Since publishing the ILRL Public Evaluation and Findings Project, I have created a public ILRL introduction and organized the method into a simple continuation path:
Conversation → editable review → human-AI interaction receipt → portable checkpoint → later continuation → outcome receipt
Public site: https://innovation-lineage-record-live.rrbberkovich.chatgpt.site/
I have also prepared public documentation for participation, evidence states, adaptive connections, contribution history, and correction handling. These materials are intended to support a small, privacy-safe outside-user evaluation. They do not establish independent validation yet.
The next measurable step is to invite a small number of adult participants to complete one continuation cycle. I will preserve what they received, what they understood, what confused them, what they corrected, and whether the checkpoint helped them continue later. Successful and unsuccessful outcomes will both remain part of the findings.
The Manifund grant would support the work described in the proposal: a sanitized public evaluation corpus, outside-reader sessions, adversarial cases, scoring, accessible demonstrations, privacy review, and a public findings report. Private conversations, credentials, and private lineage archives will not be published.
Current evidence state:
ESTABLISHED: the public site and core workflow exist.
READY: participant-protection and evaluation documents are being prepared.
OPEN: outside-user continuation results and Manifund funding.
NOT_MEASURED: broad usability, independent validation, market demand, and commercial value.
I welcome questions about the evaluation design, privacy boundary, scoring plan, or intended public benefit.
— Richard Ryan Berkovich