| EPSRC Reference: |
EP/Y030702/1 |
| Title: |
UKRI AI Centre for Doctoral Training in AI for Sustainability |
| Principal Investigator: |
Gerding, Professor EH |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Sch of Electronics and Computer Sci |
| Organisation: |
University of Southampton |
| Scheme: |
Centre for Doctoral Training |
| Starts: |
01 April 2024 |
Ends: |
30 September 2032 |
Value (£): |
8,846,359
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Energy Efficiency |
| Environmental Planning |
Transport Ops & Management |
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| EPSRC Industrial Sector Classifications: |
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| Panel History: |
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Summary on Grant Application Form |
Environmental sustainability is one of the greatest challenges the world is facing, with many organisations and countries including the UK setting ambitious targets to reduce emissions and waste and increase renewable energy production. Technologies such as artificial intelligence (AI) are seen as a key enabler to achieve these targets. This CDT will address this need by training future leaders in the application of AI to engineer a more environmentally sustainable future. Crucially, the students will not only have a fundamental understanding of AI, but they will also be able to identify the opportunities where sustainability challenges can be addressed using these tools, as well as understanding the business and social implications and needs. Stakeholder meetings and follow-up surveys have identified this type of system-level thinking as one of the key training requirements besides technical ability. Indeed, without considering People, Profit, and Planet together, solutions are unlikely to be adopted on a wide scale. Further to that, our unique selling point is that students will be trained with a view to directly respond to industry and societal challenges identified from our pool of 30 non-academic stakeholders which we will continuously refresh and grow.
Together with our network of stakeholders, we have identified 5 themes as the focus for the research: (1) Sustainable Operations and Circular Economy, (2) Sustainable Transport and Logistics, (3) Energy and Buildings, (4) AI for Biodiversity and (5) Sustainable AI. The first 4 deal with specific application areas where AI can improve environmental sustainability. For example, AI can be used to make transport more efficient including shipping and realise targets for net zero. AI can also be used to better manage energy use and production e.g. through intelligent electric vehicle charging and decentralised energy markets. Theme 5 deals with hardware, software, and social/business solutions to deal with the sustainability of AI itself. For example, ChatGPT-v3 is estimated to have cost an equivalent of over 550 tons of CO2 to train. This can be addressed by building low-powered hardware and algorithms, and understanding the quality/cost trade-offs. Interdisciplinary projects and projects that span multiple themes are particularly encouraged.
Alongside AI, sustainability is a core theme of our training, which has a range of sustainability-themed cohort activities, including innovation camps, hackathons and outreach activities, as well as regular team exercises where sustainability practices in organisations are scrutinised, re-scoped and improved. The aim is to produce a sustainability mindset whilst creating a collaborative team spirit and have an immediate impact in the operations within organisations. In addition, equality, diversity and inclusion principles are embedded throughout the CDT, from recruitment activities, to training of the management and supervisory team, as well as accommodating students with diverse backgrounds through a flexible training approach. Throughout, responsible research and innovation will be at the forefront and integrated within the training. This will be enhanced by our close collaboration with the Responsible AI (RAI) UK centre.
Whilst there are bespoke compulsory modules, a range of optional modules from 3 different faculties are offered to supplement any gaps in knowledge depending on the chosen topic of research. These range from technical subjects such as machine learning and embedded devices to economics and supply chain management. In addition, an extensive range of online and short training workshops will be available throughout the CDT, from software carpentries for data analysis to training around policy (e.g., how to engage with government and writing policy documents) and commercialisation. These training and cohort-building activities provide students with more than a PhD, and significantly enhance their employability.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.soton.ac.uk |