For lecturers + TAs

Using Policy Window in your AI-governance course

Policy Window is a free, open-licence (CC BY 4.0 content / MIT schema) evidence catalog covering 26+ AI-governance instruments across 24 topics. This page is the instructor-oriented brief: what works as a classroom resource, what doesn't yet, and a sample reading list / assignments you can drop into a syllabus.

Honest framing: PW is an evidence-catalog reference, not a textbook. Article prose is intentionally thin (a structural choice — see methodology §1); pair PW articles with traditional secondary sources for full-depth reading. Where PW is strongest is structured cross-jurisdiction comparison, per-cell pinpoint citation discipline, and permanent date-pinned URLs (?asOf=) for citation stability.

What PW is well-suited to

Comparative-method seminars. The 26 × 24 coverage matrix with a Silence Index trains the habit of naming what regulators do not say, not just what they do.
Cite-checking discipline.Every coverage cell carries a pinpoint citation (e.g. "Art. 5(1)(h) prohibition + Art. 26(10) post-hoc rules") so students learn that "EU AIA governs biometric_id" is not a sufficient citation — the article is.
Reproducible assignment workflow. ?asOf=YYYY-MM-DD permanent URLs eliminate "the page changed between when I read it and when I cited it" disputes between students and TAs.
Critique-as-pedagogy. The methodology §11 (Limits & blind spots) page explicitly names the catalog's structural biases (instrument-centric ontology, Western coverage asymmetry, no Global-South editorial representation yet). PW is citable as an object of critique.
Coverage Games as a class exercise. The inter-rater methodology at /wiki/coverage-games is replicable as a 3-week mini-assignment with student raters — see the sample below.

What PW does not replace

Analytical prose.A typical grad-seminar reading is 3,000–8,000 words; a PW article is ~200–400 words plus a matrix. Pair with traditional secondary sources (Veale & Borgesius 2021, Bommasani et al. 2021, Gebru 2024, etc.) for the "why" behind the "what".
Authoritative primary text. PW links to primary sources; it does not replicate them. Students still need to read EUR-Lex / regulations.gov for the full statutory text.
Non-English reading. English-only until funded translation partnerships land. For Chinese / Brazilian / Indian readings, pair with native-language primary sources.
Independent-editorial-warranty citations. The editorial board is 1 of 6 slots filled (see /wiki/editorial-board). For thesis-defence-grade work, recommend pairing the PW citation with the underlying primary source rather than citing PW as authority.

Sample 3-week reading list

Week 1 — Foundation models / GPAI

/wiki/foundation_models — topic matrix
/wiki/eu-ai-act — the most-cited instrument, has Q/A/C populated
/wiki/compare — try ?a=eu-ai-act&b=us-eo-14110 for the comparative pane
Pair with: Bommasani et al. 2021, On the Opportunities and Risks of Foundation Models (the technical-debate side PW does not centre)

Week 2 — Biometric ID / law-enforcement carve-outs

/wiki/biometric_id — topic with EU Art. 5(1)(h) prohibition + Art. 26(10) carve-out pinpoint
EU AIA + CN GenAI side-by-side via /wiki/compare
/wiki/for-advocates — read as a meta-text about how PW frames advocacy-relevant topics
Pair with: Algorithmic Justice League primary report

Week 3 — Silent regimes / Coverage Games

/wiki/coverage-games + the 2026-q2 case study
/wiki/methodology §11 "Limits and blind spots"
Run a mini Coverage Game in class — see assignment 3 below

Sample assignments

Pinpoint extraction. From /wiki/eu-ai-act, identify the article that governs deepfakes; then find the China-GenAI counterpart cell; explain why PW labels one "governs" and the other "implicit." (Trivially gradable: TA verifies via the ?asOf=YYYY-MM-DD permanent URL.)
Silence audit.Pick a contested topic in the Silence Index top-10. For one of the silent cells, find a primary source (regulator publication, draft bill, civil-society submission) that arguably should change PW's classification. Submit a [topic-gap] GitHub issue draft as your assignment. (Teaches use-of-evidence + meta-critique simultaneously.)
Mini Coverage Game. Working in pairs, blind-classify 10 cells of /wiki/training_data from primary sources. Compare calls. Write up the disagreement matrix and propose a rubric refinement. (Models methodological-replicability in 3 weeks.)

Citation guidance for students

The recommended citation form:

Policy Window. (YYYY). Article title. Retrieved YYYY-MM-DD from https://policywindow.org/wiki/[slug]?asOf=YYYY-MM-DD

The ?asOf=YYYY-MM-DD parameter pins the article to a specific snapshot stored in ArticleRevision. A green banner on the page confirms the pin; an amber banner indicates no snapshot was captured for that date (request a backfill via the page's "Report a problem" link).

Reference-manager (Zotero / Mendeley / EndNote) import works via the Google Scholar Highwire-Press meta tags embedded on every article page. CSL-JSON is available via the "Cite this" widget on every article. DOIs are on the Q4 2026 roadmap.

What we want from instructor adoption

Topic-gap reports.If your course covers a topic PW doesn't (state-level employment laws, algorithmic-management in gig work, indigenous data sovereignty), file an issue or open a PR. Student-found gaps are some of the most valuable inputs.
Coverage Games student data. If you run a mini Coverage Game in class and your students agree to share their classifications, those become public-record inter-rater data that PW will credit. This is the most scalable path to a higher-N reliability estimate.
Translation contributions. If your cohort includes native speakers of Portuguese / Spanish / Hindi / French / Arabic interested in translating PW articles (with appropriate editorial review), reach out via the wiki home — translation partnerships are the unlock for non-English readership.

Using Policy Window in your AI-governance course

What PW is well-suited to

Comparative-method seminars. The 26 × 24 coverage matrix with a Silence Index trains the habit of naming what regulators do not say, not just what they do.

Cite-checking discipline.Every coverage cell carries a pinpoint citation (e.g. "Art. 5(1)(h) prohibition + Art. 26(10) post-hoc rules") so students learn that "EU AIA governs biometric_id" is not a sufficient citation — the article is.

Reproducible assignment workflow. ?asOf=YYYY-MM-DD permanent URLs eliminate "the page changed between when I read it and when I cited it" disputes between students and TAs.

Critique-as-pedagogy. The methodology §11 (Limits & blind spots) page explicitly names the catalog's structural biases (instrument-centric ontology, Western coverage asymmetry, no Global-South editorial representation yet). PW is citable as an object of critique.

Coverage Games as a class exercise. The inter-rater methodology at /wiki/coverage-games is replicable as a 3-week mini-assignment with student raters — see the sample below.

What PW does not replace

Analytical prose.A typical grad-seminar reading is 3,000–8,000 words; a PW article is ~200–400 words plus a matrix. Pair with traditional secondary sources (Veale & Borgesius 2021, Bommasani et al. 2021, Gebru 2024, etc.) for the "why" behind the "what".

Authoritative primary text. PW links to primary sources; it does not replicate them. Students still need to read EUR-Lex / regulations.gov for the full statutory text.

Non-English reading. English-only until funded translation partnerships land. For Chinese / Brazilian / Indian readings, pair with native-language primary sources.

Independent-editorial-warranty citations. The editorial board is 1 of 6 slots filled (see /wiki/editorial-board). For thesis-defence-grade work, recommend pairing the PW citation with the underlying primary source rather than citing PW as authority.

Sample 3-week reading list

Week 1 — Foundation models / GPAI

/wiki/foundation_models — topic matrix
/wiki/eu-ai-act — the most-cited instrument, has Q/A/C populated
/wiki/compare — try ?a=eu-ai-act&b=us-eo-14110 for the comparative pane
Pair with: Bommasani et al. 2021, On the Opportunities and Risks of Foundation Models (the technical-debate side PW does not centre)

Week 2 — Biometric ID / law-enforcement carve-outs

/wiki/biometric_id — topic with EU Art. 5(1)(h) prohibition + Art. 26(10) carve-out pinpoint
EU AIA + CN GenAI side-by-side via /wiki/compare
/wiki/for-advocates — read as a meta-text about how PW frames advocacy-relevant topics
Pair with: Algorithmic Justice League primary report

Week 3 — Silent regimes / Coverage Games

/wiki/coverage-games + the 2026-q2 case study
/wiki/methodology §11 "Limits and blind spots"
Run a mini Coverage Game in class — see assignment 3 below

Sample assignments

Pinpoint extraction. From /wiki/eu-ai-act, identify the article that governs deepfakes; then find the China-GenAI counterpart cell; explain why PW labels one "governs" and the other "implicit." (Trivially gradable: TA verifies via the ?asOf=YYYY-MM-DD permanent URL.)

Silence audit.Pick a contested topic in the Silence Index top-10. For one of the silent cells, find a primary source (regulator publication, draft bill, civil-society submission) that arguably should change PW's classification. Submit a [topic-gap] GitHub issue draft as your assignment. (Teaches use-of-evidence + meta-critique simultaneously.)

Mini Coverage Game. Working in pairs, blind-classify 10 cells of /wiki/training_data from primary sources. Compare calls. Write up the disagreement matrix and propose a rubric refinement. (Models methodological-replicability in 3 weeks.)

Citation guidance for students

The recommended citation form:

Policy Window. (YYYY). Article title. Retrieved YYYY-MM-DD from https://policywindow.org/wiki/[slug]?asOf=YYYY-MM-DD

What we want from instructor adoption

Topic-gap reports.If your course covers a topic PW doesn't (state-level employment laws, algorithmic-management in gig work, indigenous data sovereignty), file an issue or open a PR. Student-found gaps are some of the most valuable inputs.

Coverage Games student data. If you run a mini Coverage Game in class and your students agree to share their classifications, those become public-record inter-rater data that PW will credit. This is the most scalable path to a higher-N reliability estimate.

Translation contributions. If your cohort includes native speakers of Portuguese / Spanish / Hindi / French / Arabic interested in translating PW articles (with appropriate editorial review), reach out via the wiki home — translation partnerships are the unlock for non-English readership.