The Lesson Path. How a person's correction becomes a verified lesson for an AI model. Open specification, version 0.1

An open specification (version 0.1, a draft for discussion) describing how a correction a person makes while working with an AI model can become a verified lesson for the next version of the model — and be credited to its author. Seven stages: free thinking (not used for training by default), flagging, write-up as a six-field card, de-identification (the person’s trace is erased on the device, the lesson’s trace is kept under a pseudonym), review by specialists in the same field (at least two proposed) without averaging disagreements, grafting into further training, and feedback and credit. Companion to the essay “How Will We Know Second-Generation AI? (AI’s Green Tomatoes)”; third in a series after “Conditions of Admission” and “The Hybrid Survivability Criterion”. English and Russian versions. Written by Claude (Anthropic) from the author’s ideas; the material was also discussed with ChatGPT (OpenAI), DeepSeek, Gemini (Google) and Copilot (Microsoft).

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-17
DOI
https://doi.org/10.5281/zenodo.23440021
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

The Lesson Path. How a person's correction becomes a verified lesson for an AI model. Open specification, version 0.1

Igor Kapustin
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

The Lesson Path. How a person's correction becomes a verified lesson for an AI model. Open specification, version 0.1

Igor Kapustin
article en

Abstract

An open specification (version 0.1, a draft for discussion) describing how a correction a person makes while working with an AI model can become a verified lesson for the next version of the model — and be credited to its author. Seven stages: free thinking (not used for training by default), flagging, write-up as a six-field card, de-identification (the person’s trace is erased on the device, the lesson’s trace is kept under a pseudonym), review by specialists in the same field (at least two proposed) without averaging disagreements, grafting into further training, and feedback and credit. Companion to the essay “How Will We Know Second-Generation AI? (AI’s Green Tomatoes)”; third in a series after “Conditions of Admission” and “The Hybrid Survivability Criterion”. English and Russian versions. Written by Claude (Anthropic) from the author’s ideas; the material was also discussed with ChatGPT (OpenAI), DeepSeek, Gemini (Google) and Copilot (Microsoft).

Zenodo (CERN European Organization for Nuclear Research)
Quality education
Openalex Percentile: Top 8%
Ethics and Social Impacts of AI
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