Doctoral position in History of Science, Technology & Environment at KTH and WASP-HS Graduate School
The Division of the History of Science, Technology and the Environment in the School of Architecture and Built Environment at KTH is recruiting one doctoral student within "environmental impact of AI" to be conducted within the Wallenberg AI, Autonomous Systems and Software Program – Humanity and Society (WASP-HS) . The research combines critical media studies, environmental humanities, critical geography methodologies, history and science and technology studies to examine the complex relationship between artificial intelligence (AI) and environmental and climate change. The doctoral student will be enrolled with the WASP-HS research school.
Third-cycle subject: History of Science, Technology and Environment
Project Description
AI Planetary Futures: Climate and environment in Silicon Valley’s AI paradigm
As the planetary crisis of a destabilized Earth system bringing about climate change, biodiversity loss and ocean circulation collapse carries on, in spite of the now massive, amassed science and communication on the urgency of the state of the planet, many tie in their hope to new and emerging technologies. In the 2020’s, these hopes have been centered on the potential of new AI systems to help mitigate and align the human world with the needs of the more-than-human, by for instance saving energy or otherwise decreasing greenhouse gas emissions. Climate change, biodiversity loss and ocean degradation are wicked problems that are presented as solvable through AI; from accelerating scientific discoveries to energy savings, the power of the machine appears greater than that of its creator. At the same time, leading technology firms in Silicon Valley currently offering general purpose AI to many states and corporations, are particularly focused on developing what they refer to as Artificial General Intelligence (AGI), defined by OpenAI as AGI “highly autonomous systems that outperform humans at most economically valuable work.”
The AI models of Silicon Valley are heavier and more geographical than the widespread notion of their lightness and artificiality (Crawford 2021, 2024; Nost, 2022). The quick rollout of massive hyperscale data centers have so far accelerated water and energy demands, often fueled by fossil sources and thereby drastically increasing emissions. A similar problem can be observed with regards to the hopes of energy efficiency, both for AI systems themselves and when applied to other sectors, where decreased use of energy tends to lead to lower prices and therefore larger consumption in what is known since the early days of steam-based industrialization as Jevons paradox.
Recent scholarship has highlighted how AI technologies applied for environmental and climate purposes currently come with a line of new opportunities for commodification and extraction which ultimately serve the interests of the corporations that develop them more than the benefits they promise (Bakker & Ritts 2018). One study (Nost and Colven, 2022) shows that Climate AI, understood as climate applications of AI technologies, tends to work through a general contradiction in how they can claim sustainability improvements while effectively contributing to the opposite.
Against this background, the doctoral project will analyze the climate and environmental affordances of Silicon Valley based general purpose AI systems developed and operated by the group of corporations known as Big Tech. There is a lack of knowledge about the deep contradictions within the discourse of AI and sustainability, which arguably need to be understood through the actions of the leading firms given the scale of their environmental and climate impact, both directly and through their dominance in what AI models are developed.
The project will further analyze the shifting temporalities of AI from a historical perspective, asking how conceptions of past, present and future states of human impacts on the environment are changing with accelerating AI deployment. It will target the conflicting discourses about the future in which AI becomes a main site of contestation. The project will analyze the underlying assumptions, values and imaginaries of leading AI developers in Silicon Valley and their relation to the technological form and function of general purpose AI, and further to the quest for so called Artificial General Intelligence, AGI.
Working with historical analysis and drawing on, for example, media theory, STS and critical geography methodologies, the PhD student will develop a novel approach to understanding the climate and environmental affordances of general purpose AI within the dominance of Big Tech.
Contact: Adam Wickberg