While the proliferation of commercial, GenAI applications and the hyperscaling of data centers has brought the environmental harms of these technologies into sharper focus, most notably their unsustainable resource use and energy demands as well as problems with green washing, the direct environmental impacts of the material infrastructure are not the only way in which the environment and GenAI interrelate. Although indirect environmental impacts and underlying values and assumptions are harder to identify, they remain highly influential and should be made visible.
Red teaming is typically conducted in technology companies to identify unintended, unsafe, and harmful outcomes of AI models. Recently, civil society and public sector organisations have begun to adopt red teaming in ‘the public interest’ or for ‘social good’. In the context of GenAI, this often means creating prompts to evaluate if outputs (images, text, or other modality) are suitable for a pre-defined use case, if they adhere to social norms or (unintentionally) reinforce harmful stereotypes. Usually, this involves collaborative exercises directed by different forms of expertise.
GenAI systems are transformative technologies that not only represent but are also constitutive of human–environment relationships. As their use becomes increasingly taken for granted, it risks glossing over disagreements essential to the workings of democracy by simultaneously siloing people even more, submerging sources in superficial but polished texts or images, homogenising different views, and complicating the presence and activity of commercial interests. Inadequate industry disclosure of the data, algorithms, design decisions, and business interests underlying consumer-facing GenAI applications often hinders recognition and ultimately the regulation of their shaping environmental values. Therefore, new methods and community-based approaches to examine how this occurs and what effects it has on environmental communication and meaning-making are needed.
Topic: ‘Green teaming AI’
When: 8 April 12.00 to 13.00 CET
Where: Online – link by registration
Speakers
- James White, postdoctoral researcher at the Department of Technology and Society, Lund University
- Jutta Haider, Professor of Information Studies at University of Borås
Spoken language: English
Registration: To participate is free of charge. Sign up at ai.lu.se/2026-04-08/registration and we send you an access link to the zoom platform.
Project researchers:
- Björn Ekström, Swedish School of Library and Information Science, University of Borås
- Jutta Haider, Swedish School of Library and Information Science, University of Borås
- Malte Rödl, Division of Environmental Communication, Swedish University of Agricultural Sciences
- James White, Department of Technology and Society, Lund University
