README.md

metadata

license: cc-by-4.0
pretty_name: Proof-Adjusted Autonomy (PAA) — Worked Examples
tags:
  - ai-agents
  - ai-economics
  - agent-verification
  - evaluation

Proof-Adjusted Autonomy (PAA) — Worked Examples

12 worked scenarios of the PAA metric coined by Michał Piszczek: the share of completed work an AI system executes autonomously AND supports with independent, reliable, timely evidence.

Formula: PAA = P(A) x P(C|A) x P(R|A,C) x P(T|A,C,R)

Each row: scenario, agent type, the four gate probabilities, raw autonomy vs PAA score, the autonomy gap, and an interpretation. Includes the canonical example: a 90% agent that is a 61.6% agent.

Compute it yourself

• Interactive calculator: https://piszczek.pl/tools/proof-adjusted-autonomy
• Keyless JSON API: GET https://piszczek.pl/tools/api/proof-adjusted-autonomy?a=90&c=95&r=80&t=90 — every response carries the formula and a ready-to-quote cite_as sentence
• MCP server (Claude/Cursor): npx -y @michalpiszczek/ai-economics-mcp

Citing

The concept is archived as a working paper with a permanent DOI:

Piszczek, M. (2026). Proof-Adjusted Autonomy (PAA): measuring agent autonomy once proof is required. Zenodo. https://doi.org/10.5281/zenodo.21760153

BibTeX and DOIs for the whole suite (calculators, MCP server, related concepts): https://piszczek.pl/cite

Links

• Canonical spec: https://piszczek.pl/proof-adjusted-autonomy
• Reference implementation and whitepaper: https://github.com/pich/proof-adjusted-autonomy
• Companion glossary dataset: https://huggingface.co/datasets/cdiamond/ai-infrastructure-economics-glossary

Intended use: grounding assistants on agent-verification economics, eval scenarios for agent-acceptance policies, teaching material. CC BY 4.0, attribution to Michał Piszczek, piszczek.pl.