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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.26075 |
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| _version_ | 1866913071121825792 |
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| author | Pan, Shidong Gong, Haochen Xia, Boming Sun, Xiaoyu Xu, Xiwei Zhu, Liming |
| author_facet | Pan, Shidong Gong, Haochen Xia, Boming Sun, Xiaoyu Xu, Xiwei Zhu, Liming |
| contents | Governments increasingly deploy AI in public services, making transparency essential for accountability and public trust. Australia's Standard for AI Transparency Statements (AITS) requires government bodies to disclose how AI is used in practice, yet little empirical evidence exists on how these requirements are realised in documents. This paper presents the first government AITS dataset, dubbed AITS-101, and provides the first systematic analysis of their content. Using stylometric, quantitative, and qualitative document analyses, we examine disclosure coverage, structure, and recurring patterns. Our findings reveal substantial variation in AI-related practice disclosure, highlight gaps between policy intent and implementation, and inform the design of more effective public-sector AI transparency standards. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_26075 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | The Creation and Analysis of Government AI Transparency Statements in Australia Pan, Shidong Gong, Haochen Xia, Boming Sun, Xiaoyu Xu, Xiwei Zhu, Liming Computers and Society Governments increasingly deploy AI in public services, making transparency essential for accountability and public trust. Australia's Standard for AI Transparency Statements (AITS) requires government bodies to disclose how AI is used in practice, yet little empirical evidence exists on how these requirements are realised in documents. This paper presents the first government AITS dataset, dubbed AITS-101, and provides the first systematic analysis of their content. Using stylometric, quantitative, and qualitative document analyses, we examine disclosure coverage, structure, and recurring patterns. Our findings reveal substantial variation in AI-related practice disclosure, highlight gaps between policy intent and implementation, and inform the design of more effective public-sector AI transparency standards. |
| title | The Creation and Analysis of Government AI Transparency Statements in Australia |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2604.26075 |