About this tracker

Under the Policy for the responsible use of AI in government, Commonwealth agencies have had to publish AI transparency statements since February 2025. This project keeps a faithful, dated record of those statements and makes the changes legible.

How it works

Every day, an automated program visits each agency’s statement, saves a copy, and notes anything that has changed since the day before. Over time this builds a complete, dated history of how every statement has evolved, down to the wording. This site presents that history — it adds no commentary of its own beyond the analysis described below.

Origins

This tracker began in the audience. As Senator Katy Gallagher launched the Australian Public Service’s AI Plan on 11 Nov 2025, Ben Swift opened a laptop and started archiving the agencies’ transparency statements then and there. That is why the record opens when it does, and why the statements’ first nine months, before the project was watching, fall outside it. What that start point means for the figures is set out in how to read the data.

Methodology

For a plain-language guide to what the scores and colours on this site mean, and what they don’t, see how to read the data. The notes here are the technical method behind them.

• Timeline. Each change is read straight from git. Spurious scrape churn that is later reverted, and pure reformatting, are collapsed out; commits the maintainer flagged as noise are hidden by default. Bulk imports are shown as “first tracked” rather than “published”, since we don’t know the true publication date.
• Propagation is detected lexically: passages are normalised (links, markup, punctuation and case removed) and matched across agencies, with a separate pass for canonical template phrases. We only assert that a passage co-occurs across statements — never who copied whom — though passages also found in the DTA’s own statement are marked.
• Originality is the share of a statement’s text (by length) that is not shared with other agencies or drawn from template language. The DTA scores low because it is the template source, so it is labelled accordingly.
• Similarity uses OpenAI text-embedding-3-small vectors and cosine distance. Embeddings are cached by content hash, so a statement is only re-embedded when its text changes.

Related work

Plenty of people study these statements; as far as we know, nobody else tracks how they change. The first systematic analysis of the Australian corpus — Pan et al. (2026), who assembled the AITS-101 dataset — and an audit by the ADM+S Centre both read the statements as a single snapshot. The Digital Transformation Agency’s central register aspires to surface major updates but publishes no version history. The missing time axis is what this project adds.

The method is borrowed rather than invented. Longitudinal corpora of privacy policies — notably the Princeton–Leuven corpus — and terms-of-service trackers have long committed each snapshot to git and diffed it; we point the same technique at government AI transparency statements. The nearest efforts abroad track AI use rather than the statements themselves — registers like the UK’s Algorithmic Transparency Recording Standard and the Amsterdam and Helsinki algorithm registers — or score transparency over time, like Stanford’s Foundation Model Transparency Index. None diffs the text of agency statements.

Caveats

Scraping is imperfect: site redesigns, bot-blocks and PDF extraction can introduce noise, and the coverage classification (published / not yet / exempt) is a best-effort reading of each agency’s obligations. Treat the figures as indicative, and follow the source link on any statement to check the original.

Licensing

The scraper and this site are released under the MIT License. The statement text belongs to the respective agencies; most Australian Government content is licensed CC BY 4.0, but check each agency’s site for specifics.

112 statements, 436 tracked changes, 112 embedded. Built 12 June 2026 from 85c1e2e.