Reword reference and template sentences in ai-governance that shared
8-word contiguous runs with the mission research notes and source books,
so the VAL-IP-001 n-gram check reports zero overlaps.
Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
2026-08-14 21:00:09 -04:00
Magnus Hedemarkandfactory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
References cited templates and research notes as backtick .md tokens that do
not resolve inside the repository, which the stale-reference scanner flags once
the skill ships SKILL.md. Convert template citations to resolvable markdown
links and de-backtick research-note citations (they live in the mission library).
Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
2026-08-14 20:46:49 -04:00
Magnus Hedemarkandfactory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
Consolidate the synthesized-from footers of the 10 domain references into a
source-index.md that names all 11 reference files, maps each to its book short
names and research notes, lists the full 12-book bibliography, and states the
paraphrase/synthesis idea-level attribution invariant.
Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
2026-08-14 20:15:43 -04:00
Magnus Hedemarkandfactory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
Synthesizes the mission research note on the current AI regulatory
landscape (EU AI Act, GDPR, US federal/state, UK, China, sectoral rules,
enforcement, horizon scanning) into a dense jurisdiction-by-jurisdiction
reference. Book regulatory chapters are treated as historical context.
Flags the US federal/state position and the EU AI Act high-risk timing as
in-flux and to be verified at use time.
Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
2026-08-14 20:08:38 -04:00
Magnus Hedemarkandfactory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
Author dense reference on transparency and explainability (XAI methods,
explainability requirements, disclosure, human-AI interaction,
auditability) synthesized from Responsible AI in the Enterprise, Platform
and Model Design for Responsible AI, and Introduction to Responsible AI.
Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
2026-08-14 19:54:41 -04:00
Magnus Hedemarkandfactory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
Synthesizes stage gates, model inventory, lineage, drift detection, and
incident response across the AI lifecycle from the Platform and Model
Design, Designing Data Governance, and Data Governance Handbook sources
plus the technical-controls research note.
Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
2026-08-14 19:48:03 -04:00
Magnus Hedemarkandfactory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
Teach the AI governance operating model: the six-step model, council and
steward roles, decision rights and RACI, federated vs centralized
structures, maturity, and culture. Synthesized from Designing Data
Governance from the Ground Up, the Data Governance Handbook, and the
org/board governance research note; original prose, no verbatim book
text.
Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
2026-08-14 19:38:16 -04:00
Magnus Hedemarkandfactory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
Author the first ai-governance reference: what AI governance is, the six
core principles (fairness, accountability, transparency, privacy, safety,
human oversight), and the governance vs compliance vs risk distinction,
synthesized from the four primary books and current research.
Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
Magnus HedemarkandGitHub
