Abstract
An autonomous pipeline that both detects issues and acts on them (filing tickets, refreshing a reference corpus, adopting a new rule) will, almost as soon as it does more than one kind of consequential thing, produce more than one kind of moment where its own judgment is not trustworthy enough to act on unsupervised. The conventional response is a bespoke review mechanism per kind of uncertainty, added piecemeal as each is discovered during development: a findings-review screen here, an admin flag there, a Slack thread for whatever comes up next. This disclosure documents a mechanism from a production website-accessibility scanning and remediation system that instead recognizes a shared shape underneath three, structurally different, sources of machine uncertainty, generated by three different upstream components on three different cadences, and gates all three behind one queue, one record schema, one disposition vocabulary (confirm or dismiss), and one notification path, while keeping the actual effect of a confirmation genuinely different per kind: filing a ticket, advancing a knowledge-base version, or adopting a new grounding fact for future judgment. The mechanism is illustrated with a real, dated worked example generated against a live deployment: a run that produced 20 confirmed findings, of which exactly 2, both flagged critical severity by an independent, deterministic rule, were held for human confirmation while the remaining 18 were filed automatically, all recorded in the same generated report.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Panday, Vipul, "Single-Queue, Multi-Kind Escalation: One Human-Confirmation Gate for Three Structurally Different Automated Judgments in an Autonomous Compliance Pipeline", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/11591