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Artificial Intelligence (AI)

Alternative labels
Generative AI (GenAI)
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Artificial Intelligence (AI)
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Report

Artificial intelligence, cognitive offloading and implications for education


This report investigates the challenge driven by the rapidly expanding use of artificial intelligence (AI) in schooling: the risk that students will outsource too much of the cognitive work that is crucial to establishing knowledge, skill and ‘thinking infrastructure’. The report includes specific recommendations for policy and teaching and learning strategies.
Briefing paper

Governing in turbulent times: how to redesign the ‘strategy stack’ for the late 2020s


National governments are struggling to be strategic in the late 2020s. This briefing note argues that this is not mainly a leadership flaw; it is an institutional design problem in the centre of government. The paper looks at current and past examples of strategy teams in governments and proposes designs for future ones.
Report

Perceived risk of victimisation by artificial intelligence enabled crimes


In the past 10 years, there has been a rapid proliferation of publicly available tools and applications using artificial intelligence (AI). Using Australian data, this report measured the perceived frequency of AI-enabled crimes and which specific technologies pose the greatest perceived risk of victimisation. The findings highlight priority areas for industry safeguards and public education.
Report

AI 2035: Australia’s opportunity playbook

Annie Phillips

This playbook proposes that Australia faces a simple choice: it can be an artificial intelligence (AI) leader, or an AI follower. It presents a practical path forward built on three foundations – economic growth, security and setting up Australia as a world-leader in AI – to secure Australia’s prosperity in the AI era ahead.
Report

Building pro-worker artificial intelligence


This paper defines pro-worker technologies, including artificial intelligence (AI), as technologies that make human skills and expertise more valuable by expanding worker capabilities. It presents a conceptual framework that distinguishes among five categories of technological change. The paper considers nine ways that public policy could channel advances in AI in a pro-worker direction.