This paper presents an alternative: constitutional governance for community-controlled AI. The Tractatus Framework implements explicit rules, defined by your community, that constrain what AI systems can do before any action is taken. This isn't about making AI less capable—it's about making AI accountable to the community it serves.
-The framework is implemented in the Village platform and designed to support both cloud-based AI and locally-deployed systems. We introduce the concept of Sovereign Locally-trained Language Models (SLLs)—AI systems that run on community infrastructure, adapt to community norms, and operate under community-defined constitutions rather than vendor terms of service.
+The framework is implemented in the Village platform and designed to support both cloud-based AI and locally-deployed systems. We introduce the concept of Situated Language Layers (SLLs)—AI systems that run on community infrastructure, adapt to community norms, and operate under community-defined constitutions rather than vendor terms of service.
We introduce the term Sovereign Locally-trained Language Model (SLL) to describe AI systems with specific properties:
+We introduce the term Situated Language Layer (SLL) to describe an architectural layer with specific properties:
Local deployment: Runs on your infrastructure—a home server, community hardware, or local data centre—not a vendor's cloud
Local adaptation: Fine-tuned on your community's data and norms, not generic training
diff --git a/public/architectural-alignment-policymakers.html b/public/architectural-alignment-policymakers.html index 1fb964fe..eb763da4 100644 --- a/public/architectural-alignment-policymakers.html +++ b/public/architectural-alignment-policymakers.html @@ -105,7 +105,7 @@This paper presents the Tractatus Framework, an architectural approach to AI governance through inference-time constitutional gating. Rather than relying solely on vendor training to ensure AI behaves appropriately, Tractatus requires AI systems to translate proposed actions into auditable forms and evaluate them against explicit constitutional rules before execution. This creates visible, enforceable governance at the point of deployment.
-The framework is implemented in the Village platform and designed to accommodate both centralised cloud AI and distributed local deployments, including what we term Sovereign Locally-trained Language Models (SLLs)—AI systems whose training, deployment, and governance remain under community or individual sovereignty rather than vendor control.
+The framework is implemented in the Village platform and designed to accommodate both centralised cloud AI and distributed local deployments, including what we term Situated Language Layers (SLLs)—AI systems whose training, deployment, and governance remain under community or individual sovereignty rather than vendor control.
We distinguish two deployment paradigms that have different governance implications:
Small Language Model (SLM): A technical descriptor for language models with fewer parameters than frontier LLMs, designed for efficiency and domain-specific deployment. SLMs may be deployed via cloud subscription or locally.
-Sovereign Locally-trained Language Model (SLL): An architectural descriptor we introduce for AI systems whose training, deployment, and governance remain under local sovereignty. Key properties:
+Situated Language Layer (SLL): An architectural layer comprising a small language model that is sovereign (locally trained, locally deployed, community-controlled) and situated (shaped by the specific context, values, and vocabulary of the community it serves). Key properties:
Local deployment: Runs on home or community infrastructure
Local adaptation: Fine-tuned on community-specific data
diff --git a/public/architectural-alignment.html b/public/architectural-alignment.html index 281e78a3..5155449f 100644 --- a/public/architectural-alignment.html +++ b/public/architectural-alignment.html @@ -108,7 +108,7 @@We present the Tractatus Framework as a formal specification for interrupted neural reasoning: proposals generated by AI systems must be translated into auditable forms and evaluated against constitutional constraints before execution. This shifts the trust model from "trust the vendor's training" to "trust the visible architecture." The framework is implemented within the Village multi-tenant community platform, providing an empirical testbed for governance research.
-Critically, we address the faithful translation assumption—the vulnerability that systems may misrepresent their intended actions to constitutional gates—by bounding the framework's domain of applicability to pre-superintelligence systems and specifying explicit capability thresholds and escalation triggers. We introduce the concept of Sovereign Locally-trained Language Models (SLLs) as a deployment paradigm where constitutional gating becomes both feasible and necessary.
+Critically, we address the faithful translation assumption—the vulnerability that systems may misrepresent their intended actions to constitutional gates—by bounding the framework's domain of applicability to pre-superintelligence systems and specifying explicit capability thresholds and escalation triggers. We introduce the concept of Situated Language Layers (SLLs) as a deployment paradigm where constitutional gating becomes both feasible and necessary.
The paper contributes: (1) a formal architecture for inference-time constitutional gating; (2) capability threshold specifications with escalation logic; (3) validation methodology for layered containment; (4) an argument connecting existential risk preparation to edge deployment; and (5) a call for sustained deliberation (kōrero) as the epistemically appropriate response to alignment uncertainty.
@@ -308,7 +308,7 @@6.5 Extension to Sovereign Local Deployments
We distinguish:
Small Language Model (SLM). A technical descriptor for models with fewer parameters than frontier LLMs, designed for efficiency.
-Sovereign Locally-trained Language Model (SLL). An architectural descriptor: a model whose training, deployment, and governance remain under local sovereignty. Key properties include local deployment, local adaptation, local governance, and portable sovereignty.
+Situated Language Layer (SLL). An architectural layer comprising a small language model that is sovereign (locally trained, locally deployed, community-controlled) and situated (shaped by the specific context, values, and vocabulary of the community it serves). The term draws on situated knowledge theory: understanding that emerges from a particular context rather than claiming universality.
7. Capability Thresholds and Escalation
diff --git a/public/locales/en/village-ai.json b/public/locales/en/village-ai.json index b12501e4..97c84d14 100644 --- a/public/locales/en/village-ai.json +++ b/public/locales/en/village-ai.json @@ -11,7 +11,7 @@ }, "sll": { "heading": "What is an SLL?", - "intro": "An SLL (Sovereign Locally-trained Language Model) is distinct from both LLMs and SLMs. The distinction is not size — it is control.", + "intro": "An SLL (Situated Language Layer) is distinct from both LLMs and SLMs. The distinction is not size — it is sovereignty and situatedness.", "llm_title": "LLM", "llm_subtitle": "Large Language Model", "llm_item1": "Training: provider-controlled", @@ -25,7 +25,7 @@ "slm_item3": "Governance: partial (fine-tuning)", "slm_item4": "User control: limited", "sll_title": "SLL", - "sll_subtitle": "Sovereign Locally-trained", + "sll_subtitle": "Situated Language Layer", "sll_item1": "Training: community-controlled", "sll_item2": "Data: community-owned", "sll_item3": "Governance: architecturally enforced", diff --git a/public/village-ai.html b/public/village-ai.html index 8f20ed47..772a10e8 100644 --- a/public/village-ai.html +++ b/public/village-ai.html @@ -76,7 +76,7 @@What is an SLL?
@@ -103,7 +103,7 @@- An SLL (Sovereign Locally-trained Language Model) is distinct from both LLMs and SLMs. The distinction is not size — it is control. + An SLL (Situated Language Layer) is distinct from both LLMs and SLMs. The distinction is not size — it is sovereignty and situatedness.
Sovereign Locally-trained
+Situated Language Layer