Autonomy on MayaLucIA

Autonomy Agreement — A Working Template

Sat, 28 Feb 2026 19:00:00 +0100

A practical, instantiable template for an autonomy agreement between a human and a machine. This is not a document you read — it is something you instantiate, version in git, and let evolve. The commit log becomes the amendment history.

Companion to: The Missing Primitive (position paper) and Literature Survey.

What This Is

A working agreement between a human and a machine for scientific or creative collaboration. It is not a legal document. It is a shared understanding — a protocol for how we work together, how trust is built, and how autonomy is negotiated.

Literature Survey — Autonomy, Collaboration, and Knowledge Across Traditions

Sat, 28 Feb 2026 19:00:00 +0100

This survey grounds the autonomy agreement proposal in prior work across five domains: cybernetics, pedagogy, AI alignment, anthropology of knowledge, and existing ML tools. The goal is not comprehensiveness but to identify the intellectual ancestors, locate the genuine novelty, and find the blind spots.

1. Cybernetics (1940s–present)

Ashby: Requisite Variety

The Law of Requisite Variety (1956): a controller must have at least as much variety as the system it controls. The Good Regulator Theorem (Conant & Ashby, 1970): every good regulator of a system must be a model of that system.

The Missing Primitive — Autonomy Agreements for Human-Machine Collaboration

Sat, 28 Feb 2026 19:00:00 +0100

Every framework for human-AI collaboration assumes a fixed relationship: the human commands, the machine executes. This paper argues that the critical missing primitive is not better tools or smarter agents — it is a negotiated, evolving agreement between human and machine about the scope and limits of machine autonomy. We ground this proposal in cybernetics (Pask, Ashby, Beer, Bateson), pedagogy (Vygotsky, Freire, Papert), and the philosophy of tacit knowledge (Polanyi, Ryle, Dreyfus, Indian pramāṇa theory). A key observation: the pedagogy literature addresses only human-teaches-human. Human-AI collaboration creates a 2×2 matrix with four quadrants, each with different failure modes. The autonomy agreement is the first protocol designed to operate across all four — because negotiated trust and epistemic commitments are more fundamental than the direction of instruction.