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How are you using AI in your day-to-to day work?

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Share ideas around AI might help make processes more efficient.

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What is your interest in AI in research?

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What is your interest in AI in research?

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Maybe share you role, or why you joined the community.

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What areas to you need support or guidance with?

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Do you need training, or training to be made available to your institutions? If so, in what?

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How AI should be use in your role or institution.

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Maybe share concerns around bias, sustainability or copyright/IPR.

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Does your institution provide any research specific AI tools?

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Ideas around AI might significantly transform or change an activity.

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I am concerned about the amount of energy and water AI uses, and whether this is taken into account in institutions' sustainability plans

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ChatGPT Energy Consumption Visualized - BEUK

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One of our priority projects is a pilot tool that uses multiple AI models to automatically "simulate" critical peer reviews of new research funding applications. The tool is based on modelling criticisms from past reviewers using historical data, which is used to create "benchmarks" for critiquing new draft applications. The tool has been deployed as a beta/pilot project, as a "self-serve" resource, accessed directly by faculty members to support their grant writing.

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Much of the AI demonstration and discussion in education revolves around neat things people have found. The 'show and tell' format is useful (and often an eye opener on what can be done) but there is room for a deeper discussion on the future of learning, assessment and preparation for a working world where AI is a very prominent feature. I hope we have some space to explore these slightly more philosophical things (without it just being a hot air talking shop of course).

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I'm dubious about the idea that AI is er, intelligent. I'm not sure the extent to which we might be misleading ourselves if we regard these developments as intelligent in anyway rather than something like impressively flexible algorithms - impressive, but nothing resembling autonomous thought.

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For each step in the entire research process including research administration to be supported by AI. 

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For each step in the entire research process including research administration to be supported by AI. 

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See my blog post; Improving interdisciplinary understanding using AI – Southampton Web and Data Innovation Team

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Improving interdisciplinary understanding using AI – Southampton Web and Data Innovation Team

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As with all IT jobs, we’re encouraged to use “more AI” without anybody being entirely sure what it can bring to the party.

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I'm concerned about "Gen AI creep". What I mean by that is Apple Intelligence on Macs, Copilot inbuilt in W11, Copilot within M365 apps, etc. I have been working on policies to help protect our data. Saying something like "don't put personal data into Gen AI tools" makes sense when it's the manual action of accessing a website and constructing an input prompt. However (for example) when it's embedded into Outlook and you're simply right-clicking an email and asking it to summarise, there is naturally personal data within that email. So we need to stay on our toes and check out the terms behind these embedded tools as they pop up. It was relatively easy to construct policies when using AI tools was quite an intentional action but now it's increasingly embedded into lots of things we're already using on a daily basis, it becomes increasingly difficult to word policies and guidance for staff and keep data safe - and increasingly difficult to reassure that our data is indeed safe...

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What is appropriate, what is not? When it is not appropriate how do you tackle this i.e. supervisor suspects a thesis undergoing examination has been produced using AI (something not agreed to) how do you investigate this as misconduct? Feels like a minefield!