tractatus/public/locales/en/leader.json

{
  "page": {
    "title": "For Decision-Makers | Tractatus AI Safety Framework",
    "description": "Structural AI governance for organisations deploying LLM systems at scale. Research framework addressing architectural gaps in AI safety."
  },
  "header": {
    "badge": "Research Framework • Early Development",
    "title": "Tractatus: Architectural Governance for LLM Systems",
    "subtitle": "A governance framework addressing structural gaps in AI safety through external architectural controls. Designed for organisations deploying large language models at scale where conventional oversight mechanisms prove insufficient."
  },
  "sections": {
    "governance_gap": {
      "heading": "The Governance Gap",
      "intro": "Current AI governance approaches—policy documents, training programmes, ethical guidelines—rely on voluntary compliance. LLM systems can bypass these controls simply by not invoking them. When an AI agent needs to check a policy, it must choose to do so. When it should escalate a decision to human oversight, it must recognise that obligation.",
      "problem": "This creates a structural problem: governance exists only insofar as the AI acknowledges it. For organisations subject to EU AI Act Article 14 (human oversight requirements) or deploying AI in high-stakes domains, this voluntary model is inadequate.",
      "solution": "Tractatus explores whether governance can be made architecturally external—difficult to bypass not through better prompts, but through system design that places control points outside the AI's discretion."
    },
    "architectural_approach": {
      "heading": "Architectural Approach",
      "three_layer_title": "Three-Layer Architecture",
      "services_title": "Six Governance Services",
      "arch_layers": {
        "layer_1_title": "Agent Runtime Layer",
        "layer_1_desc": "Any LLM system (Claude Code, Copilot, custom agents, LangChain, CrewAI). The AI system being governed.",
        "layer_2_title": "Governance Layer",
        "layer_2_desc": "Six autonomous services that intercept, validate, and document AI operations. External to the AI runtime.",
        "layer_3_title": "Persistent Storage Layer",
        "layer_3_desc": "Immutable audit logs, governance rules, instruction history. Cannot be altered by AI prompts."
      },
      "services": {
        "service_1_title": "BoundaryEnforcer",
        "service_1_desc": "Blocks AI from making values decisions without human approval. Enforces decision boundaries through architectural controls.",
        "service_2_title": "InstructionPersistenceClassifier",
        "service_2_desc": "Prevents pattern bias from overriding explicit instructions. Stores organisational directives external to AI context.",
        "service_3_title": "CrossReferenceValidator",
        "service_3_desc": "Validates AI actions against stored policies before execution. Detects conflicts with established rules.",
        "service_4_title": "ContextPressureMonitor",
        "service_4_desc": "Tracks session complexity, token usage, conversation length. Detects degradation in decision quality.",
        "service_5_title": "MetacognitiveVerifier",
        "service_5_desc": "Validates reasoning quality before complex operations. Self-checks alignment, coherence, alternatives.",
        "service_6_title": "PluralisticDeliberationOrchestrator",
        "service_6_desc": "Facilitates multi-stakeholder deliberation for values conflicts. Non-hierarchical engagement with documented dissent."
      }
    },
    "governance_capabilities": {
      "heading": "Governance Capabilities",
      "intro": "Three interactive demonstrations showing governance infrastructure in operation. These show mechanisms, not fictional scenarios.",
      "audit_trail_title": "Audit Trail & Compliance Evidence Generation",
      "audit_trail_desc": "Immutable logging, evidence extraction, regulatory reporting",
      "continuous_improvement_title": "Continuous Improvement: Incident → Rule Creation",
      "continuous_improvement_desc": "Learning from failures, automated rule generation, validation",
      "pluralistic_deliberation_title": "Pluralistic Deliberation: Values Conflict Resolution",
      "pluralistic_deliberation_desc": "Multi-stakeholder engagement, non-hierarchical process, moral remainder documentation"
    },
    "development_status": {
      "heading": "Development Status",
      "warning_title": "Early-Stage Research Framework",
      "warning_text": "Tractatus is a proof-of-concept developed over six months in a single project context (this website). It demonstrates architectural patterns for AI governance but has not undergone independent validation, red-team testing, or multi-organisation deployment.",
      "validation_title": "Validated vs. Not Validated"
    },
    "eu_ai_act": {
      "heading": "EU AI Act Considerations",
      "article_14_title": "Regulation 2024/1689, Article 14: Human Oversight"
    },
    "research_foundations": {
      "heading": "Research Foundations",
      "org_theory_title": "Organisational Theory & Philosophical Basis"
    },
    "scope_limitations": {
      "heading": "Scope & Limitations",
      "title": "What This Is Not • What It Offers",
      "not_title": "Tractatus is not:",
      "offers_title": "What it offers:"
    }
  }
}