Abstracts

Scope 3 emissions: What do they mean for IT?

Paul Rock, Consultant

Most education institutions have targets - set externally or internally - to reduce
their carbon emissions. This short session will explore the three key emissions 'scopes', helping us better understand their impact and consider some of the most effective ways to reduce the environmental impact of IT, particularly Scope 3 emissions.

 

Shaping agendas for the more sustainable use of digital technologies in universities

Susan Brown, Lecturer and Programme Director of Education for a Sustainable Environment, University of Manchester

Digital technology has been characterised both as socio-environmental friend and a socio-environmental foe (Greenwood & Houghman, 2015). There is significan research and debate around its role as friend in advancing education and much less around its role as foe (Selwyn, 2024).
This talk argues the need to recognise the negative socio-environmental impacts of digital technology within HE and to shape agendas for the more restrained and discerning use of digital technology.
In making this case, it draws on ideas from the digital degrowth, rewilding technologies and computing within limits movements. It argues these movements offer foundations for greater creative and sustainable thinking around digital technology use in universities.

 

AI and Sustainability: Environmental and Social Impacts

Dr Lorna Richardson, Lecturer in Digital Media and Cultures, University of East Anglia

This talk explores the hidden impacts of artificial intelligence technologies, from carbon emissions and water consumption, to e-waste, geopolitics, and ethical concerns around rare metals. This talk examines the growing ecological footprint of the 'AI revolution' while highlighting promising solutions and the crucial balance between technological advancement and panetary stewardship.

 

Remote Working: The Future or a Flawed Fantasy?

Paul Rock, Consultant

 

Using local AI computer to offset cloud AI sustainabilty

Trevor Baxter, King's College London

This discussion's premise is that not all AI queries require the largest models running on the most powerful cloud AI systems. Many can operate effectively on smaller local models using more sustainable machinery, such as Arm-based computers. By choosing where to run a query and having systems that escalate to a more powerful cloud system only when necessary, AI usage can become more environmentally friendly while still delivering results.

 

Sweating your hardware assests

John Vass-de-Zomba, IT Environmental Sustainability Manager, University of Manchester, Chris McEvoy, Head of Enterprise Services, Keele University, David Barrett, Head of Desktop, Print and Support, University of York

Seeking to gain more usage out of hardware is a common response to the demands for optimised budgets and savings realisation. This is often the case with end user devices but is also true for what we run in data centres. Deciding which hardware to utilise for longer and how to do that requires consideration of risk, cost, performance, and sustainability. Our panel brings toether HE IT professionals experienced in the field, to share their insights on what factors to consider when looking to extend device lifespans, and to provide examples of what they believe best practice sustainable lifecycle management looks like.