Library
Everything here links to its original source: the publisher's page, the journal record, the LinkedIn article or the podcast episode. The short descriptions are this website's own summaries. Book pages summarise each book from its published description and contents; they are not full-text reviews.
Concise summaries of published research and commentary on AI from many institutions, compiled for policymakers, executives and engaged readers. A synthesis of others' work rather than original research.
Cybersecurity explained for boards and executives: how the threat landscape evolved, what compliance requires, how threats differ from vulnerabilities, and what an informed executive response looks like.
A guide for leaders and practitioners to governing AI through principles, ethics and structured assessments: the history and legal setting of AI, eight guiding principles with ways to uphold each, and assessment approaches for organisations.
A workbook that turns AI governance from a compliance burden into a delivery discipline: mapping an organisation against an AI technical standard, an implementation methodology, procurement and contract governance, and oversight across the AI lifecycle.
A guide to the state of AI governance in Australia at the time of writing: the roles of federal, state and territory government, industry, civil society and academia; Australia's AI ethics principles; and what an organisation investing in AI should be mindful of.
A second volume of summaries of published work on AI, geopolitics, regulation and technology, compiled for readers who need the substance without the reading time. A synthesis of others' work rather than original research.
A qualitative study of a large public-sector IT project whose cost overrun exceeded AUD 1 billion, drawing on 181 interviews and 5,000 pages of project data. It develops a theory of situational incompetence and proposes an instrument for gauging leadership competence as project size and complexity grow.
Why do IT projects still fail when the causes are well known? Using multi-grounded theory on a major Australian IT project, this paper examines the lack of domain expertise among senior management and vendor representatives, and reads the decisions of the people involved through the Kruger-Dunning effect.
Foundation models are becoming infrastructure; the defensible work lies in engineering machine intelligence into systems that do real work, with the workflow, evaluation and context that a supplier's model cannot absorb.
A reading of a major consultancy's report on agentic shopping through the parable of the blind men and the elephant: each description of the market is accurate and none alone describes the whole.
On a government order restricting access to frontier AI models, and what such a decision reveals about competence at the top of government when the people deciding cannot tell what they are deciding about.
A response to the question of who owns the profile an AI assistant keeps on you: the answer, the author argues, is architectural, and turns on where that profile is stored and who controls it.
Argues that a merchant's terms for AI-agent purchases and Europe's payment rules converge on one requirement, a per-transaction record of what the buyer actually authorised, and that the card networks' new agent protocols verify intent at the payment end rather than where the buyer's evidence has to live.
Examines what Mastercard's Verifiable Intent and Visa's Trusted Agent Protocol actually do, layer by layer, and where each stops short of proving what an agent was instructed to do.
Where the evidence has to live when an AI agent buys the wrong thing: the instruction, the agent's reasoning under it, and the decision, all of which sit upstream of the payment. A practical account of evidentiary design for agent transactions.
Expert witnesses serve the court, not the party paying them, yet the rules differ sharply across major jurisdictions. The episode surveys those frameworks and asks how AI is beginning to reshape expert testimony.
On the growing number of documented cases of lawyers filing fabricated, AI-generated citations, and the governance gap between deploying AI tools and professional competence in using them.
How courts in different jurisdictions have responded to generative AI, from categorical prohibitions on AI-generated witness evidence to permissive positions, and what that divergence means for anyone preparing evidence.
Why large projects fail, drawing on the research behind the author's doctorate and the patterns that recur across failed IT programmes.
A companion to the book: the Australian standards and regulatory landscape for AI as it stood in late 2024.
On domain expertise in leadership: why organisations led by people who understand the work make better decisions, a theme that runs through the author's project-failure research.
Whether AI projects will repeat the failure patterns of large IT projects, and what governance would have to look like to prevent it.
Where cybersecurity governance and AI governance meet, for executives who are accountable for both.
What government agencies should weigh before investing in AI, and how public-sector project governance shapes the outcome.