Autonomous technologies
Alternative labels
Autonomous computer systems
Automated decision-making
Collection
Featured
The ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S) brings together universities, industry, government, and the community to support the development of responsible, ethical and inclusive automated decision-making. ADM+S draws on the humanities, social and technological sciences. ADM+S research is designed to expand...
Report
Who do AI agents work for?
This report argues that policymakers must confront a fundamental choice as the agentic web transforms the economy: whether artificial intelligence agents must primarily represent the interests of users or will be permitted to serve the interests of the corporations that deploy them. It finds that the potential for exploitation is great and outlines recommendations for...
Report
Making agentic AI work for government: a readiness framework
Agentic artificial intelligence (AI) is driving a fundamental shift in capability, allowing systems to autonomously execute end-to-end, multi-step workflows. This report applies a novel, department agnostic perspective on government activities. It provides a clear approach to assess where agentic AI can deliver the greatest public value and what risks must be managed before deployment at...
Report
Relational futures: Indigenous sovereignty and the governance of artificial intelligence (AI)
This report presents findings from the Relational Futures project, an Indigenous led study examining how Aboriginal and Torres Strait Islander peoples are encountering and responding to artificial intelligence (AI), including generative systems, automated decision-making tools, and AI companions. It demonstrates that artificial intelligence is not only a technical issue, but a relational, cultural and political...
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.