Project partner AfroFutures_UK ran a hugely inspiring design jam session at the Sussex Digital Humanities Lab, supporting participants to think through alternative AI futures.
This was a participatory hackathon exploring what community-oriented AI infrastructure could look like. Drawing on African and Afrofuturist thought, transfeminist futurology and CripTech, participants developed ideas around regenerative energy systems, reparative design requirements, and DIY hardware built from repurposed technology.
Huge thanks to Florence, Nikky, Olu, and Charlotte from AfroFutures_UK. Watch this space for more documentation and outputs.
DC x Sus AI Futures: AI and the Future of Sustainability Reporting
In early April, Sustainable AI Futures and Digital Catapult hosted a workshop day in London on AI and the future of sustainability reporting.
Around fifty participants across industry, academia, and policy gathered to explore the challenges of reporting on the sustainability of AI, as well as the increasing use of AI within sustainability reporting. Speakers, panellists, and session facilitators included Chanell Daniels, Jo Lindsay Walton, Melissa Gregg, Oliver Cronk, Loïc Lannelongue, Massimo Contrafatto, Jamie Riley, Justine Porterie, Alexis Normand, and Shane Brownie. Slides from the keynote and some of the activities are available here.
A couple snapshots: It was a truly interdisciplinary, multi-professional crowd, and very exciting to hear the joyful and occasionally enraged buzz in the room, as teams thought through possible future scenarios for AI and climate, and roleplayed their imaginary start-ups through the perils, pitfalls, and possibilities of the years ahead.
It was also a real pleasure to hear sustainability professionals chatting about the impact of AI on the future of their role. One view was: Yes, AI is coming for our jobs, but that is okay! Sustainability teams were never meant to be so large in the first place. If you’re in sustainability and you want to continue with somewhat similar work in the future, stick close with finance and compliance functions.
What about the use of AI within sustainability reporting? It is clear that, despite many important initiatives of convergence and alignment, the typical sustainability professional still faces a dizzying array of standards, frameworks, and reporting requirements.
A huge amount of sustainability teams’ time is taken up with data collection and reporting, while ideas for driving change get de-prioritized. A substantial amount of sustainability teams’ time is consumed by locating data, cleaning it, reconciling incompatible formats and translating it into the categories required by different reporting regimes.
There appears to be a use case for AI here, helping sustainability teams to process messy and fragmented data sources, map information onto reporting requirements, detect anomalies, and monitor changing regulations and standards. When reporting workloads are high, more ambitious ideas for organisational change can easily be deprioritised.
But even setting aside the environmental impacts of these platforms themselves, there are some big questions. GenAI appears to be a big part of the story, so naturally users are concerned about hallucination, interpretability, and accountability. Sustainability platforms are seldom transparent enough about how they are leveraging AI in their products.
When an LLM needs to draw on a data source under the developer’s control, the most widely used approach is retrieval-augmented generation, or RAG. Relevant material (probably relevant) is taken from a pre-prepared corpus and inserted into the model’s context window before it produces an answer. Retrieval is usually based on embeddings, so it can identify semantically related passages rather than relying only on exact keyword matches.
RAG can improve the relevance and evidential basis of outputs, but it does not remove the non-deterministic core of generative AI. The model may still ignore, misread, distort or embellish the retrieved material, and the quality of the result depends on how sources are selected, parsed, divided, indexed, ranked and presented, among other factors.
Crucially, RAG is often misunderstood. We have repeatedly heard it described as a form of AI that “only looks up answers in the data you give it.” But RAG does not replace generation with lookup. It retrieves material and supplies it to a generative model, which still interprets, combines and reformulates that material probabilistically. The model draws on patterns learned during training—the big, expensive training on the huge datasets scraped from the internet—rather than relying exclusively on the retrieved sources.
Research into more grounded AI systems is developing quickly. . You can equip AI with deterministic tools, you can turn down the temperature to reduce the unpredictability of outputs, you can have LLMs devoted to double-checking the outputs of LLMs. There are a great variety of RAG methods out there, all with their strengths and weaknesses. All this means it’s all the more important that any company providing AI-powered sustainability management and reporting services is transparent about which methods, if any, they are using, and how. Sharing technical detail is the only credible and ethical approach–this applies to AI across many different spaces, but sustainability reporting should certainly be leading the way.
Sustainability reporting often is a messy, approximate art, where you make do with the data you have, and prioritize moving in the right direction, rather than obsessing over measuring everything perfectly. There is a risk that this is used to justify AI-powered bodges and fudges which feel similar (“Well, humans have to make stuff up too sometimes”), but may be far more pernicious. AI offers black boxes and dilutes accountability. Its estimates, workarounds, proxies, and mistakes are not the same as human estimates, workarounds, proxies, and mistakes.
Any use of AI within sustainability reporting needs strong controls: deterministic checks, structured and traceable lineages that provide explicit links between claims and inputted evidence, clearly defined abstention or escalation rules, tools to enable human review where necessary. Above all, providers of AI-powered sustainability solutions need to be much more open about how these systems work. Methods should be presented as auditable technical documentation, not marketing copy.
And a final signal boost: research into existing climate-related reporting is underway, and DBT is interested in the experiences of companies and investors. Get in touch with climatefinresearch@iffresearch.com
Some of the insights from the day will be collected in a short publication, RAI x ESG Compass. If you’re interested in contributing, or being involved in some other way, get in touch.
We are delighted to announce that Felix Loftus will be joining SusAI Futures as a recepient of one of our artist mini-residencies.
Felix Loftus is engaged in action-research centering around contemporary relationships to the land and commoning practices, with a particular focus on how digital and network technologies can contribute to contemporary commons. His practice involves creative computing and digital fabrication with a focus on embedded electronics, permacomputing, and network commons. He works as the Specialist Technician for Web and Creative Code at Central Saint Martins and as a freelance artist and technologist. He is currently contributing to discourse on permacomputing through the London Permacomputing Club and the international community of practice.
Felix’s project will explore the possibility of locally self-hosting LLMs on upcycled devices to support the ecological stewarding of an urban green space. Stay tuned for more!
“An increasing number of studies seek to assess the net environmental impact of artificial intelligence (AI) systems, weighing both positive and negative effects. This is a critical topic, as the net impact of AI is of great societal relevance yet challenging to determine. In this article, we review current methods for the assessment of direct and indirect carbon impacts of AI systems, including those that are transferred from the more general domain of information and communication technologies. We identify common principles that are shared across the majority of frameworks and the measurement challenges that arise specifically in the context of AI. We apply our findings to a previously published case study, demonstrating that refactoring a calculation to conform to the principles identified by established frameworks has a large impact on the result. We also quantify the sensitivity of the final estimate to key parameters used in the impact calculation. Carbon impact results prove highly sensitive to methodological choices, highlighting the need for more transparent, consistent, and AI-specific approaches. Today’s frameworks fail to capture AI’s distinctive characteristics, including its indirect effects, with sufficient accuracy to inform decision-making around AI’s environmental impact.”
We are so excited to welcome Jazmin Morris and Shruthi Venkat to the Sus AI Futures project as recipients of our mini-residencies. Watch this space for news of their projects as they develop! Jazmin and Shruthi join Yasmine Boudiaf, and we hope to be able to announce our fourth artist imminently.
Jazmin Morris is a freelance Creative Computing Artist and Educator. She uses open-source tools to create digital experiences that approach social-political issues; with a specific focus on the complexities of simulating culture and identity in cyberspace. Jazmin is a former academic and an associate lecturer at University of the Arts London. She dedicates a considerable portion of her practice to education, fostering critical creative questioning around computation and design. Jazmin still fantasises over web.1 and Super Mario 64.
Shruthi Venkat is a designer, researcher, and futurist working at the intersection of emerging technologies and society. Venkat’s work translates complex systems — like AI and quantum computing — into tangible, human-centered experiences that invite critical reflection and dialogue. With roots in art and a background in industrial design, Shruthi has always been drawn to the emotional and narrative potential of artifacts. Past projects span tangible data visualizations, speculative prototypes, and participatory workshops that explore how we shape technology and it shapes us.
On 18th September 2025 the symposium ‘The Politics of AI: Governance, Resistance, Alternatives’ will take place at Goldsmiths, University of London. You can still register for the symposium here. The symposium is part of the BRAID project Sustainable AI Futures, which is mobilising interdisciplinary perspectives on AI and the environment, including the social life of AI environmental governance tools.
Getting there:
Goldsmiths is near New Cross and New Cross Gate stations. More details here. The day will open in RHB300A (note the ‘A’!). Turn right when coming into the front entrance of the building and go up the stairs. Note that all rooms can be found via the room finder: https://www.gold.ac.uk/campus-map/rhb-room-finder/ .
About the symposium
The rapid expansion of AI and computational infrastructure raises critical questions on whether we are governing AI responsibly, and if that is even possible at all. Contemporary governance regimes reduce social and environmental impacts to mere issues of quantification of harms and management of resources. Even if we track down an elusive number for its carbon emissions or water usage, how can we reconcile that with AI’s complex, messy and highly uncertain social impacts? What are AI’s sociopolitical effects, and how do we begin to notice, imagine, manage, or measure these effects?
This symposium bring together researchers who question AI’s implications for sustainability, public interest technology, and economic justice across multiple disciplines. The talks will critically engage with concepts like responsible AI, sustainable AI, and AI governance, and present alternative visions to the current AI entanglements with green capitalism and the twin transition, austerity, war, and accelerationism?
Programme: ‘The Politics of AI: Governance, Resistance, Alternatives’
We are thrilled to announce our first artist-in-residence, Yasmine Boudiaf. Yasmine is an Algerian creative technologist and researcher based in London. She is a research fellow at UAL’s Creative Computing Institute, a fellow of the Royal Society of Arts and previously at the Ada Lovelace Institute. She was recognised as one of ‘100 Brilliant Women in AI Ethics 2022’. Her projects interrogate the impact of new technologies on cultural life using anti-colonial approaches.
Yasmine’s project will sit at the intersection of generative AI, intangible heritage, and decolonial practice. It responds to the urgent need to rethink AI infrastructures that rely on extractive data practices, high carbon footprints, and cultural appropriation. The residency will investigate technical pipelines, participatory design and techno-rituals.
The research project Sustainable AI Futures (AHRC BRAID) is seeking creative practitioners to create original artworks (in any medium) exploring AI and the environment. We expect to award three mini-residencies, each consisting of £2,750 plus up to £1,000 of expenses (travel, materials etc.).
This is an opportunity to be part of a timely interdisciplinary project investigating AI and its complex impacts on our planet. Artists-in-residence will have the opportunity to engage with the project team’s expertise, and use it to inspire and inform their work.
Artists-in-residence will undertake creative practice (which may be entirely new, or develop existing work in new directions), and will deliver some form of event. The event could be an artist talk as part of one of the project’s workshops, or it could be a stand-alone event (e.g. public arts workshop, performance).
Timeline: We expect to confirm our decisions by February 2026, with mini-residencies to be completed by November 2026.
Suggested angles: We are open to many different angles, including but not limited to: Indigenous knowledge in relation to both AI and the climate / environment; decolonial approaches to AI and the climate / environment; AI and climate change against the background of MAGA-Silicon Valley convergence (and fall-out?); reviving obsolete / ‘dead tech’; subversive and imaginative uses of mainstream AI tools ‘against the grain’; AI, climate justice, and slow violence; interventions around building alternative AI infrastructures and capacity; resisting AI / abolishing AI; creative uses of AI against anthropocentrism; AI, the environment and archives; AI, the environment and data surveillance; AI and solastalgia / eco-grief. We would especially like to see work that is interactive / participatory.
We are seeking a Research Associate in AI and the Environment to join the AHRC BRAID project Sustainable AI Futures. This role offers the opportunity to conduct cutting-edge research, influence policy and practice, and collaborate with academic and industry partners to build more sustainable AI futures. (This is a full-time, 30-month fixed term contract). Application deadline 13 August.Apply here.
About the Role
Within the role you will explore the intersection of responsible AI and environmental sustainability. You will conduct cutting-edge research through literature reviews and expert interviews, co-author academic publications, toolkits, and policy papers, and track global AI governance standards (ISO, ITU, IEEE) to ensure our work remains relevant and impactful.
You’ll also help build a thriving community of practice, contributing to workshops, symposia, and other high-profile activities that shape the future of AI and the environment.
About You
Completed PhD in a relevant discipline (open to arts and humanities, social sciences, and STEM)
Research experience in at least one relevant domain, specifically: a) environmental sustainability and/or climate change; b) Artificial Intelligence (e.g. AI policy, AI ethics, responsible AI, critical AI studies); policy and governance, particularly relating to science, technology, or the environment
Strong analytic and communication skills, with evidence of producing high-quality outputs (e.g. publications, toolkits, standards, policy papers, reports)
Excellent collaboration and interpersonal skills, which could be evidenced through activities such as conducting interviews or fieldwork, building relationships with stakeholders, helping to cultivate a community of practice, conducting campaigns or driving change, or in other ways
Independent and proactive, capable of working flexibly individually and as part of a team
Experience engaging with legislation, policy, technical standards, or governance frameworks, including any work related to responsible AI (e.g. ISO, IEEE, OECD, BSI, or internal industry frameworks)
Experience of working with partners from outside academia (e.g. industry, NGOs, policymakers, cultural or creative organisations), and/or delivering impact outside academia
Research experience in more than one relevant domain (see point 2 under ‘essential’ criteria)
AI is poised to transform sustainability reporting by introducing new capabilities for data collection, analysis, and verification—with the potential to support more transparent, accurate, and engaging disclosures. But adopting these tools means understanding not only what they can and can’t do, but also ensuring they themselves align with sustainable and responsible AI principles. At the same time, AI introduces new challenges for sustainability reporting—such as the difficulty of measuring the carbon footprint of AI systems themselves.
This interactive workshop, hosted by Sustainable AI Futures (UKRI BRAID) and Digital Catapult, offers an opportunity to map the landscape, share ideas, make connections, and explore emerging issues at the intersection of AI and sustainability reporting.
