Saved in:
Bibliographic Details
Main Authors: Pan, Shidong, Gong, Haochen, Xia, Boming, Sun, Xiaoyu, Xu, Xiwei, Zhu, Liming
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2604.26075
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866913071121825792
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