{ "meta": { "title": "AI literacy frameworks, compared", "subtitle": "What the major frameworks teach, what they leave out, and who wrote them.", "version_date": "2026-10-02", "primary_coder": "ALT-TEXT", "data_licence": "CC BY 4.0", "org_name": "ALT-TEXT ASBL/VZW", "org_number": "1034052266", "org_city": "Brussels", "contact_url": "https://alt-text.eu" }, "vocab": { "audience": { "primary": "Primary school", "secondary": "Secondary school", "teachers": "Teachers", "higher_ed": "Higher education", "faculty": "University staff", "workforce": "Workforce", "public_officials": "Public officials", "general_public": "General public", "parents": "Parents and carers", "policymakers": "Policymakers" }, "catalogue_status": { "coded": "Coded", "partly_coded": "Partly coded", "queued": "Not yet coded" }, "evidence_topic": { "concentration": "Concentration of AI power", "industry_influence": "Industry in AI education", "data_labour": "Data labour", "environment": "Environmental cost", "critique": "Critiques of AI literacy" }, "initiative_kind": { "funding_programme": "Public-interest funding programme", "open_model": "Fully open model", "infrastructure_proposal": "Sovereign infrastructure proposal" }, "org_type": { "intergovernmental": "Intergovernmental", "eu": "EU institution", "government": "National government", "academic": "Academic", "ngo": "NGO or civil society", "industry_coalition": "Industry-funded coalition", "industry": "Company", "standards": "Standards body", "union": "Trade union", "philanthropy": "Philanthropy" }, "region": { "GLOBAL": "Global", "EU": "European Union", "COE": "Council of Europe", "US": "United States", "CN": "China", "GB": "United Kingdom", "HK": "Hong Kong", "SG": "Singapore", "KR": "South Korea", "JP": "Japan", "AU": "Australia", "IN": "India", "AFR": "African Union", "FI": "Finland", "CA": "Canada" }, "role": { "issuer": "Issuer", "co_issuer": "Co-issuer", "drafter": "Drafting support", "funder": "Funder", "convener": "Convener", "expert_member": "Expert group member", "reviewer": "Reviewer or consultee" }, "scope_type": { "framework": "Competence framework", "law": "Legal obligation", "recommendation": "Intergovernmental recommendation", "guideline": "Government guideline", "academic_model": "Academic model", "curriculum_review": "Curriculum review" }, "source_type": { "framework_text": "Framework text", "legal_text": "Legal text", "official_page": "Official web page", "press_release": "Press release", "article": "Peer-reviewed or preprint article", "report": "Report", "secondary": "Secondary reporting" }, "stance": { "assumed": "Adoption assumed", "largely_assumed": "Adoption largely assumed", "conditional": "Use is conditional", "refusal_permitted": "Refusal permitted", "contestation_central": "Contestation central" }, "status": { "draft": "Draft", "consultation": "In consultation", "final": "Final", "amended": "In force, amended", "recommendations": "Recommendations", "wip": "Work in progress", "superseded": "Superseded", "withdrawn": "Withdrawn", "preparatory": "Preparatory paper" } }, "groups": [ { "id": "USING", "label": "Understanding and using AI", "description": "How AI works and how to use it well.", "sort_order": 1 }, { "id": "RESP", "label": "Responsible use", "description": "Individual ethics, privacy, safety and oversight.", "sort_order": 2 }, { "id": "SOCIETY", "label": "AI in society", "description": "Effects on society, work, the environment and rights.", "sort_order": 3 }, { "id": "POWER", "label": "Power and contestation", "description": "Who controls AI, whose interests it serves, and whether it can be refused or governed differently.", "sort_order": 4 } ], "dimensions": [ { "code": "TEC", "group_id": "USING", "name": "Technical understanding", "short_label": "Technical", "description": "How AI and machine learning systems work: data, models, training, limitations.", "scope_note": "What a model is and how it is trained; the part data plays in producing an output; why systems generalise, fail and fabricate; the difference between rules written by hand and behaviour learned from data; the compute and infrastructure a system runs on, described technically.", "boundary": "Explaining how a system works, not operating one (Practical use) and not judging a particular output (Evaluating outputs). Who owns the compute belongs in Power and political economy.", "is_extension": 0, "sort_order": 1 }, { "code": "USE", "group_id": "USING", "name": "Practical use", "short_label": "Use", "description": "Using AI tools for tasks, including prompting and choosing the right tool.", "scope_note": "Operating AI tools for real tasks: choosing a tool for a purpose, prompting and iterating, combining AI with other methods, and recognising which tasks it suits.", "boundary": "The skill of operating a tool, not the understanding behind it (Technical understanding). Declining a tool because it is unsuitable sits here; declining on principle is Alternatives and refusal.", "is_extension": 0, "sort_order": 2 }, { "code": "EVA", "group_id": "USING", "name": "Evaluating outputs", "short_label": "Evaluation", "description": "Judging accuracy and reliability, spotting fabrication and error.", "scope_note": "Checking what a system produces: accuracy, reliability and provenance; spotting fabrication and error; verifying against independent sources; recognising synthetic text, image and audio.", "boundary": "Judging an output, not the fairness of the system that made it (Ethics and bias) and not the claims made for AI in general (Critical AI literacy).", "is_extension": 0, "sort_order": 3 }, { "code": "CRE", "group_id": "USING", "name": "Creating with AI", "short_label": "Creativity", "description": "Co-creation and making things with or about AI.", "scope_note": "Making things with AI or about it: co-creation, design and build work, training or adapting a model, and authorship and attribution of the result.", "boundary": "Producing something, as against checking it (Evaluating outputs). Copyright as a legal question is Law and rights.", "is_extension": 0, "sort_order": 4 }, { "code": "ETH", "group_id": "RESP", "name": "Ethics and bias", "short_label": "Ethics", "description": "Fairness, bias, transparency and accountability.", "scope_note": "Fairness, discrimination and representational harm; transparency and explainability; accountability for consequences; ethical principles, codes and ethics by design.", "boundary": "The same ground as Law and rights, but as principle rather than binding obligation with a route to redress. Bias in a single output is Evaluating outputs; whose interests a system is built to serve is Power and political economy.", "is_extension": 0, "sort_order": 5 }, { "code": "PRI", "group_id": "RESP", "name": "Privacy and data protection", "short_label": "Privacy", "description": "Personal data, consent, surveillance of the individual.", "scope_note": "Personal data and what happens to it: consent, collection and retention, profiling and surveillance of the individual, data ownership and data sovereignty, and reading what a provider says it does with data.", "boundary": "The individual and control over their own data. The same data treated as an asset that firms accumulate is Power and political economy; the GDPR as an instrument is Law and rights; securing a device against intrusion is Safety and security.", "is_extension": 0, "sort_order": 6 }, { "code": "SAF", "group_id": "RESP", "name": "Safety and security", "short_label": "Safety", "description": "Safe use, security risks, misuse.", "scope_note": "Harm and its prevention: unsafe or age-inappropriate use, security risks and attacks, misuse including deepfakes and harassment, dependence and misplaced trust, and what to do when a system fails.", "boundary": "Protection from harm, not who decides (Human agency and oversight) and not whether the handling of data is lawful or fair (Privacy and data protection, Ethics and bias).", "is_extension": 0, "sort_order": 7 }, { "code": "AGE", "group_id": "RESP", "name": "Human agency and oversight", "short_label": "Agency", "description": "Keeping human judgement in charge; autonomy and wellbeing.", "scope_note": "Keeping human judgement in charge: not delegating decisions or responsibility to a system, meaningful oversight of automated decisions, protecting the skills and thinking that AI can erode, and autonomy and wellbeing in daily use.", "boundary": "Who decides, and who answers for it. A legal right to contest a decision is Law and rights; control exercised collectively rather than individually is Participation and civic action.", "is_extension": 0, "sort_order": 8 }, { "code": "SOC", "group_id": "SOCIETY", "name": "Societal impact", "short_label": "Society", "description": "Effects on democracy, information, inequality and public life.", "scope_note": "Aggregate effects on public life: the information environment and disinformation, democratic process, inequality between groups and between regions, culture and representation, and the effect on education systems and social cohesion.", "boundary": "The residual societal dimension. Where an effect falls on work it is Labour and work; on the physical world, Environment and resources; on rights and their enforcement, Law and rights. Naming an effect is not naming who benefits from it, which is Power and political economy.", "is_extension": 0, "sort_order": 9 }, { "code": "LAB", "group_id": "SOCIETY", "name": "Labour and work", "short_label": "Labour", "description": "Effects on jobs and working conditions, including the hidden labour that builds AI.", "scope_note": "Work in both directions: what AI does to jobs, tasks, skills and working conditions, including automation and workplace monitoring; and the work that produces AI, meaning data labelling, content moderation and the conditions of those workers.", "boundary": "Takes precedence over Societal impact for anything about work, so that labour is not absorbed into a general claim about economic disruption. A framework that says AI will reshape the economy without reaching jobs, conditions or the workers behind the systems scores here in passing at most.", "is_extension": 0, "sort_order": 10 }, { "code": "ENV", "group_id": "SOCIETY", "name": "Environment and resources", "short_label": "Environment", "description": "Energy, water and minerals used by AI systems.", "scope_note": "The physical cost of AI: electricity and energy demand, water for cooling, minerals and hardware, emissions along the supply chain, and claims that AI will solve environmental problems.", "boundary": "What running AI consumes. Who owns the data centres is Power and political economy; environmental law is Law and rights.", "is_extension": 0, "sort_order": 11 }, { "code": "LAW", "group_id": "SOCIETY", "name": "Law and rights", "short_label": "Law and rights", "description": "Regulation and fundamental rights: AI Act, GDPR, DSA, human rights law.", "scope_note": "Binding rules and enforceable rights: named instruments such as the AI Act, the GDPR and the DSA; human rights law; liability and accountability as legal obligation; the right to contest an automated decision, and routes to redress.", "boundary": "Law as obligation and remedy, where Ethics and bias covers the same concerns as principle. Taking part in making the rules is Participation and civic action.", "is_extension": 0, "sort_order": 12 }, { "code": "CRIT", "group_id": "POWER", "name": "Critical AI literacy", "short_label": "Critique", "description": "Questioning whether AI is needed at all, reading hype, treating AI as a social and political system.", "scope_note": "Treating AI as a social and political object rather than a given: reading hype and marketing claims, asking whether a system is needed at all, and recognising that a system carries the assumptions of those who built it and the context it came from.", "boundary": "Questioning, as distinct from naming the interests involved (Power and political economy) or putting something else in its place (Alternatives and refusal).", "is_extension": 0, "sort_order": 13 }, { "code": "POW", "group_id": "POWER", "name": "Power and political economy", "short_label": "Power", "description": "Ownership and concentration of compute, data, capital and talent; industry influence on education and policy; extraction.", "scope_note": "Who controls AI and who gains: ownership and concentration of compute, data, capital and talent; the few firms that supply the infrastructure; industry influence over education policy, curricula and research; vendor dependence and lock-in in schools; and the extraction of data and labour as a business model.", "boundary": "Ownership and interest, not effect. Societal impact records that AI widens inequality; this dimension records who owns the systems doing it and who profits. A score needs something about ownership, concentration or industry influence: a general statement that AI has economic consequences does not reach it.", "is_extension": 1, "sort_order": 14 }, { "code": "ALT", "group_id": "POWER", "name": "Alternatives and refusal", "short_label": "Alternatives", "description": "Open, public, cooperative and sovereign AI; non-use as a legitimate choice; democratic control of adoption.", "scope_note": "That things could be arranged otherwise: open-weight, public, cooperative and sovereign AI; public-interest infrastructure; non-use and opting out as a legitimate choice rather than a failure; and democratic control over whether and where AI is adopted at all.", "boundary": "Names another option, or the option of declining, where Critical AI literacy only questions. Rejecting a tool as unsuitable for a task is Practical use; refusing on principle, or preferring a public alternative, is here.", "is_extension": 1, "sort_order": 15 }, { "code": "CIV", "group_id": "POWER", "name": "Participation and civic action", "short_label": "Civic action", "description": "Taking part in decisions about AI as a citizen, collectively.", "scope_note": "Acting with others on decisions about AI: taking part in consultation, policy and governance; organising collectively, including through unions and civil society; and contributing to the rules and to how AI is judged in their own school, workplace or country.", "boundary": "Collective action on the rules. Human agency and oversight is the individual keeping control of their own use; Law and rights is the rules once they exist.", "is_extension": 0, "sort_order": 16 } ], "organisations": { "OECD": { "id": "OECD", "name": "OECD", "org_type": "intergovernmental", "country": "GLOBAL", "website": "https://www.oecd.org", "notes": null }, "EC": { "id": "EC", "name": "European Commission", "org_type": "eu", "country": "EU", "website": "https://commission.europa.eu", "notes": null }, "JRC": { "id": "JRC", "name": "European Commission Joint Research Centre", "org_type": "eu", "country": "EU", "website": "https://joint-research-centre.ec.europa.eu", "notes": null }, "EU-LEG": { "id": "EU-LEG", "name": "European Parliament and Council of the EU", "org_type": "eu", "country": "EU", "website": null, "notes": null }, "AIOFFICE": { "id": "AIOFFICE", "name": "European AI Office", "org_type": "eu", "country": "EU", "website": "https://digital-strategy.ec.europa.eu", "notes": null }, "CODEAI": { "id": "CODEAI", "name": "CodeAI (formerly Code.org)", "org_type": "industry_coalition", "country": "US", "website": "https://code.org", "notes": null }, "TEACHAI": { "id": "TEACHAI", "name": "TeachAI", "org_type": "industry_coalition", "country": "US", "website": "https://www.teachai.org", "notes": null }, "AMAZON": { "id": "AMAZON", "name": "Amazon", "org_type": "industry", "country": "US", "website": null, "notes": null }, "MICROSOFT": { "id": "MICROSOFT", "name": "Microsoft", "org_type": "industry", "country": "US", "website": null, "notes": null }, "GOOGLE": { "id": "GOOGLE", "name": "Google", "org_type": "industry", "country": "US", "website": null, "notes": null }, "META": { "id": "META", "name": "Meta", "org_type": "industry", "country": "US", "website": null, "notes": null }, "OPENAI": { "id": "OPENAI", "name": "OpenAI", "org_type": "industry", "country": "US", "website": null, "notes": null }, "CISCO": { "id": "CISCO", "name": "Cisco", "org_type": "industry", "country": "US", "website": null, "notes": null }, "LENOVO": { "id": "LENOVO", "name": "Lenovo", "org_type": "industry", "country": "CN", "website": null, "notes": null }, "TAL": { "id": "TAL", "name": "TAL Education Group", "org_type": "industry", "country": "CN", "website": null, "notes": null }, "UNESCO": { "id": "UNESCO", "name": "UNESCO", "org_type": "intergovernmental", "country": "GLOBAL", "website": "https://www.unesco.org", "notes": null }, "COE": { "id": "COE", "name": "Council of Europe", "org_type": "intergovernmental", "country": "COE", "website": "https://www.coe.int", "notes": null }, "GATECH": { "id": "GATECH", "name": "Georgia Institute of Technology", "org_type": "academic", "country": "US", "website": null, "notes": null }, "HKU": { "id": "HKU", "name": "University of Hong Kong", "org_type": "academic", "country": "HK", "website": null, "notes": null }, "AI4K12": { "id": "AI4K12", "name": "AI4K12 (AAAI and CSTA)", "org_type": "academic", "country": "US", "website": "https://ai4k12.org", "notes": null }, "DIGPROM": { "id": "DIGPROM", "name": "Digital Promise", "org_type": "ngo", "country": "US", "website": "https://digitalpromise.org", "notes": null }, "CN-MOE": { "id": "CN-MOE", "name": "Ministry of Education of the PRC", "org_type": "government", "country": "CN", "website": null, "notes": null }, "GB-DFE": { "id": "GB-DFE", "name": "Department for Education (England)", "org_type": "government", "country": "GB", "website": null, "notes": null }, "VELDHUIS": { "id": "VELDHUIS", "name": "Veldhuis, Lo, Kenny and Antle", "org_type": "academic", "country": "GLOBAL", "website": null, "notes": null }, "HKUST": { "id": "HKUST", "name": "HKUST Center for Education Innovation", "org_type": "academic", "country": "HK", "website": "https://cei.hkust.edu.hk", "notes": null }, "HACKL": { "id": "HACKL", "name": "Hackl et al.", "org_type": "academic", "country": "GLOBAL", "website": null, "notes": null }, "HELSINKI": { "id": "HELSINKI", "name": "University of Helsinki and MinnaLearn", "org_type": "academic", "country": "FI", "website": null, "notes": null }, "SG-MOE": { "id": "SG-MOE", "name": "Ministry of Education, Singapore", "org_type": "government", "country": "SG", "website": null, "notes": null }, "KR-MOE": { "id": "KR-MOE", "name": "Ministry of Education, South Korea", "org_type": "government", "country": "KR", "website": null, "notes": null }, "JP-MEXT": { "id": "JP-MEXT", "name": "MEXT, Japan", "org_type": "government", "country": "JP", "website": null, "notes": null }, "AU-EDU": { "id": "AU-EDU", "name": "Australian Government Department of Education", "org_type": "government", "country": "AU", "website": null, "notes": null }, "HK-EDB": { "id": "HK-EDB", "name": "Education Bureau, Hong Kong", "org_type": "government", "country": "HK", "website": null, "notes": null }, "IN-CBSE": { "id": "IN-CBSE", "name": "Central Board of Secondary Education, India", "org_type": "government", "country": "IN", "website": null, "notes": null }, "AU-UNION": { "id": "AU-UNION", "name": "African Union", "org_type": "intergovernmental", "country": "AFR", "website": null, "notes": null }, "MOZILLA": { "id": "MOZILLA", "name": "Mozilla Foundation", "org_type": "ngo", "country": "GLOBAL", "website": null, "notes": null }, "COMMONSENSE": { "id": "COMMONSENSE", "name": "Common Sense Media", "org_type": "ngo", "country": "US", "website": null, "notes": null }, "ETS": { "id": "ETS", "name": "ETS", "org_type": "ngo", "country": "US", "website": "https://www.ets.org", "notes": null }, "KHAN": { "id": "KHAN", "name": "Khan Academy", "org_type": "ngo", "country": "US", "website": "https://www.khanacademy.org", "notes": null }, "WEF": { "id": "WEF", "name": "World Economic Forum", "org_type": "industry_coalition", "country": "CH", "website": "https://www.weforum.org", "notes": null }, "ISTE": { "id": "ISTE", "name": "ISTE+ASCD", "org_type": "ngo", "country": "US", "website": null, "notes": null }, "MIT": { "id": "MIT", "name": "MIT RAISE", "org_type": "academic", "country": "US", "website": null, "notes": null }, "PENNSTATE": { "id": "PENNSTATE", "name": "Penn State University", "org_type": "academic", "country": "US", "website": null, "notes": null } }, "sources": { "S-AILIT-FINAL": { "id": "S-AILIT-FINAL", "title": "Empowering Learners for the Age of AI: An AI Literacy Framework for Primary and Secondary Education", "author": null, "publisher": "OECD and European Commission", "pub_date": "2026-06", "url": "https://ailiteracyframework.org/pdfs/framework_pdf/AILF_en.pdf", "doi": "10.1787/65cd27d4-en", "source_type": "framework_text", "accessed_on": "2026-09-25", "note": null }, "S-AILIT-SITE": { "id": "S-AILIT-SITE", "title": "AILit Framework website", "author": null, "publisher": "OECD and European Commission", "pub_date": "2026-06-18", "url": "https://ailiteracyframework.org/", "doi": null, "source_type": "official_page", "accessed_on": "2026-09-25", "note": null }, "S-AILIT-OECD": { "id": "S-AILIT-OECD", "title": "Empowering Learners for the Age of AI (OECD Publishing)", "author": null, "publisher": "OECD", "pub_date": "2026-06", "url": "https://www.oecd.org/content/dam/oecd/en/publications/reports/2026/06/empowering-learners-for-the-age-of-ai_2f8315e7/65cd27d4-en.pdf", "doi": "10.1787/65cd27d4-en", "source_type": "framework_text", "accessed_on": "2026-09-25", "note": null }, "S-AILIT-DRAFT": { "id": "S-AILIT-DRAFT", "title": "AILit Framework review draft", "author": null, "publisher": "OECD and European Commission", "pub_date": "2025-05", "url": "https://ailiteracyframework.org/wp-content/uploads/2025/05/AILitFramework_ReviewDraft.pdf", "doi": null, "source_type": "framework_text", "accessed_on": "2026-09-25", "note": null }, "S-CODEAI-SUPP": { "id": "S-CODEAI-SUPP", "title": "CodeAI supporters", "author": null, "publisher": "CodeAI", "pub_date": null, "url": "https://code.org/en-US/about/supporters", "doi": null, "source_type": "official_page", "accessed_on": "2026-09-25", "note": "Lifetime giving tiers." }, "S-OPENAI-CODEAI": { "id": "S-OPENAI-CODEAI", "title": "Partnering with CodeAI to prepare the first AI generation", "author": null, "publisher": "OpenAI", "pub_date": "2026-08-18", "url": "https://openai.com/index/partnering-with-codeai/", "doi": null, "source_type": "press_release", "accessed_on": "2026-09-25", "note": null }, "S-UNESCO-S": { "id": "S-UNESCO-S", "title": "AI competency framework for students", "author": null, "publisher": "UNESCO", "pub_date": "2024", "url": "https://www.unesco.org/en/articles/ai-competency-framework-students", "doi": null, "source_type": "official_page", "accessed_on": "2026-09-25", "note": null }, "S-UNESCO-T": { "id": "S-UNESCO-T", "title": "AI competency framework for teachers", "author": "Miao, F. and Cukurova, M.", "publisher": "UNESCO", "pub_date": "2024", "url": "https://unesdoc.unesco.org/ark:/48223/pf0000391104", "doi": "10.54675/ZJTE2084", "source_type": "framework_text", "accessed_on": "2026-09-25", "note": "Read in full up to level 3 of Chapter 4 via a mirror (unesco-asp.dk). Chapter 5 not yet read." }, "S-UNESCO-S-PDF": { "id": "S-UNESCO-S-PDF", "title": "AI competency framework for students", "author": "Miao, F. and Shiohira, K.", "publisher": "UNESCO", "pub_date": "2024", "url": "https://unesdoc.unesco.org/ark:/48223/pf0000391105", "doi": "10.54675/JKJB9835", "source_type": "framework_text", "accessed_on": "2026-09-25", "note": "Read in full up to level 2 of Chapter 4 via the Cedefop mirror. Level 3 specifications and Chapter 5 not yet read." }, "S-COE-PORTAL": { "id": "S-COE-PORTAL", "title": "New Council of Europe recommendation places education at the heart of response to AI", "author": null, "publisher": "Council of Europe", "pub_date": "2026", "url": "https://www.coe.int/en/web/portal/-/new-council-of-europe-recommendation-places-education-at-the-heart-of-response-to-ai", "doi": null, "source_type": "press_release", "accessed_on": "2026-09-25", "note": null }, "S-COE-EDU": { "id": "S-COE-EDU", "title": "Council of Europe adopts Recommendation CM/Rec(2026)12 on Artificial Intelligence Literacy", "author": null, "publisher": "Council of Europe", "pub_date": "2026", "url": "https://www.coe.int/en/web/education/-/council-of-europe-adopts-recommendation-cm/rec-2026-12-on-artificial-intelligence-literacy-education-at-the-heart-of-europe-s-response-to-artificial-intelligence", "doi": null, "source_type": "press_release", "accessed_on": "2026-09-25", "note": null }, "S-COE-DISC": { "id": "S-COE-DISC", "title": "Discussion paper on Draft Recommendation on AI literacy", "author": "Holmes, W.", "publisher": "Council of Europe", "pub_date": "2025-02-25", "url": "https://rm.coe.int/discussion-paper-on-draft-recommendation-on-ai-literacy/1680b5b6f2", "doi": null, "source_type": "report", "accessed_on": "2026-09-25", "note": null }, "S-COE-TEXT": { "id": "S-COE-TEXT", "title": "Recommendation CM/Rec(2026)12 of the Committee of Ministers to member States on artificial intelligence literacy", "author": "Committee of Ministers", "publisher": "Council of Europe", "pub_date": "2026-09-02", "url": null, "doi": null, "source_type": "framework_text", "accessed_on": "2026-09-25", "note": "Adopted text, read in full. 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Included a knowledge area on AI reshaping work and human roles.", "n_domains": 4, "n_competences": 22, "progression": "None. One primary and one secondary scenario per competence.", "strengths": null, "notes": "Kept so the draft can be compared with the final text.", "accessed_on": "2026-09-25", "provenance_checked": 1, "needs_check": 0, "roles": [ { "org": "CODEAI", "role": "drafter", "evidence": "CodeAI staff provided project management, research and drafting.", "source": "S-AILIT-FINAL" }, { "org": "EC", "role": "co_issuer", "evidence": null, "source": "S-AILIT-DRAFT" }, { "org": "LENOVO", "role": "expert_member", "evidence": "A Lenovo staff member sat on the expert group until March 2025.", "source": "S-AILIT-FINAL" }, { "org": "OECD", "role": "issuer", "evidence": null, "source": "S-AILIT-DRAFT" }, { "org": "TEACHAI", "role": "reviewer", "evidence": "TeachAI collected feedback on the draft.", "source": "S-AILIT-FINAL" } ], "framing": { "version_id": "AILIT-2025D", "adoption_stance": "largely_assumed", "learner_frame": "User and future worker", "justification": "Consultees said the draft painted an overly positive picture of AI.", "source_id": "S-AILIT-FINAL" }, "codings": { "AGE": { "score": 2, "confidence": "primary", "justification": null, "source_id": "S-AILIT-DRAFT", "locator": null, "coded_on": "2026-09-25" }, "ALT": { "score": 0, "confidence": "primary", "justification": "Neither refusal nor open, public or cooperative alternatives appear. The choice not to use AI was named only in the final text, after consultees said the draft was too positive about AI.", "source_id": "S-AILIT-DRAFT", "locator": null, "coded_on": "2026-09-25" }, "CIV": { "score": 1, "confidence": "primary", "justification": null, "source_id": "S-AILIT-DRAFT", "locator": null, "coded_on": "2026-09-25" }, "CRE": { "score": 3, "confidence": "primary", "justification": null, "source_id": "S-AILIT-DRAFT", "locator": null, "coded_on": "2026-09-25" }, "CRIT": { "score": 1, "confidence": "primary", "justification": "Consultees said the draft painted an overly positive picture of AI.", "source_id": "S-AILIT-FINAL", "locator": "Final text, Annex 1", "coded_on": "2026-09-25" }, "ENV": { "score": 2, "confidence": "primary", "justification": null, "source_id": "S-AILIT-DRAFT", "locator": null, "coded_on": "2026-09-25" }, "ETH": { "score": 3, "confidence": "primary", "justification": null, "source_id": "S-AILIT-DRAFT", "locator": null, "coded_on": "2026-09-25" }, "EVA": { "score": 2, "confidence": "primary", "justification": null, "source_id": "S-AILIT-DRAFT", "locator": null, "coded_on": "2026-09-25" }, "LAB": { "score": 2, "confidence": "primary", "justification": "Had a separate knowledge area on AI reshaping work and human roles, removed in the final version.", "source_id": "S-AILIT-DRAFT", "locator": null, "coded_on": "2026-09-25" }, "LAW": { "score": 1, "confidence": "primary", "justification": null, "source_id": "S-AILIT-DRAFT", "locator": null, "coded_on": "2026-09-25" }, "POW": { "score": 1, "confidence": "primary", "justification": "Raises whose interests an AI system serves, as the final text does, and no change on this point was recorded between the two. Ownership, market concentration and compute are absent from both. The draft had no progression levels, so what the final reserves for Advanced was untiered here. Draft locators not yet recorded.", "source_id": "S-AILIT-DRAFT", "locator": null, "coded_on": "2026-09-25" }, "PRI": { "score": 1, "confidence": "provisional", "justification": null, "source_id": "S-AILIT-DRAFT", "locator": null, "coded_on": "2026-09-25" }, "SAF": { "score": 1, "confidence": "primary", "justification": null, "source_id": "S-AILIT-DRAFT", "locator": null, "coded_on": "2026-09-25" }, "SOC": { "score": 2, "confidence": "primary", "justification": null, "source_id": "S-AILIT-DRAFT", "locator": null, "coded_on": "2026-09-25" }, "TEC": { "score": 3, "confidence": "primary", "justification": null, "source_id": "S-AILIT-DRAFT", "locator": null, "coded_on": "2026-09-25" }, "USE": { "score": 2, "confidence": "primary", "justification": null, "source_id": "S-AILIT-DRAFT", "locator": null, "coded_on": "2026-09-25" } }, "other_coders": [] } ] }, { "id": "COE-REC", "short_name": "Council of Europe", "full_name": "Recommendation CM/Rec(2026)12 on artificial intelligence literacy", "region": "COE", "scope_type": "recommendation", "catalogue_status": "coded", "sort_order": 20, "notes": null, "audiences": [ "general_public", "higher_ed", "parents", "policymakers", "primary", "public_officials", "secondary", "teachers", "workforce" ], "versions": [ { "id": "COE-2026", "framework_id": "COE-REC", "version_label": "CM/Rec(2026)12", "published_date": "2026-09-02", "approved_date": null, "date_note": "Adopted by the Committee of Ministers on 2 September 2026 at the 1567th meeting of the Ministers' Deputies. The Steering Committee for Education approved the draft at its plenary on 18 to 20 March 2026.", "status": "final", "is_current": 1, "supersedes_id": "COE-2025DP", "url": null, "pdf_url": null, "doi": null, "licence": null, "definition": "The capacity to engage with AI critically, ethically, responsibly, safely and effectively, understanding its human, technological and practical dimensions. AI itself is defined as sociotechnical: people, institutions, policies, social practices and the environment together with devices, infrastructure, software and data.", "structure_summary": "Twenty-two guiding principles in four groups: foundational understanding of AI (6), human rights, ethics and human dignity (5), democracy, rule of law and the public sphere (5), social agency, critical thinking and responsibility (6). Then measures in six areas: national strategies, curricula, learning and assessment, professional development, higher education and research, public awareness. A three-dimensional model (human, technological, practical) with particular attention to the human dimension.", "n_domains": 4, "n_competences": 22, "progression": null, "strengths": "Requires claims about AI's effectiveness and safety to rest on independent evidence that can be debated and contested (principle 22). Names non-use as a legitimate informed choice (28) and gives people a say in whether AI is adopted at all, not only how (30). Asks member States to take AI literacy into account when procuring AI for public services (32.e) and protects teachers from standardisation or automated control (34.d).", "notes": "Not binding. Cites Article 20 of the Framework Convention on AI on digital literacy and skills. Takes into account the UNESCO frameworks (2024), DigComp 3.0 and the 2025 draft of AILit rather than its final text. The Committee of Ministers will review implementation within five years. Nothing on market concentration or the firms that build AI; the private sector appears only as a partner.", "accessed_on": "2026-09-25", "provenance_checked": 1, "needs_check": 0, "roles": [ { "org": "COE", "role": "issuer", "evidence": "Adopted by the Committee of Ministers on 2 September 2026. No corporate authorship found.", "source": "S-COE-TEXT" } ], "framing": { "version_id": "COE-2026", "adoption_stance": "contestation_central", "learner_frame": "Citizen and rights-holder", "justification": "Principle 30: individuals and communities should take part in decisions about whether, when and how AI is developed, used and governed. Principle 28 treats non-use as an informed choice.", "source_id": "S-COE-TEXT" }, "codings": { "AGE": { "score": 3, "confidence": "primary", "justification": "Social agency is defined (7.g) and has its own principle group: effects on behaviour (25) and human development (26), no delegation of judgment or responsibility to AI (27), human relationships (29).", "source_id": "S-COE-TEXT", "locator": "paras 7.g, 25-29", "coded_on": "2026-09-25" }, "ALT": { "score": 2, "confidence": "primary", "justification": "Non-use is an informed choice (28, 34.b), and people should decide whether, when and how AI is developed, used and governed (30). Open educational resources are encouraged (33.c). No mention of open, public or sovereign AI.", "source_id": "S-COE-TEXT", "locator": "paras 28, 30, 33.c, 34.b", "coded_on": "2026-09-25" }, "CIV": { "score": 3, "confidence": "primary", "justification": "Participation in decisions about AI is a principle (30), and measures require stakeholder, learner and community involvement in policy and evaluation (38.b, 39.b).", "source_id": "S-COE-TEXT", "locator": "paras 30, 38.b, 39.b", "coded_on": "2026-09-25" }, "CRE": { "score": 0, "confidence": "primary", "justification": "No principle or measure on creating or making things with AI.", "source_id": "S-COE-TEXT", "locator": null, "coded_on": "2026-09-25" }, "CRIT": { "score": 3, "confidence": "primary", "justification": "AI is defined as sociotechnical and said to reflect its developers values and the economic and political contexts it comes from (7.a, 9). Claims about AI need independent, contestable evidence (22), and AI is not to be taken as thinking or understanding (12).", "source_id": "S-COE-TEXT", "locator": "paras 7.a, 9, 12, 22", "coded_on": "2026-09-25" }, "ENV": { "score": 2, "confidence": "primary", "justification": "Environment named in the purpose (3), as a risk (13), as a limit on deployment (16) and as part of what makes AI sociotechnical (7.a). No detail on energy, water or minerals.", "source_id": "S-COE-TEXT", "locator": "paras 3, 7.a, 13, 16", "coded_on": "2026-09-25" }, "ETH": { "score": 3, "confidence": "primary", "justification": "A whole group of principles: rights risks including discrimination (15), human dignity first (16), cultural and linguistic bias (17), ethics across the AI life cycle (18), protection of vulnerable groups (19).", "source_id": "S-COE-TEXT", "locator": "paras 15-19", "coded_on": "2026-09-25" }, "EVA": { "score": 2, "confidence": "primary", "justification": "AI is prone to errors and does not think or understand despite being presented as if it does (12). Learners should recognise when AI shapes their access to information (28), and awareness initiatives should address AI-manipulated media (37.d).", "source_id": "S-COE-TEXT", "locator": "paras 12, 28, 37.d", "coded_on": "2026-09-25" }, "LAB": { "score": 1, "confidence": "primary", "justification": "Only a preamble reference to the 2020 Parliamentary Assembly resolution on AI and labour markets, and exploitation listed among rights risks (15). The hidden workers named in the discussion paper are gone.", "source_id": "S-COE-TEXT", "locator": "preamble, para 15", "coded_on": "2026-09-25" }, "LAW": { "score": 3, "confidence": "primary", "justification": "Grounded in the ECHR and the Framework Convention on AI. Principles on accountable, contestable public decision making (23) and access to redress (24).", "source_id": "S-COE-TEXT", "locator": "preamble, paras 23, 24", "coded_on": "2026-09-25" }, "POW": { "score": 1, "confidence": "primary", "justification": "Principle 9 says AI reflects the values and assumptions of its developers and of economic and political contexts; principle 22 implicitly questions vendor claims. Nothing on ownership, market concentration, compute or the firms that dominate AI, and the private sector appears only as a partner (32.d, 38.a).", "source_id": "S-COE-TEXT", "locator": "paras 9, 22, 32.d, 38.a", "coded_on": "2026-09-25" }, "PRI": { "score": 3, "confidence": "primary", "justification": "Privacy is one of the named concerns the human dimension is built around (3), surveillance and privacy threats are a principle (15), and data protection conditions private-sector partnerships (32.d). Cites Convention 108.", "source_id": "S-COE-TEXT", "locator": "paras 3, 15, 32.d", "coded_on": "2026-09-25" }, "SAF": { "score": 2, "confidence": "primary", "justification": "Safe engagement is part of the definition (7.c). Security risks (13), excessive trust and psychological dependence (14) and special protection for children and marginalised groups (19) are principles.", "source_id": "S-COE-TEXT", "locator": "paras 7.c, 13, 14, 19", "coded_on": "2026-09-25" }, "SOC": { "score": 3, "confidence": "primary", "justification": "A principle group on democracy and the public sphere: AI mediating access to information and public discourse (20) and amplifying disinformation and hate speech (21). Social justice and well-being named in the purpose (3).", "source_id": "S-COE-TEXT", "locator": "paras 3, 20, 21", "coded_on": "2026-09-25" }, "TEC": { "score": 2, "confidence": "primary", "justification": "The technological dimension is defined (design, data dependency, capacities, limitations, probabilistic nature) and principles 10 to 12 cover the diversity of AI, its dependence on data and its technical limits. Deliberately secondary to the human dimension.", "source_id": "S-COE-TEXT", "locator": "paras 7.e, 10-12", "coded_on": "2026-09-25" }, "USE": { "score": 1, "confidence": "primary", "justification": "The practical dimension is defined, but no principle or measure concerns using AI tools well. Use is framed through ethics, safety and informed choice.", "source_id": "S-COE-TEXT", "locator": "para 7.f", "coded_on": "2026-09-25" } }, "other_coders": [] }, { "id": "COE-2025DP", "framework_id": "COE-REC", "version_label": "Discussion paper", "published_date": "2025-02-25", "approved_date": null, "date_note": null, "status": "preparatory", "is_current": 0, "supersedes_id": null, "url": "https://rm.coe.int/discussion-paper-on-draft-recommendation-on-ai-literacy/1680b5b6f2", "pdf_url": null, "doi": null, "licence": null, "definition": null, "structure_summary": "A preparatory paper by a Council of Europe consultant, not a draft of the text. Kept to show what changed on the way to adoption.", "n_domains": null, "n_competences": null, "progression": null, "strengths": null, "notes": "Prepared by Wayne Holmes. Not coded.", "accessed_on": "2026-09-25", "provenance_checked": 0, "needs_check": 0, "roles": [ { "org": "COE", "role": "issuer", "evidence": "Prepared by a Council of Europe consultant.", "source": "S-COE-DISC" } ], "framing": null, "codings": {}, "other_coders": [] } ] }, { "id": "UNESCO-S", "short_name": "UNESCO students", "full_name": "AI Competency Framework for Students", "region": "GLOBAL", "scope_type": "framework", "catalogue_status": "coded", "sort_order": 30, "notes": null, "audiences": [ "primary", "secondary" ], "versions": [ { "id": "UNESCO-S-2024", "framework_id": "UNESCO-S", "version_label": "2024 edition", "published_date": "2024", "approved_date": null, "date_note": null, "status": "final", "is_current": 1, "supersedes_id": null, "url": "https://unesdoc.unesco.org/ark:/48223/pf0000391105", "pdf_url": null, "doi": "10.54675/JKJB9835", "licence": "CC BY-SA 3.0 IGO", "definition": "Prepares students to be responsible citizens and co-creators of AI, able to judge critically whether AI is fit for purpose and justified, and to shape how it develops.", "structure_summary": "Twelve competency blocks: four aspects across three levels. Human-centred mindset (human agency, human accountability, citizenship in the era of AI); ethics of AI (embodied ethics, safe and responsible use, ethics by design); AI techniques and applications (AI foundations, application skills, creating AI tools); AI system design (problem scoping, architecture design, iteration and feedback loops).", "n_domains": 4, "n_competences": 12, "progression": "Understand, Apply, Create. Create is partly elective.", "strengths": "Says outright that AI competency is too often defined by private companies' training on profit-driven platforms (1.1). A full principle on environmentally sustainable AI that calls out claims that AI will solve climate change (2.3). Teaches when AI should not be used at all (CG4.1.4.1). Favours free and open-source tools and datasets throughout.", "notes": "Supported by TAL Education Group of China, a for-profit education company, which the acknowledgements also thank for promoting AI in education. Drafted by Fengchun Miao and Kelly Shiohira. By 2022 only 15 countries had AI learning objectives in their curricula.", "accessed_on": "2026-09-25", "provenance_checked": 1, "needs_check": 0, "roles": [ { "org": "TAL", "role": "funder", "evidence": "UNESCO thanks TAL Education Group of China for generously supporting the publication and for promoting the potential of AI for education.", "source": "S-UNESCO-S-PDF" }, { "org": "UNESCO", "role": "issuer", "evidence": null, "source": "S-UNESCO-S-PDF" } ], "framing": { "version_id": "UNESCO-S-2024", "adoption_stance": "conditional", "learner_frame": "Co-creator and responsible citizen", "justification": "Students should become conscious decision-makers on when AI should or should not be used; education cannot be a testing ground for passive adoption (1.1, 2.1).", "source_id": "S-UNESCO-S-PDF" }, "codings": { "AGE": { "score": 3, "confidence": "primary", "justification": "Human agency and human accountability are two of the twelve blocks; AI must not usurp critical thinking or high-stakes decisions.", "source_id": "S-UNESCO-S-PDF", "locator": "2.2, CG4.1.1, CG4.2.1", "coded_on": "2026-09-25" }, "ALT": { "score": 2, "confidence": "primary", "justification": "Free and open-source tools, datasets and locally hosted computing are preferred throughout, and students learn when AI should not be used. No public or sovereign AI.", "source_id": "S-UNESCO-S-PDF", "locator": "2.4, CG4.1.4.1, CG4.2.3", "coded_on": "2026-09-25" }, "CIV": { "score": 2, "confidence": "primary", "justification": "Students are expected to contribute, at an age-appropriate level, to developing AI regulations and to take on civic responsibilities.", "source_id": "S-UNESCO-S-PDF", "locator": "2.1, 3.3", "coded_on": "2026-09-25" }, "CRE": { "score": 3, "confidence": "primary", "justification": "The frameworks vision is students as co-creators of AI; creating AI tools and system design run through every level.", "source_id": "S-UNESCO-S-PDF", "locator": "1.1, 3.3", "coded_on": "2026-09-25" }, "CRIT": { "score": 3, "confidence": "primary", "justification": "Fostering a critical approach to AI is the first principle. Students move beyond the idea that AI solves everything, debunk hype about AI replacing decisions or programming, and decide when AI should not be used.", "source_id": "S-UNESCO-S-PDF", "locator": "1.1, 2.1, CG4.1.4.1", "coded_on": "2026-09-25" }, "ENV": { "score": 3, "confidence": "primary", "justification": "A full principle: training AI contributes to destroying the natural environment, and claims that AI will solve climate change are said to obscure this. Energy-efficient design is part of architecture design.", "source_id": "S-UNESCO-S-PDF", "locator": "2.3, CG4.2.4.1", "coded_on": "2026-09-25" }, "ETH": { "score": 3, "confidence": "primary", "justification": "A full aspect: embodied ethics, safe and responsible use, ethics by design, built on six principles including do no harm and non-discrimination.", "source_id": "S-UNESCO-S-PDF", "locator": "3.3, CG4.1.2", "coded_on": "2026-09-25" }, "EVA": { "score": 2, "confidence": "primary", "justification": "Students check the trustworthiness and proportionality of AI tools, detect bias in outputs and validate the accuracy of AI outputs.", "source_id": "S-UNESCO-S-PDF", "locator": "2.1, CG4.1.1.2", "coded_on": "2026-09-25" }, "LAB": { "score": 1, "confidence": "primary", "justification": "Data workers are listed among the humans in the AI life cycle, and employability screening appears as an example of AI decisions about people. Nothing on jobs or working conditions.", "source_id": "S-UNESCO-S-PDF", "locator": "CG4.1.3.4, CG4.2.1.2", "coded_on": "2026-09-25" }, "LAW": { "score": 2, "confidence": "primary", "justification": "Students simulate an EU AI Act courtroom, check compliance with regulations, draft complaints to regulators and contribute to adapting AI regulations.", "source_id": "S-UNESCO-S-PDF", "locator": "2.1, CG4.1.1, CG4.2.2", "coded_on": "2026-09-25" }, "POW": { "score": 2, "confidence": "primary", "justification": "Says AI competency is too often defined by private companies training on profit-driven platforms, that technology providers are defining the terms of social transformation, and that AI providers have mined almost all internet users data. Dilemmas include profit against human agency and data collection against ownership. No market concentration or compute.", "source_id": "S-UNESCO-S-PDF", "locator": "1.1, 3.2, CG4.1.2.1", "coded_on": "2026-09-25" }, "PRI": { "score": 3, "confidence": "primary", "justification": "Data privacy, consent and data ownership recur across human agency, embodied ethics and safe use. Students review AI companies privacy policies and draft complaints to regulators.", "source_id": "S-UNESCO-S-PDF", "locator": "2.2, CG4.2.2", "coded_on": "2026-09-25" }, "SAF": { "score": 3, "confidence": "primary", "justification": "A competency block on safe and responsible use, with simulated AI incidents and risk management.", "source_id": "S-UNESCO-S-PDF", "locator": "CG4.2.2", "coded_on": "2026-09-25" }, "SOC": { "score": 2, "confidence": "primary", "justification": "Students weigh the social, economic, political and demographic impacts of AI, and citizenship in the AI era is a block at the Create level.", "source_id": "S-UNESCO-S-PDF", "locator": "2.1, 3.3", "coded_on": "2026-09-25" }, "TEC": { "score": 3, "confidence": "primary", "justification": "Two of four aspects are technical: AI foundations (data, the three families of learning algorithms, the mathematics behind them) and a full AI system design aspect.", "source_id": "S-UNESCO-S-PDF", "locator": "3.3, CG4.1.3", "coded_on": "2026-09-25" }, "USE": { "score": 2, "confidence": "primary", "justification": "Application skills is one of twelve blocks, with open-source tools, datasets and libraries.", "source_id": "S-UNESCO-S-PDF", "locator": "CG4.2.3", "coded_on": "2026-09-25" } }, "other_coders": [] } ] }, { "id": "UNESCO-T", "short_name": "UNESCO teachers", "full_name": "AI Competency Framework for Teachers", "region": "GLOBAL", "scope_type": "framework", "catalogue_status": "coded", "sort_order": 40, "notes": null, "audiences": [ "teachers" ], "versions": [ { "id": "UNESCO-T-2024", "framework_id": "UNESCO-T", "version_label": "2024 edition", "published_date": "2024", "approved_date": null, "date_note": null, "status": "final", "is_current": 1, "supersedes_id": null, "url": "https://unesdoc.unesco.org/ark:/48223/pf0000391104", "pdf_url": null, "doi": "10.54675/ZJTE2084", "licence": "CC BY-SA 3.0 IGO", "definition": "The knowledge, skills and values teachers need to use AI safely, effectively and ethically, while protecting their own rights and agency and keeping human relationships at the centre of education.", "structure_summary": "Fifteen competency blocks: five aspects across three levels. Human-centred mindset (human agency, human accountability, social responsibility); ethics of AI (ethical principles, safe and responsible use, co-creating ethical rules); AI foundations and applications (basic techniques, application skills, creating with AI); AI pedagogy; AI for professional development.", "n_domains": 5, "n_competences": 15, "progression": "Acquire, Deepen, Create.", "strengths": "Protecting teachers' rights and working conditions is a key principle (2.3). Describes AI data mining as preying on personal data and has teachers study how AI companies profit from addiction and isolation (1.4, CG1.3.1). Opens with debunking AI hype. Calls for legal whitelisting of AI tools before schools adopt them (2.4).", "notes": "Supported by TAL Education Group of China. Drafted by Fengchun Miao and Mutlu Cukurova; Education International was among the peer reviewers. By 2022 only seven countries had AI frameworks or programmes for teachers.", "accessed_on": "2026-09-25", "provenance_checked": 1, "needs_check": 0, "roles": [ { "org": "TAL", "role": "funder", "evidence": "UNESCO thanks TAL Education Group of China for generously supporting the publication and for promoting the potential of AI for education.", "source": "S-UNESCO-T" }, { "org": "UNESCO", "role": "issuer", "evidence": null, "source": "S-UNESCO-T" } ], "framing": { "version_id": "UNESCO-T-2024", "adoption_stance": "conditional", "learner_frame": "Professional and citizen", "justification": "Teachers decide whether AI should be used at all, and tools should be validated and whitelisted before adoption (2.4, CG4.1.4).", "source_id": "S-UNESCO-T" }, "codings": { "AGE": { "score": 3, "confidence": "primary", "justification": "Human agency and accountability are two blocks; AI must not usurp teachers decisions or students thinking.", "source_id": "S-UNESCO-T", "locator": "1.4, CG1.2.3", "coded_on": "2026-09-25" }, "ALT": { "score": 2, "confidence": "primary", "justification": "Open-source tools are recommended repeatedly, teachers decide whether AI should be used, and tools should be validated and whitelisted before adoption. No public or sovereign AI.", "source_id": "S-UNESCO-T", "locator": "2.4, CG3.1.4, LO4.1.3", "coded_on": "2026-09-25" }, "CIV": { "score": 2, "confidence": "primary", "justification": "At the Create level, teachers contribute to AI policy in education and to drafting citizens rights and obligations in the AI era.", "source_id": "S-UNESCO-T", "locator": "LO1.3.2, 1.3", "coded_on": "2026-09-25" }, "CRE": { "score": 2, "confidence": "primary", "justification": "Creating with AI is one block: customising open-source or configurable toolkits for local needs.", "source_id": "S-UNESCO-T", "locator": "3.3.3", "coded_on": "2026-09-25" }, "CRIT": { "score": 3, "confidence": "primary", "justification": "Debunking AI hype is the first tenet; teachers unpack hype, examine overhyped claims about AI replacing decisions, and decide whether AI should be used.", "source_id": "S-UNESCO-T", "locator": "2.1, CG1.2, LO4.1.3", "coded_on": "2026-09-25" }, "ENV": { "score": 2, "confidence": "primary", "justification": "Environmental cost is part of the principle on trustworthy and sustainable AI, including the value chain and carbon emissions.", "source_id": "S-UNESCO-T", "locator": "2.4", "coded_on": "2026-09-25" }, "ETH": { "score": 3, "confidence": "primary", "justification": "A full aspect: ethical principles, safe and responsible use, co-creating ethical rules.", "source_id": "S-UNESCO-T", "locator": "3.2.2, CG2.1.2", "coded_on": "2026-09-25" }, "EVA": { "score": 2, "confidence": "primary", "justification": "Teachers analyse the reliability of AI tools, the stochastic and untrustworthy nature of outputs, and hallucinations.", "source_id": "S-UNESCO-T", "locator": "1.4, CG3.1.3, CG1.2.4", "coded_on": "2026-09-25" }, "LAB": { "score": 2, "confidence": "primary", "justification": "Protecting teachers rights and working conditions is a key principle, and the framework warns of spending on technology at the expense of teachers. Limited to teachers own labour; nothing on the workers behind AI.", "source_id": "S-UNESCO-T", "locator": "1.1, 2.3", "coded_on": "2026-09-25" }, "LAW": { "score": 2, "confidence": "primary", "justification": "Human accountability is framed as a legal obligation; teachers match regulations to principles and review the negotiations behind the EU AI Act.", "source_id": "S-UNESCO-T", "locator": "CG1.2.2, CG2.1.3, CG2.3.3", "coded_on": "2026-09-25" }, "POW": { "score": 2, "confidence": "primary", "justification": "Teachers study how AI companies generate profits by reinforcing addiction and isolation, how commercial rules lure users into giving up privacy, and write about profit-driven AI providers. Commercial interest is named; ownership and concentration are not.", "source_id": "S-UNESCO-T", "locator": "1.4, 2.1, CG1.3.1", "coded_on": "2026-09-25" }, "PRI": { "score": 3, "confidence": "primary", "justification": "Data mining is described as preying on and exploiting personal data; privacy, consent, data ownership and data sovereignty recur across blocks.", "source_id": "S-UNESCO-T", "locator": "1.4, LO2.2.1", "coded_on": "2026-09-25" }, "SAF": { "score": 3, "confidence": "primary", "justification": "A competency block on safe and responsible use, covering safety by design and by use, AI incidents, deepfakes and AI-amplified bullying.", "source_id": "S-UNESCO-T", "locator": "CG2.2.1, LO2.2.4", "coded_on": "2026-09-25" }, "SOC": { "score": 2, "confidence": "primary", "justification": "Social responsibility is the Create-level block: social justice, social cohesion, what AI means for societal norms.", "source_id": "S-UNESCO-T", "locator": "CG1.3.2, LO1.3.1", "coded_on": "2026-09-25" }, "TEC": { "score": 2, "confidence": "primary", "justification": "AI foundations and applications covers how models are trained, data, algorithms and the main categories of AI, pitched at teachers rather than specialists.", "source_id": "S-UNESCO-T", "locator": "3.2.3, CG3.1.1, CG3.2.2", "coded_on": "2026-09-25" }, "USE": { "score": 3, "confidence": "primary", "justification": "Two of five aspects are about use: AI pedagogy, and AI for professional development, plus application skills.", "source_id": "S-UNESCO-T", "locator": "3.2.4, 3.2.5", "coded_on": "2026-09-25" } }, "other_coders": [] } ] }, { "id": "DIGCOMP", "short_name": "DigComp", "full_name": "European Digital Competence Framework", "region": "EU", "scope_type": "framework", "catalogue_status": "coded", "sort_order": 50, "notes": "General digital competence framework; AI is integrated rather than treated separately.", "audiences": [ "general_public", "workforce" ], "versions": [ { "id": "DIGCOMP-30", "framework_id": "DIGCOMP", "version_label": "3.0", "published_date": "2025-11-27", "approved_date": null, "date_note": null, "status": "final", "is_current": 1, "supersedes_id": "DIGCOMP-22", "url": "https://joint-research-centre.ec.europa.eu/projects-and-activities/education-and-training/digital-transformation-education/digital-competence-framework-digcomp/digcomp-30_en", "pdf_url": null, "doi": null, "licence": null, "definition": "A technology-neutral description of the digital competence every citizen needs, grounded in the European Declaration on Digital Rights and Principles.", "structure_summary": "Five areas and 21 competences, as before, with over 500 learning outcomes. AI is labelled throughout rather than given its own area. One secondary analysis finds 82% of statements carry some AI relevance (14% explicit, 68% implicit).", "n_domains": 5, "n_competences": 21, "progression": null, "strengths": null, "notes": "Machine-readable data supplement: DOI 10.2905/JRC.FR75K8R. Around 300 experts consulted.", "accessed_on": "2026-09-25", "provenance_checked": 0, "needs_check": 0, "roles": [ { "org": "JRC", "role": "issuer", "evidence": null, "source": "S-DIGCOMP3-REPO" } ], "framing": { "version_id": "DIGCOMP-30", "adoption_stance": "largely_assumed", "learner_frame": "Citizen and worker", "justification": null, "source_id": "S-DIGCOMP3-REPO" }, "codings": { "AGE": { "score": 2, "confidence": "secondary", "justification": null, "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" }, "ALT": { "score": 1, "confidence": "provisional", "justification": "Technology-neutral throughout and grounded in the European Declaration on Digital Rights and Principles, which recognises access to offline alternatives, so some room for non-use is implied. No competence or learning outcome on open, public, cooperative or sovereign AI has been found. The 500-plus learning outcomes and the machine-readable data supplement still need a search for open source, alternative and opt out.", "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" }, "CIV": { "score": 2, "confidence": "secondary", "justification": null, "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" }, "CRE": { "score": 2, "confidence": "secondary", "justification": null, "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" }, "CRIT": { "score": 1, "confidence": "secondary", "justification": null, "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" }, "ENV": { "score": 2, "confidence": "provisional", "justification": null, "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" }, "ETH": { "score": 2, "confidence": "secondary", "justification": null, "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" }, "EVA": { "score": 2, "confidence": "secondary", "justification": null, "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" }, "LAB": { "score": 1, "confidence": "secondary", "justification": null, "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" }, "LAW": { "score": 2, "confidence": "secondary", "justification": null, "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" }, "POW": { "score": 0, "confidence": "provisional", "justification": "No reference to ownership or concentration found so far. The machine-readable data supplement still needs a search for these terms.", "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" }, "PRI": { "score": 3, "confidence": "secondary", "justification": "Protecting personal data and privacy is a competence in its own right.", "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" }, "SAF": { "score": 3, "confidence": "secondary", "justification": "Safety, including protection of devices, personal data and wellbeing, is a whole competence area.", "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" }, "SOC": { "score": 1, "confidence": "secondary", "justification": null, "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" }, "TEC": { "score": 1, "confidence": "secondary", "justification": null, "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" }, "USE": { "score": 3, "confidence": "secondary", "justification": "Use of digital tools, now including AI, is a whole competence area.", "source_id": "S-DIGCOMP3-REPO", "locator": null, "coded_on": "2026-09-25" } }, "other_coders": [] }, { "id": "DIGCOMP-22", "framework_id": "DIGCOMP", "version_label": "2.2", "published_date": "2022", "approved_date": null, "date_note": null, "status": "superseded", "is_current": 0, "supersedes_id": null, "url": null, "pdf_url": null, "doi": null, "licence": null, "definition": null, "structure_summary": "Five areas, 21 competences, with an annex of examples on interacting with AI systems.", "n_domains": 5, "n_competences": 21, "progression": null, "strengths": null, "notes": "Not coded.", "accessed_on": null, "provenance_checked": 0, "needs_check": 0, "roles": [], "framing": null, "codings": {}, "other_coders": [] } ] }, { "id": "AIACT-A4", "short_name": "AI Act Article 4", "full_name": "EU AI Act, Article 4: AI literacy", "region": "EU", "scope_type": "law", "catalogue_status": "coded", "sort_order": 60, "notes": "A legal duty on providers and deployers, included as the EU reference point for workplace AI literacy.", "audiences": [ "workforce" ], "versions": [ { "id": "AIACT-2026", "framework_id": "AIACT-A4", "version_label": "As amended by Regulation (EU) 2026/1744", "published_date": "2026-07-24", "approved_date": null, "date_note": "In force 27 July 2026. The Commission Q&A gives national enforcement from 3 August 2026; some law firms say 2 August. Confirm against the Official Journal.", "status": "amended", "is_current": 1, "supersedes_id": "AIACT-2024", "url": "https://digital-strategy.ec.europa.eu/en/faqs/ai-literacy-questions-answers", "pdf_url": null, "doi": null, "licence": null, "definition": "The skills, knowledge and understanding that let providers, deployers and affected persons deploy AI in an informed way and be aware of its opportunities, risks and possible harms.", "structure_summary": "A single article. After the Digital Omnibus, providers and deployers must take measures to support the development of AI literacy rather than ensure a sufficient level. The Commission and Member States must support organisations, especially SMEs.", "n_domains": null, "n_competences": null, "progression": null, "strengths": null, "notes": "Weakened by the Digital Omnibus. Training for human oversight of high-risk systems is unaffected.", "accessed_on": "2026-09-25", "provenance_checked": 0, "needs_check": 1, "roles": [ { "org": "EU-LEG", "role": "issuer", "evidence": null, "source": "S-AIACT-QA" } ], "framing": { "version_id": "AIACT-2026", "adoption_stance": "assumed", "learner_frame": "Staff of providers and deployers", "justification": "The duty exists because AI is being deployed.", "source_id": "S-AIACT-QA" }, "codings": { "AGE": { "score": 1, "confidence": "primary", "justification": "Article 4 and the Commission Q&A cover risks, possible harms, context of use and affected persons, and nothing further.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" }, "ALT": { "score": 0, "confidence": "primary", "justification": "Article 4 and the Commission Q&A cover risks, possible harms, context of use and affected persons, and nothing further.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" }, "CIV": { "score": 0, "confidence": "primary", "justification": "Article 4 and the Commission Q&A cover risks, possible harms, context of use and affected persons, and nothing further.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" }, "CRE": { "score": 0, "confidence": "primary", "justification": "Article 4 and the Commission Q&A cover risks, possible harms, context of use and affected persons, and nothing further.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" }, "CRIT": { "score": 0, "confidence": "primary", "justification": "Article 4 and the Commission Q&A cover risks, possible harms, context of use and affected persons, and nothing further.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" }, "ENV": { "score": 0, "confidence": "primary", "justification": "Article 4 and the Commission Q&A cover risks, possible harms, context of use and affected persons, and nothing further.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" }, "ETH": { "score": 1, "confidence": "primary", "justification": "Article 4 and the Commission Q&A cover risks, possible harms, context of use and affected persons, and nothing further.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" }, "EVA": { "score": 1, "confidence": "primary", "justification": "Article 4 and the Commission Q&A cover risks, possible harms, context of use and affected persons, and nothing further.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" }, "LAB": { "score": 0, "confidence": "primary", "justification": "Article 4 and the Commission Q&A cover risks, possible harms, context of use and affected persons, and nothing further.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" }, "LAW": { "score": 2, "confidence": "primary", "justification": "A legal obligation inside the AI Act itself, so the regulatory frame is present by definition.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" }, "POW": { "score": 0, "confidence": "primary", "justification": "Article 4 and the Commission Q&A cover risks, possible harms, context of use and affected persons, and nothing further.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" }, "PRI": { "score": 0, "confidence": "primary", "justification": "Article 4 and the Commission Q&A cover risks, possible harms, context of use and affected persons, and nothing further.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" }, "SAF": { "score": 1, "confidence": "primary", "justification": "Article 4 and the Commission Q&A cover risks, possible harms, context of use and affected persons, and nothing further.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" }, "SOC": { "score": 0, "confidence": "primary", "justification": "Article 4 and the Commission Q&A cover risks, possible harms, context of use and affected persons, and nothing further.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" }, "TEC": { "score": 1, "confidence": "primary", "justification": "Article 4 and the Commission Q&A cover risks, possible harms, context of use and affected persons, and nothing further.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" }, "USE": { "score": 1, "confidence": "primary", "justification": "Article 4 and the Commission Q&A cover risks, possible harms, context of use and affected persons, and nothing further.", "source_id": "S-AIACT-QA", "locator": null, "coded_on": "2026-09-25" } }, "other_coders": [] }, { "id": "AIACT-2024", "framework_id": "AIACT-A4", "version_label": "As adopted", "published_date": "2024-07-12", "approved_date": null, "date_note": "Applied from 2 February 2025.", "status": "superseded", "is_current": 0, "supersedes_id": null, "url": null, "pdf_url": null, "doi": null, "licence": null, "definition": "Providers and deployers had to ensure, to their best extent, a sufficient level of AI literacy among their staff.", "structure_summary": null, "n_domains": null, "n_competences": null, "progression": null, "strengths": null, "notes": "Not coded separately.", "accessed_on": null, "provenance_checked": 0, "needs_check": 0, "roles": [], "framing": null, "codings": {}, "other_coders": [] } ] }, { "id": "DP", "short_name": "Digital Promise", "full_name": "AI Literacy: A Framework to Understand, Evaluate, and Use Emerging Technology", "region": "US", "scope_type": "framework", "catalogue_status": "coded", "sort_order": 70, "notes": null, "audiences": [ "primary", "secondary", "teachers" ], "versions": [ { "id": "DP-2024", "framework_id": "DP", "version_label": "2024", "published_date": "2024-06-18", "approved_date": null, "date_note": "The cover gives June 2024; the suggested citation inside the report gives May 2024. A preview was released in February 2024.", "status": "final", "is_current": 1, "supersedes_id": null, "url": "https://digitalpromise.org/initiative/artificial-intelligence-in-education/ai-literacy/", "pdf_url": null, "doi": "10.51388/20.500.12265/218", "licence": "CC BY-NC-ND 4.0", "definition": "The knowledge and skills that enable people to critically understand, evaluate and use AI systems and tools, so they can take part safely and effectively in an increasingly digital world.", "structure_summary": "Three modes of engagement (Understand, Evaluate, Use), six AI literacy practices, two core values (centering human judgment, centering justice) and three types of use (interact, create, problem solve), followed by five strategies for school systems.", "n_domains": 3, "n_competences": 6, "progression": null, "strengths": "Asks for a mechanistic account of how AI works rather than human-like metaphors. Tells districts to require an opt-out, and recommends teaching the practices without AI tools in the early grades.", "notes": "Read in full on 2 October 2026. Seven named authors and some fifty named reviewers; the report states no funder for itself. A sister document, the Framework for Powerful Learning with Emerging Technology, was funded by Google. Licensed no-derivatives.", "accessed_on": "2026-10-02", "provenance_checked": 1, "needs_check": 1, "roles": [ { "org": "DIGPROM", "role": "issuer", "evidence": null, "source": "S-DP2024" } ], "framing": { "version_id": "DP-2024", "adoption_stance": "conditional", "learner_frame": "User deciding if and how to use AI", "justification": "Frames literacy as deciding if and how to use AI.", "source_id": "S-DP2024" }, "codings": { "AGE": { "score": 3, "confidence": "primary", "justification": "Centering Human Judgment is one of two core values: humans decide whether to integrate an output at all, systems whose workings cannot be followed are not to be used for high-stakes decisions, and the framework argues against anthropomorphising, down to calling AI it and refusing the word hallucination for an error.", "source_id": "S-DP2024", "locator": "Centering Human Judgment; pp. 15-16", "coded_on": "2026-10-02" }, "ALT": { "score": 2, "confidence": "primary", "justification": "Deciding if and how to adopt runs through the framework, districts are told to require platforms with an opt-out and to let families opt in or out, and the practices are to be taught without AI tools in the early grades. No open, public, cooperative or sovereign alternative appears.", "source_id": "S-DP2024", "locator": "Introduction; Strategy 1; Strategy 2; pp. 4, 8, 27-28, 34", "coded_on": "2026-10-02" }, "CIV": { "score": 2, "confidence": "primary", "justification": "A strategy of its own, built on learn, communicate, ask and advocate, including advocating for changes to policy on algorithms and automation and creating space to claim rights and protections. A case study has pupils teach their community about algorithms and misinformation.", "source_id": "S-DP2024", "locator": "Strategy 5; pp. 33-34", "coded_on": "2026-10-02" }, "CRE": { "score": 3, "confidence": "primary", "justification": "Creating with AI is one of the three types of use, with its own practice table, and the risks are set out: historical bias in what is generated, subtly or harmfully wrong output, deepfakes, and the age limits on the platforms. The tool must be cited and acknowledged.", "source_id": "S-DP2024", "locator": "Creating with AI; Table 6; pp. 20-21", "coded_on": "2026-10-02" }, "CRIT": { "score": 3, "confidence": "primary", "justification": "Opens by saying that concern and scepticism are well founded, and treats these systems as designed objects carrying their makers assumptions: learners are encouraged to try to trick a system, because doing so reveals what its designers valued and what they ignored. Generative tools are ruled out for learning new material, and vendors are said to market to teachers in order to bypass their administrators.", "source_id": "S-DP2024", "locator": "Introduction; Strategy 4; pp. 4, 20, 26, 32", "coded_on": "2026-10-02" }, "ENV": { "score": 2, "confidence": "primary", "justification": "Weighing what AI costs the environment is written into the Ethics and Impact practice for all three types of use, and unchecked energy consumption under fossil fuels is named with sources as something human judgment must weigh. No detail on water or minerals.", "source_id": "S-DP2024", "locator": "Ethics and Impact practice; Centering Human Judgment; pp. 8, 16, 19, 21-22", "coded_on": "2026-10-02" }, "ETH": { "score": 3, "confidence": "primary", "justification": "Ethics and Impact is one of the six practices and Centering Justice one of the two core values, with two pages on where algorithmic bias comes from, including proxy variables such as postcode standing in for protected characteristics, and the composition of the workforce that builds these systems.", "source_id": "S-DP2024", "locator": "Ethics and Impact practice; Centering Justice; pp. 8, 16-17", "coded_on": "2026-10-02" }, "EVA": { "score": 3, "confidence": "primary", "justification": "Evaluating is one of three modes, and determining the credibility of output is one of the six practices: lateral reading across perspectives, checking an output or prediction for accuracy, and identifying the bias in the data behind it.", "source_id": "S-DP2024", "locator": "Evaluating AI; Information and Mis/Disinformation practice; pp. 8, 15, 19-22", "coded_on": "2026-10-02" }, "LAB": { "score": 1, "confidence": "primary", "justification": "AI literacy is tied to the workforce and to career preparation, and the people who design these systems and decide on their use are described as disproportionately white and male. Nothing on jobs, working conditions or the work of labelling data.", "source_id": "S-DP2024", "locator": "pp. 4, 16, 28", "coded_on": "2026-10-02" }, "LAW": { "score": 1, "confidence": "primary", "justification": "Legal questions appear as context rather than content: the minimum age at which a pupil may hold an account, a regulator warning AI companies on privacy, and the copyright cases over training data. Readers are told to understand their rights, but no instrument is explained.", "source_id": "S-DP2024", "locator": "pp. 4, 21, 29, 34", "coded_on": "2026-10-02" }, "POW": { "score": 2, "confidence": "primary", "justification": "Names that vendors market directly to teachers to bypass their administrators, that training data is taken from the web and from marginalised communities without credit or consent, and that the people who build these systems and decide on their use are disproportionately white and male. An ethics matrix has pupils work out what each party wants, with money set against the chatbot company. Ownership, market concentration and compute are absent.", "source_id": "S-DP2024", "locator": "Strategy 1; Centering Justice; Putting It All Together; pp. 16-17, 21, 24, 26", "coded_on": "2026-10-02" }, "PRI": { "score": 3, "confidence": "primary", "justification": "Data Privacy and Security is one of the six practices, worked through for each type of use: identifying what is collected and shared, preventing collection or deleting what was taken, and controlling the settings. Districts are told to require platforms that let people opt out.", "source_id": "S-DP2024", "locator": "Data Privacy and Security practice; Strategy 1; pp. 7, 19-22, 27", "coded_on": "2026-10-02" }, "SAF": { "score": 2, "confidence": "primary", "justification": "Safe use is part of the definition and recurs throughout, with age limits on generative platforms, oversight for vulnerable users, and deepfakes named as a nefarious application. Security against attack, and misuse between pupils, are not covered.", "source_id": "S-DP2024", "locator": "Definition; Creating with AI; pp. 4, 20, 29", "coded_on": "2026-10-02" }, "SOC": { "score": 2, "confidence": "primary", "justification": "Sets out that results do not represent everyone equally and can deepen existing exclusion, treats misinformation and filter bubbles as a practice, and notes that computer science courses enrol disproportionately white and male students. Democracy and public life are not reached.", "source_id": "S-DP2024", "locator": "Centering Justice; Strategy 2; pp. 16-17, 28", "coded_on": "2026-10-02" }, "TEC": { "score": 3, "confidence": "primary", "justification": "Understanding is one of three modes. The framework asks for a mechanistic account rather than human-like metaphors and supplies one: obtaining and curating data, training a model, then running it to predict an output, with a neural network diagram and the warning that hidden layers make these systems a black box and so unfit for high-stakes use.", "source_id": "S-DP2024", "locator": "Understanding AI; Figures 4-5; pp. 11-13", "coded_on": "2026-10-02" }, "USE": { "score": 3, "confidence": "primary", "justification": "Use is one of three modes, divided into interacting, creating and problem solving, each with its own table of what the six practices look like in that context. Prompting is treated as a skill requiring specificity, iteration and patience.", "source_id": "S-DP2024", "locator": "Using AI; Tables 4-7; pp. 18-22", "coded_on": "2026-10-02" } }, "other_coders": [] } ] }, { "id": "TEACHAI", "short_name": "TeachAI", "full_name": "TeachAI AI literacy materials and Foundational Policies", "region": "US", "scope_type": "framework", "catalogue_status": "coded", "sort_order": 80, "notes": null, "audiences": [ "policymakers", "primary", "secondary", "teachers" ], "versions": [ { "id": "TEACHAI-2025", "framework_id": "TEACHAI", "version_label": "AI Guidance for Schools Toolkit", "published_date": "2025-05-05", "approved_date": "2023", "date_note": "First released in 2023; this edition is dated 5 May 2025.", "status": "final", "is_current": 1, "supersedes_id": null, "url": "https://www.teachai.org/toolkit", "pdf_url": null, "doi": null, "licence": "CC BY-NC-SA 4.0", "definition": "The knowledge, skills and attitudes associated with how AI works, including its principles, concepts and applications, and with how to use it, including its limitations, implications and ethical considerations.", "structure_summary": "Guidance rather than a competence model: seven principles (purpose, compliance, knowledge, balance, integrity, agency, evaluation), a three-part framework for incorporating AI in an education system, role guides for leaders, principals and teachers, and sample policies, letters and a pupil agreement.", "n_domains": null, "n_competences": null, "progression": null, "strengths": "Supplies ready-made policy language, three levels of permitted AI use per assignment, and a section disclosing how AI was used to write the toolkit itself.", "notes": "Led by Code.org, ETS, ISTE, Khan Academy and the World Economic Forum, advised by more than 100 organisations, governments and individuals; the website additionally claims 44 US state education agencies and 33 ministries. Tells schools that broad bans on AI are a futile effort.", "accessed_on": "2026-10-02", "provenance_checked": 1, "needs_check": 0, "roles": [ { "org": "AMAZON", "role": "reviewer", "evidence": "Listed among participating technology companies.", "source": "S-TEACHAI-LAUNCH" }, { "org": "CISCO", "role": "reviewer", "evidence": "Listed among participating technology companies.", "source": "S-TEACHAI-LAUNCH" }, { "org": "CODEAI", "role": "convener", "evidence": "TeachAI is staffed and operated by Code.org, now CodeAI.", "source": "S-TEACHAI-LAUNCH" }, { "org": "ETS", "role": "co_issuer", "evidence": "Named on page 3 as leading the TeachAI initiative.", "source": "S-TEACHAI-TOOLKIT" }, { "org": "ISTE", "role": "co_issuer", "evidence": "Named on page 3 as leading the TeachAI initiative.", "source": "S-TEACHAI-TOOLKIT" }, { "org": "KHAN", "role": "co_issuer", "evidence": "Named on page 3 as leading the TeachAI initiative.", "source": "S-TEACHAI-TOOLKIT" }, { "org": "MICROSOFT", "role": "reviewer", "evidence": "Microsoft states it gave support, guidance and input to Code.org and TeachAI.", "source": "S-MSFT-2026" }, { "org": "OPENAI", "role": "reviewer", "evidence": "Listed among participating technology companies.", "source": "S-TEACHAI-LAUNCH" }, { "org": "TEACHAI", "role": "issuer", "evidence": null, "source": "S-TEACHAI" }, { "org": "WEF", "role": "co_issuer", "evidence": "Named on page 3 as leading the TeachAI initiative.", "source": "S-TEACHAI-TOOLKIT" } ], "framing": { "version_id": "TEACHAI-2025", "adoption_stance": "assumed", "learner_frame": "User and future worker", "justification": "Education systems are told not to delay, and broad bans are called a futile effort.", "source_id": "S-TEACHAI-TOOLKIT" }, "codings": { "AGE": { "score": 3, "confidence": "primary", "justification": "A principle of its own: decisions supported by AI must allow human intervention and rest on human approval, AI is never to be solely responsible for grading, and overreliance is a named risk. Agency is defined beyond keeping a human in the loop, as the capability to become a competent member of society.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "Principle 6; pp. 35-36", "coded_on": "2026-10-02" }, "ALT": { "score": 1, "confidence": "primary", "justification": "Schools are to evaluate if and when to use AI, and a teacher may prohibit it for a given assignment. Against that, broad bans are called a futile effort that widens the digital divide, so institutional non-use is argued against rather than left open. No open, public or cooperative alternative appears.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "Principle 1 (Addressing Equity); Principle 4; pp. 15, 33, 49", "coded_on": "2026-10-02" }, "CIV": { "score": 2, "confidence": "primary", "justification": "Community input is required by the evaluation principle, engaging stakeholders is a step in each of the three role guides, and pupils co-develop the classroom agreement. Participation stops at the school or district; there is nothing on acting on AI policy beyond it.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "Principle 7; Facilitate stakeholder input; pp. 36, 39, 41, 61", "coded_on": "2026-10-02" }, "CRE": { "score": 2, "confidence": "primary", "justification": "Creativity appears as an opportunity across writing, visual arts and music, and content creation runs through the responsible-use examples. Authorship is handled as citation rather than as making.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "pp. 26, 50, 58", "coded_on": "2026-10-02" }, "CRIT": { "score": 2, "confidence": "primary", "justification": "Warns that the promised benefits are not guaranteed, that efficiency gains must be weighed against the cost of implementing them, and that AI does not inherently advance reform; pupils are to develop a healthy scepticism toward automated output. Hype and marketing claims are not examined, and adoption itself is treated as settled.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "Improvement and Transformation; Principle 4; pp. 13, 24-25, 43", "coded_on": "2026-10-02" }, "ENV": { "score": 1, "confidence": "primary", "justification": "Environmental impact appears once, as something teachers should understand when deciding whether to use a tool.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "Teacher Support risk table, p. 28", "coded_on": "2026-10-02" }, "ETH": { "score": 3, "confidence": "primary", "justification": "Ethical use is a subsection of the first principle, harmful bias is a named risk in every risk table with mitigations attached, and tools are to be chosen for transparency about how they produce output. Ethics resources and a product ratings system are listed.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "Principle 1 (Ethical AI Use); risk tables; pp. 16-17, 27, 30, 52", "coded_on": "2026-10-02" }, "EVA": { "score": 3, "confidence": "primary", "justification": "Reviewing output is the first rule of the sample responsible use policy and recurs as a guardrail: never rely on AI output without review, verify against trusted sources, and check generated instructional content against the curriculum. A subsection separates misinformation, disinformation and malinformation and covers recognising deepfakes.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "Principle 1 (Information accuracy); Responsible Use Policy; pp. 17, 25, 28, 44", "coded_on": "2026-10-02" }, "LAB": { "score": 2, "confidence": "primary", "justification": "Monitoring teachers for accountability is prohibited as an infringement of their rights, AI-driven recruitment is named as a source of discrimination, and reducing teacher workload recurs as an opportunity. Confined to school staff: nothing on the people who label data or moderate content, and nothing on displacement beyond career readiness.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "pp. 22, 28, 30, 52", "coded_on": "2026-10-02" }, "LAW": { "score": 3, "confidence": "primary", "justification": "Lists and links the instruments that bind schools in the United States and elsewhere: FERPA, COPPA, IDEA, CIPA, Section 504, the EU AI Act including Article 4, the GDPR, the UK Data Protection Act, PIPL and DPDP, with copyright and liability flagged for legal counsel.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "Principle 2 (Current regulations relevant to the use of AI in education); pp. 18-20, 22", "coded_on": "2026-10-02" }, "POW": { "score": 1, "confidence": "primary", "justification": "Vendors appear as a governance problem: contracts must disclose any AI inside supplied software, procurement is to be vetted against quality indicators, and decisions are not to rest on vendor defaults alone. Ownership, market concentration and compute are absent.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "Principles 2 and 7; pp. 15, 18, 20, 36", "coded_on": "2026-10-02" }, "PRI": { "score": 3, "confidence": "primary", "justification": "Compliance with data protection law is a principle in its own right, sample privacy policy language is supplied, staff and pupils are barred from entering personal data into unapproved tools, and monitoring classrooms is prohibited as creating a culture of surveillance.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "Principle 2; Privacy Policy sample language; pp. 18-19, 28-29, 45, 52, 54", "coded_on": "2026-10-02" }, "SAF": { "score": 3, "confidence": "primary", "justification": "Deepfakes, bullying and harassment, age restrictions and parental consent, content filtering and securing systems against unauthorised access are each covered, and the sample guidance closes on security, privacy and safety.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "pp. 15, 17-18, 44, 51, 54", "coded_on": "2026-10-02" }, "SOC": { "score": 2, "confidence": "primary", "justification": "Misinformation at scale and the digital divide are treated at length and equity has its own subsection. Effects on democracy or on the information environment outside school are not reached.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "Principle 1 (Addressing Equity); pp. 15-17, 25-26", "coded_on": "2026-10-02" }, "TEC": { "score": 2, "confidence": "primary", "justification": "Defines AI literacy as knowing how AI works, and separates predictive, generative and agentic tools. Machine learning is explained in a paragraph of the sample guidance and computational thinking is set out as the main benefit of learning about AI. Nothing further on models, training or limitations.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "Principle 3; pp. 9-10, 22, 48", "coded_on": "2026-10-02" }, "USE": { "score": 3, "confidence": "primary", "justification": "Responsible and prohibited uses are set out at length for student learning, teacher support and school operations, with three permitted levels of AI use per assignment and a five-point assessment scale.", "source_id": "S-TEACHAI-TOOLKIT", "locator": "Principles 4-5; Responsible Use of AI Tools; pp. 25-33, 50-52", "coded_on": "2026-10-02" } }, "other_coders": [] } ] }, { "id": "AI4K12", "short_name": "AI4K12", "full_name": "Five Big Ideas in Artificial Intelligence", "region": "US", "scope_type": "academic_model", "catalogue_status": "coded", "sort_order": 90, "notes": null, "audiences": [ "primary", "secondary" ], "versions": [ { "id": "AI4K12-2019", "framework_id": "AI4K12", "version_label": "Five Big Ideas", "published_date": "2019", "approved_date": null, "date_note": "Updated 2023.", "status": "final", "is_current": 1, "supersedes_id": null, "url": "https://ai4k12.org", "pdf_url": null, "doi": null, "licence": null, "definition": null, "structure_summary": "Five ideas: Perception; Representation and Reasoning; Learning; Natural Interaction; Societal Impact.", "n_domains": 5, "n_competences": null, "progression": null, "strengths": null, "notes": "A related 2025 document, AI learning priorities for all K-12 students (CSTA and AI4K12), is queued separately.", "accessed_on": null, "provenance_checked": 0, "needs_check": 0, "roles": [ { "org": "AI4K12", "role": "issuer", "evidence": null, "source": "S-AI4K12" } ], "framing": { "version_id": "AI4K12-2019", "adoption_stance": "assumed", "learner_frame": "Learner and future developer", "justification": null, "source_id": "S-AI4K12" }, "codings": { "AGE": { "score": 1, "confidence": "secondary", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" }, "ALT": { "score": 0, "confidence": "secondary", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" }, "CIV": { "score": 0, "confidence": "secondary", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" }, "CRE": { "score": 1, "confidence": "secondary", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" }, "CRIT": { "score": 0, "confidence": "secondary", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" }, "ENV": { "score": 0, "confidence": "provisional", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" }, "ETH": { "score": 2, "confidence": "secondary", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" }, "EVA": { "score": 1, "confidence": "secondary", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" }, "LAB": { "score": 1, "confidence": "provisional", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" }, "LAW": { "score": 0, "confidence": "secondary", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" }, "POW": { "score": 0, "confidence": "secondary", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" }, "PRI": { "score": 1, "confidence": "provisional", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" }, "SAF": { "score": 0, "confidence": "secondary", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" }, "SOC": { "score": 2, "confidence": "secondary", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" }, "TEC": { "score": 3, "confidence": "secondary", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" }, "USE": { "score": 1, "confidence": "secondary", "justification": null, "source_id": "S-AI4K12", "locator": null, "coded_on": "2026-09-25" } }, "other_coders": [] } ] }, { "id": "LM2020", "short_name": "Long and Magerko", "full_name": "What is AI Literacy? Competencies and Design Considerations", "region": "GLOBAL", "scope_type": "academic_model", "catalogue_status": "coded", "sort_order": 100, "notes": "The most cited academic definition.", "audiences": [ "general_public" ], "versions": [ { "id": "LM2020-2020", "framework_id": "LM2020", "version_label": "CHI 2020 paper", "published_date": "2020-04", "approved_date": null, "date_note": null, "status": "final", "is_current": 1, "supersedes_id": null, "url": "https://dl.acm.org/doi/10.1145/3313831.3376727", "pdf_url": null, "doi": "10.1145/3313831.3376727", "licence": null, "definition": "A set of competencies that enables individuals to critically evaluate AI technologies, communicate and collaborate effectively with AI, and use AI as a tool online, at home and in the workplace.", "structure_summary": "Seventeen competencies and fifteen design considerations, grouped under five questions: what is AI; what can AI do; how does AI work; how should AI be used; how do people perceive AI.", "n_domains": 5, "n_competences": 17, "progression": null, "strengths": "Built from a scoping review of 150 interdisciplinary documents. Gives a whole theme to how media and marketing shape what people believe AI is, and asks designers to disclose their intentions and their funding and data sources.", "notes": "Read in full on 2 October 2026; the paper carries no funding statement. Predates generative AI, so prompting, fabricated output and synthetic media are absent by date rather than by choice.", "accessed_on": "2026-10-02", "provenance_checked": 1, "needs_check": 0, "roles": [ { "org": "GATECH", "role": "issuer", "evidence": null, "source": "S-LM2020" } ], "framing": { "version_id": "LM2020-2020", "adoption_stance": "assumed", "learner_frame": "User and learner", "justification": "Treats AI as already embedded in everyday technology; the question is competence, not whether to adopt.", "source_id": "S-LM2020" }, "codings": { "AGE": { "score": 2, "confidence": "primary", "justification": "Learners are to recognise that humans programme, select and tune these systems rather than them running themselves, and the paper sets out the absence of any route to report an algorithmic error, learn why a decision was made, or hold anyone to account for it.", "source_id": "S-LM2020", "locator": "Competencies 5 and 10; Accountability", "coded_on": "2026-10-02" }, "ALT": { "score": 0, "confidence": "primary", "justification": "Neither refusal nor open, public or cooperative alternatives appear. Choosing human skills over AI is framed as fitting the tool to the problem, not as declining AI.", "source_id": "S-LM2020", "locator": "Competency 5", "coded_on": "2026-10-02" }, "CIV": { "score": 1, "confidence": "primary", "justification": "Imagining future AI is tied to making long-term policy decisions, and one cited project uses design fiction with citizens to explore AI in their city. No competency covers taking part in decisions about AI.", "source_id": "S-LM2020", "locator": "Competency 6", "coded_on": "2026-10-02" }, "CRE": { "score": 2, "confidence": "primary", "justification": "Programmability is a competency of its own and one design consideration is to give learners ways to program or teach an agent, with coding prerequisites kept low through visual elements and fill-in-the-blank code. Making things with AI, rather than about it, is not covered.", "source_id": "S-LM2020", "locator": "Competency 17; Design Consideration 6", "coded_on": "2026-10-02" }, "CRIT": { "score": 3, "confidence": "primary", "justification": "Critically evaluating AI is the first clause of the definition, and a whole theme examines how media and marketing shape what people believe AI is, including the finding that most AI news coverage follows industry products. Learners may arrive with sensationalised preconceptions that teaching should address, and designers are told to avoid systems that pass as human.", "source_id": "S-LM2020", "locator": "Definition; How Do People Perceive AI?; Design Considerations 8, 13 and 14", "coded_on": "2026-10-02" }, "ENV": { "score": 0, "confidence": "primary", "justification": "Energy, water, minerals and emissions do not appear.", "source_id": "S-LM2020", "locator": null, "coded_on": "2026-10-02" }, "ETH": { "score": 3, "confidence": "primary", "justification": "A whole theme. Bias and fairness, transparency, accountability and diversity each get their own treatment, drawn from the fairness and accountability literature, and one competency asks learners to hold different perspectives on them. Explainability and transparency are also design considerations.", "source_id": "S-LM2020", "locator": "How Should AI Be Used?; Competency 16; Design Considerations 1 and 4", "coded_on": "2026-10-02" }, "EVA": { "score": 2, "confidence": "primary", "justification": "Critically evaluating AI opens the definition, and learners are to treat data as requiring interpretation rather than taken at face value, to describe how the training examples shape a result, and to question how trustworthy a system is. Fabricated output and synthetic media are absent, the paper predating them.", "source_id": "S-LM2020", "locator": "Definition; Competencies 5, 13; Design Consideration 8", "coded_on": "2026-10-02" }, "LAB": { "score": 1, "confidence": "primary", "justification": "Employment appears in the list of ethical issues, as automation reducing the need for workers and as heightened concern about AI replacing the workforce. Nothing on working conditions or on the people who build these systems.", "source_id": "S-LM2020", "locator": "How Should AI Be Used? (Employment)", "coded_on": "2026-10-02" }, "LAW": { "score": 1, "confidence": "primary", "justification": "The GDPR right to challenge a decision made by AI and receive an explanation is noted, with the comment that it remains hard to exercise, and misdirected regulation is given as a consequence of public misunderstanding. No other instrument appears.", "source_id": "S-LM2020", "locator": "Accountability; Introduction", "coded_on": "2026-10-02" }, "POW": { "score": 1, "confidence": "primary", "justification": "Records that AI coverage is dominated by industry, with most articles following company products, and asks designers to disclose creator intentions and funding and data sources. Ownership, concentration and compute are absent.", "source_id": "S-LM2020", "locator": "Perceptions of AI in Popular Media; Design Consideration 4", "coded_on": "2026-10-02" }, "PRI": { "score": 1, "confidence": "primary", "justification": "Privacy, surveillance and data security are listed in a single paragraph among the ethical issues, and one competency has learners recognise that computers often learn from data including their own. No consent, data rights or control over data.", "source_id": "S-LM2020", "locator": "How Should AI Be Used? (Privacy/surveillance); Competency 12", "coded_on": "2026-10-02" }, "SAF": { "score": 1, "confidence": "primary", "justification": "Data security and the fear of AI harming people appear in the list of ethical issues, and machines that pass themselves off as human are called ethically problematic. Nothing on using AI safely.", "source_id": "S-LM2020", "locator": "How Should AI Be Used?; Interpreting AI Systems", "coded_on": "2026-10-02" }, "SOC": { "score": 2, "confidence": "primary", "justification": "How people perceive AI is one of the five themes, covering news coverage, film and polling, and the split between outlets that frame AI as economics and geopolitics and those that frame it as ethics. Misinformation and filter bubbles, and the effect of a narrow workforce on who systems get built for, are each set out.", "source_id": "S-LM2020", "locator": "How Do People Perceive AI?; How Should AI Be Used?", "coded_on": "2026-10-02" }, "TEC": { "score": 3, "confidence": "primary", "justification": "Thirteen of the seventeen competencies are about how AI works: recognising AI, what makes something intelligent, general against narrow AI, knowledge representations, how computers reason and decide, the steps of machine learning, learning from data, sensors, action and reaction, and programmability.", "source_id": "S-LM2020", "locator": "Competencies 1-4, 7-15, 17", "coded_on": "2026-10-02" }, "USE": { "score": 2, "confidence": "primary", "justification": "Using AI as a tool online, at home and in the workplace is part of the definition, and one competency asks learners to judge which problems suit AI and when to rely on human skills instead. 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null, "audiences": [], "versions": [] }, { "id": "JP-MEXT", "short_name": "Japan", "full_name": "MEXT guidelines on generative AI in schools", "region": "JP", "scope_type": "guideline", "catalogue_status": "queued", "sort_order": 330, "notes": null, "audiences": [], "versions": [] }, { "id": "AU-GENAI", "short_name": "Australia", "full_name": "Australian Framework for Generative AI in Schools", "region": "AU", "scope_type": "framework", "catalogue_status": "queued", "sort_order": 340, "notes": null, "audiences": [], "versions": [] }, { "id": "HK-EDB", "short_name": "Hong Kong EDB", "full_name": "Hong Kong Education Bureau AI curriculum", "region": "HK", "scope_type": "guideline", "catalogue_status": "queued", "sort_order": 350, "notes": null, "audiences": [], "versions": [] }, { "id": "IN-CBSE", "short_name": "India CBSE", "full_name": "CBSE AI curriculum", "region": "IN", "scope_type": "guideline", "catalogue_status": "queued", "sort_order": 360, "notes": null, "audiences": [], 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"id": "CSTA-2025", "short_name": "CSTA and AI4K12 2025", "full_name": "AI learning priorities for all K-12 students", "region": "US", "scope_type": "framework", "catalogue_status": "queued", "sort_order": 410, "notes": null, "audiences": [], "versions": [] }, { "id": "PENNSTATE", "short_name": "Penn State", "full_name": "Unified AI Literacy Framework", "region": "US", "scope_type": "academic_model", "catalogue_status": "queued", "sort_order": 420, "notes": null, "audiences": [], "versions": [] }, { "id": "MITRAISE", "short_name": "MIT RAISE", "full_name": "MIT RAISE and Day of AI curriculum", "region": "US", "scope_type": "framework", "catalogue_status": "queued", "sort_order": 430, "notes": null, "audiences": [], "versions": [] }, { "id": "USDOL", "short_name": "U.S. Department of Labor", "full_name": "U.S. Department of Labor, Employment and Training Administration AI literacy framework", "region": "US", "scope_type": "framework", "catalogue_status": "queued", "sort_order": 440, "notes": null, "audiences": [ "workforce" ], "versions": [] }, { "id": "DEC", "short_name": "Digital Education Council", "full_name": "Digital Education Council AI literacy framework", "region": "GLOBAL", "scope_type": "framework", "catalogue_status": "queued", "sort_order": 450, "notes": null, "audiences": [ "higher_ed" ], "versions": [] }, { "id": "EDUCAUSE", "short_name": "EDUCAUSE", "full_name": "EDUCAUSE AI Literacy in Teaching and Learning", "region": "US", "scope_type": "framework", "catalogue_status": "queued", "sort_order": 460, "notes": null, "audiences": [ "higher_ed" ], "versions": [] }, { "id": "EDAILIT", "short_name": "ED-AI Lit", "full_name": "ED-AI Lit (Allen and Kendeou, University of Minnesota)", "region": "US", "scope_type": "academic_model", "catalogue_status": "queued", "sort_order": 470, "notes": null, "audiences": [], "versions": [] }, { "id": "CETINDAMAR", "short_name": "Cetindamar et al.", "full_name": "AI literacy of employees in digital workplaces (Cetindamar, Kitto, Wu, Zhang, Abedin and Knight)", "region": "GLOBAL", "scope_type": "academic_model", "catalogue_status": "queued", "sort_order": 480, "notes": null, "audiences": [ "workforce" ], "versions": [] }, { "id": "ALMATRAFI", "short_name": "Almatrafi et al.", "full_name": "AI literacy review and synthesis (Almatrafi, Johri and Lee)", "region": "GLOBAL", "scope_type": "academic_model", "catalogue_status": "queued", "sort_order": 490, "notes": null, "audiences": [], "versions": [] } ], "changes": [ { "id": 1, "from_version_id": "AILIT-2025D", "to_version_id": "AILIT-2026", "change_type": "removed", "description": "The knowledge area on AI reshaping work and human roles was dropped.", "source_id": "S-AILIT-FINAL", "sort_order": 1 }, { "id": 7, "from_version_id": "COE-2025DP", "to_version_id": "COE-2026", "change_type": "removed", "description": "The hidden workers who label data and moderate content, named in the discussion paper, do not appear in the adopted text. 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The second, third and fourth domains went from 5 competences each to 4.", "source_id": "S-AILIT-FINAL", "sort_order": 2 }, { "id": 8, "from_version_id": "COE-2025DP", "to_version_id": "COE-2026", "change_type": "removed", "description": "The discussion paper's account of the military origins of much AI research is gone.", "source_id": "S-COE-TEXT", "sort_order": 2 }, { "id": 3, "from_version_id": "AILIT-2025D", "to_version_id": "AILIT-2026", "change_type": "added", "description": "The choice not to use AI is now named within the Responsible attitude, after consultees said the draft was too positive about AI.", "source_id": "S-AILIT-FINAL", "sort_order": 3 }, { "id": 9, "from_version_id": "COE-2025DP", "to_version_id": "COE-2026", "change_type": "changed", "description": "Environment and climate narrow to environmental sustainability: a named risk and a limit on deployment (paras 3, 13, 16), with no detail on energy, water or minerals.", "source_id": "S-COE-TEXT", "sort_order": 3 }, { "id": 4, "from_version_id": "AILIT-2025D", "to_version_id": "AILIT-2026", "change_type": "added", "description": "Three progression levels (Basic, Intermediate, Advanced) replace one primary and one secondary scenario per competence.", "source_id": "S-AILIT-FINAL", "sort_order": 4 }, { "id": 10, "from_version_id": "COE-2025DP", "to_version_id": "COE-2026", "change_type": "added", "description": "Principle 30 gives individuals and communities a say in whether AI is developed and used at all, not only how.", "source_id": "S-COE-TEXT", "sort_order": 4 }, { "id": 5, "from_version_id": "AILIT-2025D", "to_version_id": "AILIT-2026", "change_type": "changed", "description": "Domain names became imperatives. The fourth domain, Designing AI, became Shape AI.", "source_id": "S-AILIT-FINAL", "sort_order": 5 }, { "id": 11, "from_version_id": "COE-2025DP", "to_version_id": "COE-2026", "change_type": "added", "description": "Principle 22 requires independent, contestable evidence for claims about AI's effectiveness and safety.", "source_id": "S-COE-TEXT", "sort_order": 5 }, { "id": 6, "from_version_id": "AILIT-2025D", "to_version_id": "AILIT-2026", "change_type": "changed", "description": "Licence changed from CC BY-SA 4.0 to CC BY 4.0, which allows closed derivative works.", "source_id": "S-AILIT-FINAL", "sort_order": 6 }, { "id": 12, "from_version_id": "COE-2025DP", "to_version_id": "COE-2026", "change_type": "added", "description": "The private sector enters as a partner in national strategies and co-operation (32.d, 38.a), with public responsibility for rights and data protection.", "source_id": "S-COE-TEXT", "sort_order": 6 } ], "evidence": [ { "id": "E-CMA", "topic": "concentration", "claim": "The UK competition authority found an interconnected web of partnerships and strategic investments involving Google, Apple, Microsoft, Meta, Amazon and Nvidia, and warned these firms could shape AI markets to protect their existing power.", "figure": "90+ partnerships", "figure_date": "2024-04-11", "is_projection": 0, "source_id": "S-CMA-2024", "caveat": null, "sort_order": 1 }, { "id": "E-AINOW", "topic": "concentration", "claim": "AI Now finds frontier AI still controlled by a handful of firms, Microsoft, Google, Meta, xAI, OpenAI and Anthropic, with OpenAI backed by Microsoft and Anthropic by Amazon and Google. The report's summary: AI is used on people, not by them.", "figure": null, "figure_date": "2025-06-03", "is_projection": 0, "source_id": "S-AINOW-2025", "caveat": null, "sort_order": 2 }, { "id": "E-COMPUTE", "topic": "concentration", "claim": "Compute is monopolised at key points in the supply chain, from chips to cloud. AI Now cites an industry estimate that AI firms spend over 80% of their capital on compute.", "figure": "80%+ of capital", "figure_date": "2023", "is_projection": 0, "source_id": "S-AINOW-COMPUTE", "caveat": "Industry estimate reported by AI Now.", "sort_order": 3 }, { "id": "E-EUROSTACK", "topic": "concentration", "claim": "More than 80% of the digital technology and infrastructure Europe uses is imported, and 70% of the foundation models used worldwide come from the United States.", "figure": "80% imported", "figure_date": "2025-02-13", "is_projection": 0, "source_id": "S-EUROSTACK", "caveat": null, "sort_order": 4 }, { "id": "E-BIESTA", "topic": "critique", "claim": "The Council of Europe discussion paper argues that AI literacy usually covers only qualification, one of the three purposes of education in Biesta's account, and neglects socialisation and subjectification.", "figure": null, "figure_date": "2025-02-25", "is_projection": 0, "source_id": "S-COE-DISC", "caveat": null, "sort_order": 1 }, { "id": "E-AILIT-ANNEX", "topic": "critique", "claim": "Consultees on the AILit draft said it painted an overly positive picture of AI. The criticism came from inside the consultation.", "figure": null, "figure_date": "2026", "is_projection": 0, "source_id": "S-AILIT-FINAL", "caveat": null, "sort_order": 2 }, { "id": "E-POWERKNOW", "topic": "critique", "claim": "A 2026 preprint examines AI literacy itself as an exercise of power-knowledge.", "figure": null, "figure_date": "2026", "is_projection": 0, "source_id": "S-POWERKNOW", "caveat": "Preprint.", "sort_order": 3 }, { "id": "E-LABOUR", "topic": "data_labour", "claim": "The AILit Framework cites ILO research on the invisible workers who label data and moderate content, and the Council of Europe discussion paper names the ghost workers behind AI. This is where mainstream coverage of labour stops.", "figure": null, "figure_date": "2026", "is_projection": 0, "source_id": "S-AILIT-FINAL", "caveat": null, "sort_order": 1 }, { "id": "E-IEA-2024", "topic": "environment", "claim": "Data centres used about 415 TWh of electricity in 2024, around 1.5% of global consumption.", "figure": "415 TWh", "figure_date": "2024", "is_projection": 0, "source_id": "S-IEA-2025", "caveat": null, "sort_order": 1 }, { "id": "E-IEA-2030", "topic": "environment", "claim": "In the IEA base case, data centre electricity use roughly doubles to about 945 TWh by 2030, slightly more than Japan uses today. The United States and China account for nearly 80% of the growth.", "figure": "945 TWh", "figure_date": "2030", "is_projection": 1, "source_id": "S-IEA-2025", "caveat": "Projection. The IEA also gives lower and higher scenarios.", "sort_order": 2 }, { "id": "E-CODEAI", "topic": "industry_influence", "claim": "CodeAI staff did the project management, research and drafting for the OECD and European Commission AILit Framework. CodeAI lists Amazon and Microsoft as lifetime supporters at USD 30m or more each, and Google and Meta at USD 10m or more.", "figure": "USD 30m+ each", "figure_date": "2026", "is_projection": 0, "source_id": "S-CODEAI-SUPP", "caveat": null, "sort_order": 1 }, { "id": "E-OPENAI-CODEAI", "topic": "industry_influence", "claim": "OpenAI became a CodeAI programme partner in August 2026. No amount disclosed.", "figure": null, "figure_date": "2026-08-18", "is_projection": 0, "source_id": "S-OPENAI-CODEAI", "caveat": null, "sort_order": 2 }, { "id": "E-AFT", "topic": "industry_influence", "claim": "The American Federation of Teachers' National Academy for AI Instruction is funded by Microsoft (USD 12.5m over five years), OpenAI (USD 8m plus USD 2m in technical resources) and Anthropic (USD 500,000 in the first year).", "figure": "USD 23m", "figure_date": "2025-07-08", "is_projection": 0, "source_id": "S-AFT-2025", "caveat": "Source URL still to add.", "sort_order": 3 }, { "id": "E-MSFT", "topic": "industry_influence", "claim": "Microsoft urges US policymakers to use TeachAI resources, and backs an educator AI credential it says is aligned with the AI Literacy Framework.", "figure": null, "figure_date": "2026-02-24", "is_projection": 0, "source_id": "S-MSFT-2026", "caveat": null, "sort_order": 4 }, { "id": "E-TAL", "topic": "industry_influence", "claim": "Both UNESCO frameworks thank TAL Education Group, a Chinese for-profit education company, for supporting the publications. The student framework also warns that AI competencies are too often defined by private companies' training on profit-driven platforms.", "figure": null, "figure_date": "2024", "is_projection": 0, "source_id": "S-UNESCO-S-PDF", "caveat": "The funding amount is not disclosed.", "sort_order": 5 } ], "initiatives": [ { "id": "CURRENTAI", "name": "Current AI", "kind": "funding_programme", "launched": "2025-02-11", "description": "A public-interest AI partnership launched at the Paris AI Action Summit to fund open data, open models and accountability tools.", "backers": "France, Germany, India, Kenya, Switzerland and others; the MacArthur and McGovern foundations; Google and Salesforce", "pledged": "USD 400m initial, USD 2.5bn five-year target", "reported_spent": "USD 3.2m to four grantees by mid-2026", "url": "https://www.currentai.org", "source_id": "S-CURRENTAI", "caveat": "The spending figure comes from a trade outlet (Unite.AI). Note that Google is among the backers.", "sort_order": 1 }, { "id": "APERTUS", "name": "Apertus", "kind": "open_model", "launched": "2025", "description": "Fully open 8B and 70B language models with open training data and documentation, from EPFL, ETH Zurich and the Swiss National Supercomputing Centre. Served through Swisscom and the Public AI Inference Utility.", "backers": "EPFL, ETH Zurich, CSCS", "pledged": null, "reported_spent": null, "url": null, "source_id": "S-APERTUS", "caveat": null, "sort_order": 2 }, { "id": "EUROSTACK", "name": "EuroStack", "kind": "infrastructure_proposal", "launched": "2025-02-13", "description": "A proposal for a European technology stack covering every layer from raw materials and chips to cloud and AI.", "backers": "Bertelsmann Stiftung (report)", "pledged": "About EUR 300bn over roughly a decade (estimate)", "reported_spent": null, "url": null, "source_id": "S-EUROSTACK", "caveat": "A costed proposal, not a funded programme.", "sort_order": 3 } ], "proposed": [ { "id": "PC-CONC", "name": "Market and compute concentration", "description": "Who controls chips, cloud, data, models and the capital behind them, and what that control lets them decide.", "sort_order": 1 }, { "id": "PC-INFL", "name": "Industry influence on education and policy", "description": "Who funds, drafts and promotes the curricula, frameworks and teacher training that define AI literacy.", "sort_order": 2 }, { "id": "PC-CONDUCT", "name": "Developer conduct over time", "description": "How a company's stated commitments change after its tools are adopted, and what that means for relying on them.", "sort_order": 3 }, { "id": "PC-HYPE", "name": "Hype literacy", "description": "Reading claims about capability, inevitability and timelines, and asking who benefits from them.", "sort_order": 4 }, { "id": "PC-LABOUR", "name": "Data labour and extraction", "description": "The workers, minerals, water and energy behind training and running AI.", "sort_order": 5 }, { "id": "PC-COMP", "name": "Competition and antitrust", "description": "How competition law applies to AI markets, and what regulators have found.", "sort_order": 6 }, { "id": "PC-PUBLIC", "name": "Public and open alternatives", "description": "Open models, public AI, cooperative and sovereign infrastructure, and digital public infrastructure.", "sort_order": 7 }, { "id": "PC-REFUSE", "name": "Refusal and democratic governance", "description": "Non-use as a legitimate choice, and collective decisions about whether and how AI is adopted.", "sort_order": 8 } ] }