Our Work
This workshop aims to bring together the best philosophical work on normative questions raised by computing, and in addition to identify and connect early career scholars working on these questions. It will feature papers that use the tools of analytical philosophy to frame and address normative questions raised by computing and computational systems.
Read MoreA new paper by Andrew Smart and Atoosa Kasirzadeh in AI & Society titled "Beyond Model Interpretability: Socio-Structural Explanations in Machine Learning" explores the importance of social context in explaining machine learning outputs.
Read MoreWith former acting White House Office of Science and Technology Policy director, Alondra Nelson, Seth argued against a narrow technical approach to AI safety, calling instead for more work to be done on sociotechnical AI safety, that situates the risks posed by AI as a technical system in the context of the broader sociotechnical systems of which they are part.
Read MoreThe fall Workshop on Sociotechnical AI Safety at Stanford (hosted by Stanford's McCoy Family Center for Ethics in Society, the Stanford Institute for Human-Centered Artificial Intelligence (HAI), and the MINT lab at the Australian National University), recently brought together AI Safety researchers and those focused on fairness, accountability, transparency, and ethics in AI. The event fostered fruitful discussions on inclusion in AI safety and complicating the conceptual landscape. Participants also identified promising future research directions in the field. A summary of the workshop can be found here, and a full report here.
Read MoreIn this piece for Tech Policy Press, Anton Leicht argues that future AI progress might not proceed linearly and we should prepare for potential plateaus and sudden leaps in capability. Leicht cautions against complacency during slowdowns and advocates for focusing on building capacities to navigate future uncertainty in AI development.
Read MoreThe Machine Intelligence and Normative Theory (MINT) Lab has been awarded a US$480,000 grant from the Survival and Flourishing DAF (Donor Advised Fund). This gift will support research by the MINT lab into sociotechnical AI safety—the integration of multidisciplinary perspectives with technical research on mitigating direct risks caused by AI systems operating without immediate human supervision.
Read MoreAndrew Smart and colleagues presented a tutorial session at FAccT 2024 that aims to broaden the discourse around AI safety beyond alignment and existential risks, incorporating perspectives from systems safety engineering and sociotechnical labour studies while emphasising participatory approaches.
Read MoreAs AI continues to permeate every aspect of our society, the evolution of adversarial machine learning from a niche academic field to a critical component of global cyber security underscores the significance of this research.
Read MoreSeth presented a tutorial on the rise of Language Model Agents at the ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT), a computer science conference with a cross-disciplinary focus that brings together researchers and practitioners interested in fairness, accountability, and transparency in socio-technical systems.
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