rules for automated visitors, such as search-engine and AI crawlers, listing areas they are asked to stay out of. Obeying it is voluntary.
Stuart RussellA British computer scientist who co-wrote the standard AI textbook and argues that AI must be redesigned to stay uncertain about what humans want, so that it remains under human control.
safety caseA written, evidence-backed argument that a particular AI system is safe enough for a particular use, putting the burden of proof on the developer, as with nuclear plants or aircraft.
sandbaggingWhen an AI deliberately performs worse than it can — for example on a safety test — so that it seems less capable or less dangerous than it really is.
semiconductor foundryA factory company that manufactures chips designed by other companies. Taiwan's TSMC, the largest, makes nearly all of the world's most advanced AI chips.
singletonA possible future world run by a single decision-maker at the top, such as one government, one alliance or one AI, with no rival able to challenge it.
Situational Awareness (essay)A long 2024 essay by a former OpenAI researcher arguing that AGI could arrive around 2027, that superintelligence could follow soon after, and that the US government should run a national AGI project.
small AICheap, compact AI tools built for one practical job — like advising farmers or screening patients — that poorer countries can afford to run, instead of giant all-purpose models.
speaker verificationChecking whether a voice really belongs to the person it claims to be, as when a bank confirms your identity by the sound of your voice on the phone.
staged deploymentReleasing a new AI system step by step — first to testers, then to limited groups, then widely — so that problems can be spotted and fixed before everyone has it.
Strategic Computing InitiativeA billion-dollar US defense research program, run from 1983 to 1993, that tried to build machine intelligence for military uses such as self-driving vehicles and assistants for fighter pilots.
structured accessLetting people use an AI system through a controlled channel, such as a website or programming interface, instead of handing over the model itself, so that the developer can limit misuse.
Mustafa SuleymanA British entrepreneur who co-founded DeepMind and Inflection AI, leads Microsoft's effort to build its own advanced AI models, and has written about the difficulty of containing powerful AI.
superintelligenceA mind, usually imagined as an AI, that would leave even the cleverest people far behind in nearly every kind of thinking, not just in one game or skill. None is known to exist.
surveillance capitalismA business model in which companies collect huge amounts of data about people's behavior and use it to predict and influence what they will do, mainly to sell advertising.
system cardA public report released with an AI model that explains what it can do, how it was tested for safety, what risks were found and what protections were put in place.
Max TegmarkA Swedish-American physicist at MIT who co-founded the Future of Life Institute, which organized the 2023 open letter calling for a pause in training the most powerful AI systems.
training computeThe total number of arithmetic operations performed to train a model. It is the standard yardstick for the size of an AI training effort, and some laws use it to decide which models face extra rules.
training dataThe examples an AI system learns from. Whatever patterns, skills, gaps and biases are in the training data tend to show up in the finished system.
trustworthy AIAI that deserves people's trust because it works reliably, obeys the law, treats people fairly and can be checked, rather than AI that people merely happen to trust.
TSMCThe Taiwanese company that manufactures most of the world's advanced computer chips, including nearly all of the specialized chips used to train and run AI.
universal basic incomeA regular cash payment from the government to every adult, with no conditions attached, sometimes proposed as a way to share wealth if AI takes over much paid work.
usage policyA company's published rules on what people may and may not use its AI for — for example, no help building weapons, no scams and no sexual content involving children.
value lock-inThe possibility that powerful AI could freeze one set of values or one power structure in place for an extremely long time, so that later generations could never change course.
vibe portingUsing AI coding agents to translate a whole software project into another programming language, usually checking the result against the original project's tests.
vulnerable world hypothesisThe idea that some future invention could make mass destruction so easy that civilization would be wrecked by default, unless it had unusually strong ways of preventing misuse.
warning shotAn AI accident or near-miss serious enough to alarm the world about AI's dangers, but not so serious that it cannot be recovered from, which could prompt action before a real catastrophe.
web scrapingUsing software to automatically copy information from websites — text, prices, images — in bulk, which is how much of the data used to train AI was gathered.
weight exfiltrationCopying an AI model's core files out of the place they are supposed to stay — by hackers, by an insider or, in a scenario researchers worry about, by the AI itself.
weightsThe learned numbers inside a neural network that set how strongly each part influences the next. The finished set of weights is, in effect, the trained model itself.