ART-AI exists to educate interdisciplinary professional experts to make the best, and safest, use of artificial intelligence (AI) and to explore the opportunities, challenges and constraints presented by the diverse range of contexts for AI.
The University of Bath Campus
ART-AI offers a uniquely interdisciplinary doctoral training approach, recruiting students from a range of backgrounds across computer science and artificial intelligence, engineering and technology, and humanities and social sciences.
ART-AI draws together a wide range of topics: from algorithms to ethics; robotics safety to computational and public policy; probabilistic machine learning to symbolic AI; provenance, transparency and uncertainty quantification to intelligibility and trust in heterogeneous intelligent systems; reinforcement learning to emotion in human-machine interaction; and many others.
Scott Wellington, along with fellow ART-AI students, Rob Clarke, Doug Tilley, Syeda Gulnoor Zahra and Todd van Steenwyk, attended the CogX Festival 2022. Scott has also recently come back from visiting the AI Department of the Luleå University of Technology (LTU).
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UKRI’s Global Research and Innovation Programme (GRIP) has supported a three-week visit by ART-AI student Deborah Morgan to research centres, summits and academics across the US working in fields directly related to her PhD and wider research interests.
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View the recording of our ART-AI Seminar with Raluca Crisan, Co-founder & Chief Technology Officer of Etiq, entitled ‘On the Path of Building Responsible Machine Learning: ML Testing and Monitoring’.
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Our students are looking forward to once again spending 3 days at a residential Writing Retreat at the Ammerdown Retreat Centre this summer.
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AI governance: from principle to practice is an online invitation-only roundtable event, happening on the 8th September 2022, focusing on contemporary and future AI regulation.
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A Statistical Learning and Differential Privacy Workshop is taking place at the University of Bath on the 12th-13th September 2022.
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