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@node-and-norm

NODE & NORM

Independent AI assurance & evaluation research lab. Evidence behind AI-assisted decisions: evaluation, authority, challenge, and correction.

AI under control. Can you prove it?

Node & Norm studies the evidence behind AI-assisted decisions: how they are evaluated, authorized, challenged, and corrected. The research examines whether safeguards worked and whether the evidence exists to show it.

Explore the research · Where the work stands · Brand assets

From governance to evidence

Policies, risk reviews, and approvals establish expectations for AI use. A consequential decision still needs evidence that those expectations held. What supported the recommendation? Who could challenge it? Did the correction reach execution?

Node & Norm develops methods, evidence records, and reference implementations for examining those questions. Sources, versions, and unresolved findings stay attached to the work.

Explore the research

Human Control & Decision Authority

Can the person assigned responsibility actually affect what happens?

Research What to inspect
Trust, Autonomy & Evidence (TAE) Conditions for practical human control, from evidence access to an intervention taking effect. Three selected historical cases; one assessor.
Human Influence Telemetry (HIT) What documentary records establish about the exercise of human authority. Broader validation remains open.

Decision Evidence & Governed Action

Can a team reconstruct why it proceeded, stopped, or waited, and what obligations remained?

Research What to inspect
Governed Decision Intelligence (GDI) General decision-record specification and reference implementation.
AI Assistance Governance A method/profile for bounded AI participation, assigned human authority, and dependency assessment.
Regulated Gate Decision Support (RGDS) Regulated phase-gate reference implementation, illustrative records, and validation tools.
RGDS independent study Historical, exploratory research with its own record. Read the study.

GDI supplies the general decision architecture, AI Assistance Governance defines its participation profile, and RGDS supplies a regulated reference implementation. Availability of code does not establish field effectiveness.

AI Evaluation & Assurance

Do evaluation rules, implementation, and evidence support the reported result?

Catholic Doctrinal Fidelity Index (CDFI) develops evaluation-governance methodology and a reference implementation for domain-specific doctrinal assessment. Scoring-contract reconciliation remains open. SAICRED is an external collaborative project with its own leadership and publication authority.

Where the work stands

These are different dimensions: publication status, ongoing research, and source availability. Status reflects the author's website update of 15 September 2026; it does not advance the scope of earlier findings.

Work Dimension Current record
TAE manuscript Publication status On hold pending arXiv approval
HIT Research status Research in progress
CDFI Research status Evolving
GDI Availability Open source
RGDS Availability Open source
Poenitentia Institutionum Publication status Editorial review
Emerging research and shared infrastructure

AI Incident Reconstruction & Assurance examines what happened, which controls held, and what supports a correction. Website case records remain provisional documentary reviews.

Institutional Responsibility & Repair asks what an institution owes those affected by AI-mediated harm. Poenitentia Institutionum develops the normative argument; its repository is private and empirical outcome validation remains open.

Control Evidence Corpus (CEC) is private development infrastructure for testing whether independent reviewers can reconstruct control operation from surviving evidence. Its empirical integration with downstream projects remains prospective.

These areas preserve the three permanent research programs above. The website Registry owns presentation identities and admitted summaries. Each source repository retains its research and release authority.

Research workflow, provenance, and reuse

Applied AI Research Translator turns research inputs into traceable claims, bounded tasks, and decision records subject to human review.

Each project maintains its own scope, versions, validation status, and releases. Reuse must preserve source dependence, missingness, evidence cutoffs, and exact-version provenance. Shared organizational ownership supplies no additional validity to a method or result.

Start with the project's research-status statement, then inspect its versioned release, sources, and validation instructions. Use its contribution and correction process. Cite the authors and exact artifact version.


Founded by Mark Julius Banasihan. Independent replication and field studies remain necessary to establish broader reliability and practical benefit.

Every decision is a Node. Every standard is a Norm.

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  1. governed-decision-intelligence governed-decision-intelligence Public

    Defines the decision layer for AI systems where deployment outcomes are governed, recorded, and reconstructable. 5th conforming implementation of draft-farley-acta-signed-receipts (IETF).

    Python 3

  2. applied-ai-research-translator applied-ai-research-translator Public

    Governed research-to-decision translator for applied AI: safety-policy intake, claim extraction, bounded tasks, human gate, and audit-ready decision records.

    Python 1

  3. rgds rgds Public

    A reference implementation for human-governed, defensible phase-gate decisions in regulated environments (non-agentic, schema-validated).

    Python 1

  4. rgds-ai-governance rgds-ai-governance Public

    Working AI Assistance Governance method/profile for bounded AI participation, assigned human authority, and structural/substantive dependency assessment.

    Python 1

  5. human-influence-telemetry human-influence-telemetry Public

    Open documentary assurance method for evaluating whether human authority retained practical force in AI-mediated institutional decisions.

    Python 1

  6. trust-autonomy-evidence trust-autonomy-evidence Public

    Evidence architecture for justified reliance and practical human control in AI-mediated decisions.

    Python 1

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