{
  "$schema_version": "1.0",
  "name": "CoSAI AI Shared Responsibility Framework Glossary Registry",
  "description": "Canonical, deduplicated definitions for every SRF term. Each term is independently retrievable at /api/glossary/<anchor>.json and carries a canonical_id that resolves to a single ontology node.",
  "srf_version": "1.0",
  "updated": "2026-06-14",
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      "term": "Layer",
      "section": "Framework Architecture",
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      "definition": "One of five enterprise architecture tiers in the CoSAI SRF (L1-L5). Each layer represents a distinct accountability domain. Requirements cascade from L1 downward through L2, L3, L4, and L5.",
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      "term": "L1: AI Business & Usage",
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        "L1"
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      "term": "L2: AI Information",
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      "definition": "The data ownership and privacy layer. Accountable for training data provenance, master data management, privacy controls, and data classification decisions.",
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      "definition": "The development and integration layer. Responsible for guardrails, input validation, output filtering, prompt engineering, RAG pipelines, and agent orchestration logic.",
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      "definition": "The infrastructure and runtime layer. Covers compute, LLM gateways, model routers, guardrail infrastructure, and platform-level IAM.",
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      "term": "Persona",
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      "definition": "A named stakeholder role in the SRF. There are eight personas, each mapped to one or more layers. Controls assign accountability to exactly one persona.",
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      "section": "Framework Architecture",
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      "definition": "One of four deployment archetypes (AI-SaaS, AI-PaaS, Agent-PaaS, IaaS) that determines how L1-L5 accountability shifts between customer and provider.",
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      "section": "Accountability Rules",
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      "definition": "The obligation that cannot be delegated. Exactly one party per activity. The SRF's central rule: \"shared\" is a valid matrix value during analysis but must resolve to a single named persona in every control.",
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      "section": "Accountability Rules",
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      "definition": "The single persona named as accountable for a given control. If a control shows \"shared\" in the responsibility matrix, the accountable party is still the one who cannot transfer the obligation.",
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      "definition": "The principle that security and governance requirements set at L1 propagate downward through L2, L3, L4, and L5. An L1 policy decision constrains every layer below it.",
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      "section": "Accountability Rules",
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      "definition": "A state in the responsibility matrix where both customer and provider carry obligations for a control. Not a final answer: each shared control must still name one accountable persona.",
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      "term": "RACI",
      "section": "Accountability Rules",
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      "definition": "Responsible, Accountable, Consulted, Informed. The SRF applies RACI at the control level but enforces exactly one Accountable owner per row.",
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      "anchor": "AI-SaaS",
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      "definition": "AI-Enabled SaaS. Provider manages the application (L3), platform (L4), and model (L5). Customer retains L1 governance and L2 data obligations. Lowest customer technical responsibility.",
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      "definition": "AI Platform as a Service. Customer builds and owns L3. Provider manages L4 and L5. Customer and provider share L2.",
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      "see_also": "https://aisharedresponsibility.com/operating-models/#AI-PaaS",
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      "anchor": "Agent-PaaS",
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      "section": "Operating Models",
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      "definition": "Agentic Platform as a Service. Customer owns agent definitions and L1 business logic on a provider-managed orchestration runtime. L3 and L5 are shared.",
      "anchor_url": "https://aisharedresponsibility.com/glossary/#Agent-PaaS",
      "see_also": "https://aisharedresponsibility.com/operating-models/#Agent-PaaS",
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      "anchor": "IaaS",
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      "section": "Operating Models",
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      "definition": "Infrastructure as a Service. Maximum customer responsibility. Customer owns L1-L3 and most of L5. Provider is accountable only for physical infrastructure within L4.",
      "anchor_url": "https://aisharedresponsibility.com/glossary/#IaaS",
      "see_also": "https://aisharedresponsibility.com/operating-models/#IaaS",
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      "anchor": "autonomy-level",
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      "term": "Autonomy Level",
      "section": "Agentic Extensions",
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      "definition": "A six-point scale (L0-L5) classifying how independently an AI agent acts. L0 = fully human-controlled; L5 = fully autonomous with no human oversight. Every agentic deployment must declare its autonomy level.",
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      "term": "Human Override Tier",
      "section": "Agentic Extensions",
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      "definition": "A five-point scale (T1-T5) specifying the required human intervention capability for an agentic system. T1 = immediate human takeover at any step; T5 = retrospective audit only. Must be declared alongside autonomy level.",
      "anchor_url": "https://aisharedresponsibility.com/glossary/#human-override-tier",
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      "term": "Agentic System",
      "section": "Agentic Extensions",
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      "definition": "An AI system that can take multi-step actions, use tools, or operate across sessions with limited human supervision. Agentic systems require autonomy level and human override tier declarations in addition to standard SRF layer assignments.",
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      "anchor": "control",
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      "section": "Evidence & Controls",
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      "definition": "A specific accountability assignment within a vertical schema. Each control has an ID (e.g. SRF-L1-DEV-001), a layer, an accountable persona, applicable operating models, and an evidence threshold.",
      "anchor_url": "https://aisharedresponsibility.com/glossary/#control",
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      "definition": "The measurable criterion that satisfies a control. Specifies a metric, operator, parameter, window, and breach action. Used to determine whether accountability is being exercised.",
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      "section": "Evidence & Controls",
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      "definition": "Open Cybersecurity Schema Framework. The evidence schema used to specify what telemetry or log data satisfies a control's evidence requirement.",
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      "definition": "The full set of controls for a vertical. Six are published: Financial Services (40 controls), Healthcare (40), Insurance (40), Public Sector (40), Defense (53), Manufacturing (45).",
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      "definition": "Defines security control objectives, measures implementations, and enforces compliance. Includes AI risk officers, compliance teams, and governance boards.",
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      "term": "Data Provider",
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      "definition": "Supplies training data, evaluation datasets, or inference data. Includes data aggregators and dataset licensors.",
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      "term": "Application Developer",
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      "definition": "Integrates AI models into applications via APIs or embedded models. Accountable for application-level security, input validation, and output filtering.",
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      "definition": "Provides compute, APIs, and platform services for AI model hosting. Includes cloud providers and MLOps platforms.",
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      "definition": "Develops, trains, and tunes foundation models. Accountable for model security, model cards, and vulnerability disclosure.",
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}