+ A framework for AI safety through architectural constraints, preserving human agency where it matters most. +
++ The Tractatus Framework exists to address a fundamental problem in AI safety: current approaches rely on training, fine-tuning, and corporate governance—all of which can fail, drift, or be overridden. We propose safety through architecture. +
++ Inspired by Ludwig Wittgenstein's Tractatus Logico-Philosophicus, our framework recognizes that some domains—values, ethics, cultural context, human agency—cannot be systematized. What cannot be systematized must not be automated. AI systems should have structural constraints that prevent them from crossing these boundaries. +
++ "Whereof one cannot speak, thereof one must be silent."+
+ — Ludwig Wittgenstein, Tractatus (§7) +
+ Applied to AI: "What cannot be systematized must not be automated." +
++ Individuals and communities must maintain control over decisions affecting their data, privacy, and values. AI systems must preserve human agency, not erode it. +
++ All AI decisions must be explainable, auditable, and reversible. No black boxes. Users deserve to understand how and why systems make choices, and have power to override them. +
++ AI systems must not cause harm through action or inaction. This includes preventing drift, detecting degradation, and enforcing boundaries against values erosion. +
++ AI safety is a collective endeavor. We are committed to open collaboration, knowledge sharing, and empowering communities to shape the AI systems that affect their lives. +
++ The Tractatus Framework consists of five integrated components that work together to enforce structural safety: +
++ Classifies instructions by quadrant (Strategic, Operational, Tactical, System, Stochastic) and determines persistence level (HIGH/MEDIUM/LOW/VARIABLE). +
++ Validates AI actions against stored instructions to prevent contradictions (like the 27027 incident where MongoDB port was changed from explicit instruction). +
++ Ensures AI never makes values decisions without human approval. Privacy trade-offs, user agency, cultural context—these require human judgment. +
++ Detects when session conditions increase error probability (token pressure, message length, task complexity) and adjusts behavior or suggests handoff. +
++ AI self-checks complex reasoning before proposing actions. Evaluates alignment, coherence, completeness, safety, and alternatives. +
++ The Tractatus Framework emerged from real-world AI failures experienced during extended Claude Code sessions. The "27027 incident"—where AI contradicted an explicit instruction about MongoDB port after 85,000 tokens—revealed that traditional safety approaches were insufficient. +
++ After documenting multiple failure modes (parameter contradiction, values drift, silent degradation), we recognized a pattern: AI systems lacked structural constraints. They could theoretically "learn" safety, but in practice they failed when context pressure increased, attention decayed, or subtle values conflicts emerged. +
++ The solution wasn't better training—it was architecture. Drawing inspiration from Wittgenstein's insight that some things lie beyond the limits of language (and thus systematization), we built a framework that enforces boundaries through structure, not aspiration. +
++ The Tractatus Framework is open source under the MIT License. We encourage: +
++ The framework is intentionally permissive because AI safety benefits from transparency and collective improvement, not proprietary control. +
++ Help build AI systems that preserve human agency through architectural guarantees. +
+ ++ The foundational values that guide the Tractatus Framework's development, governance, and community. +
++ These four values form the foundation of the Tractatus Framework. They are not aspirational—they are architectural. The framework is designed to enforce these values through structure, not training. +
++ Principle: Individuals and communities must maintain control over decisions affecting their data, privacy, values, and agency. AI systems must preserve human sovereignty, not erode it. +
+ ++ Principle: All AI decisions must be explainable, auditable, and reversible. No black boxes. Users deserve to understand how and why systems make choices. +
+ ++ Principle: AI systems must not cause harm through action or inaction. This includes preventing drift, detecting degradation, and enforcing boundaries against values erosion. +
+ ++ Principle: AI safety is a collective endeavor, not a corporate product. Communities must have tools, knowledge, and agency to shape AI systems affecting their lives. +
+ ++ Context: The Tractatus Framework is developed in Aotearoa New Zealand. We acknowledge Te Tiriti o Waitangi (the Treaty of Waitangi, 1840) as the founding document of this nation, and recognize the ongoing significance of tino rangatiratanga (self-determination) and kaitiakitanga (guardianship) in the digital realm. +
++ This acknowledgment is not performative. Digital sovereignty—the principle that communities control their own data and technology—has deep roots in indigenous frameworks that predate Western tech by centuries. +
++ Te Tiriti o Waitangi establishes principles of partnership, protection, and participation. These principles directly inform the Tractatus Framework's approach to digital sovereignty: +
++ We do not claim to speak for Māori or indigenous communities. Instead, we: +
++ Indigenous data sovereignty is the principle that indigenous peoples have the right to control the collection, ownership, and application of their own data. This goes beyond privacy—it's about self-determination in the digital age. +
++ The Tractatus Framework aligns with the CARE Principles, developed by indigenous data governance experts: +
+ ++ Data ecosystems shall be designed and function in ways that enable Indigenous Peoples to derive benefit from the data. +
++ Indigenous Peoples' rights and interests in Indigenous data must be recognized and their authority to control such data be empowered. +
++ Those working with Indigenous data have a responsibility to share how data are used to support Indigenous Peoples' self-determination and collective benefit. +
++ Indigenous Peoples' rights and wellbeing should be the primary concern at all stages of the data life cycle and across the data ecosystem. +
+Leading network advancing Māori data sovereignty in Aotearoa.
+International framework for indigenous data rights.
+Global collaboration on indigenous data sovereignty.
++ Values without enforcement are aspirations. The Tractatus Framework implements these values through architectural governance: +
++ Quarterly reviews of framework alignment with stated values. Any drift from sovereignty, transparency, harmlessness, or community principles triggers mandatory correction. +
++ All major decisions (architectural changes, partnerships, licensing) must pass values alignment check. If a decision would compromise any core value, it is rejected. +
++ AI-generated content (documentation, code examples, case studies) requires human approval before publication. No AI makes values decisions without human judgment. +
++ Open source development means community oversight. If we fail to uphold these values, the community can fork, modify, or create alternatives. This is by design. +
++ These values are not negotiable. They form the architectural foundation of the Tractatus Framework. We commit to: +
++ When in doubt, we choose human agency over AI capability. Always. +
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