AI systems are built on global supply chains with deep planetary impacts that often remain hidden. In this update, we document new cases from around the world — from lithium and rare-earth extraction to energy- and water-intensive data centres — showing how narratives of progress in AI mask environmental harm, social inequality, and a lack of transparency.

From lithium mining in Zimbabwe and rare-earth extraction in Myanmar, to data centres in India, the United States, Mexico, the UK, and Germany, these cases challenge dominant narratives of technological progress.

Many scholars have talked about the importance of imagination as a tool for resistance, whether it is imagination of possible alternatives for our ways of life, or possible futures for humanity and Earth, positive or negative. Personally, I sometimes find it difficult to become emotionally invested in an environmental or even a political development unless I sit down to imagine, by thinking or by reading, what its impact is or will be on people, ecosystems, and our planet in its plurality. Fiction really helps me in this effort. I have collected here a few of my personal recommendations for novels and stories with really stark imaginations that have impressed onto my brain what the future might look like, which helps me want to shape it.

AI has global reach, and global consequences. As we try to examine and map AI and its planetary justice impacts, we want to map and expose the testimonies of real-world impacts of the AI supply chain. In our Observatory of Planetary Justice Impacts of AI, we endeavour to bear witness to the impacts of AI, so as to to spread information, share resources, and build a catalogue of real-world examples. In this blog, we highlight some of the latest additions to the Observatory, which we believe are stark examples of ways in which power and resistance coexist and balance each other at every stage of the AI supply chain and in many locations across the world. 

At the Digital Citizen Summit in Hyderabad, the AI + Planetary Justice Alliance (AIPJ) highlighted the hidden social and ecological impacts of AI. On the first day, we led a participatory workshop exploring the AI supply chain—from mineral extraction and hardware manufacturing to data centres and e-waste—using our AI Supply Chain Impact Framework to map environmental, labour, and community effects and discuss local strategies for equitable infrastructure.

On the second day, Sara Marcucci joined a panel situating Hyderabad’s emerging data centre ecosystem within global AI supply chains, emphasizing who benefits and who bears the costs. Discussions focused on alternatives such as smaller-scale AI, meaningful community participation, and governance that treats resources and affected communities as rights-bearing.

Raw Materials for AI is a visual introduction to the physical foundations of artificial intelligence, tracing seven key minerals – like cobalt, silicon, and lithium – used to build and power AI systems. Produced as part of our Below the Algorithm project, the zine invites readers to rethink AI as something rooted in land, labor, and extraction, not just data and code. Rather than offering technical depth, it provides a grounding entry point to begin connecting the dots between the material world and the digital systems built upon it.

A new batch of case studies has been added to our Observatory of Planetary Justice Impacts of AI! This is one of our core initiatives, where we map real-world examples of the planetary justice impacts of the AI supply chain. It is a continuous, adaptive effort to collect data, to track cases and investigations, and see what patterns emerge.

In this reflection from the Data for Public Goals event at Politecnico di Milano, we call for a radical reframing of how we understand and govern data for AI. Moving beyond technical metrics and ethical tweaks, the piece introduces a planetary justice lens that traces AI's impacts across its full supply chain–from resource extraction to model deployment. Highlighting the ecological, labor, and epistemic costs embedded in AI systems, the post challenges the narrative of data neutrality and questions the assumption that automation is inherently beneficial. What if, instead of optimizing AI, we asked whether it is needed at all–and who gets to decide?

AI is often seen as the answer to our planetary crises. But what if it’s also part of the problem? In this reflection from the ISEE/Degrowth 2025 Conference, Sara Marcucci argues that AI is not just a neutral tool—it’s a product of growthism and dualism, built on extractive infrastructures and driven by an ideology of more. Drawing on real-world supply chain impacts and grounded community practices, the piece offers a framework for reimagining AI through a degrowth lens: starting with collective purpose, guided by relational values, and enacted through democratic, low-impact practices.

Tracking and analyzing real-world impacts of the AI supply chain is a key part of our work, and the Observatory of Planetary Justice Impacts of AI is the tool we are using to collect and analyse such examples.

It aims to catalog the different stages of the AI supply chain and the impact that each stage has on various communities from a planetary justice perspective.

It is a dynamic and collaborative collection tool, where categories will evolve to attempt to map out the data as it grows. We aim for the Observatory to be a collaborative and bottom-up effort, therefore we have opened this module for anyone to be able to submit their case-studies for planetary justice impacts of AI.

The AI + Planetary Justice Alliance joined researchers, organizers, and practitioners in Bengaluru for the Mapping Data Work workshop — a gathering that foregrounded the invisible labor behind AI systems. In our blog, we report key takeaways, reflect on what it means to build “ethical datasets,” question the assumptions behind datafication, and share insights from our own research on epistemic justice in agricultural AI in India. What if the push to represent is just another form of surveillance? And why are we building AI in the first place? Read the full piece to explore the planetary justice implications of some of AI’s quietest supply chains: data work.

AI is not inevitable, nor is it a given. As Kate Crawford reveals in Atlas of AI, behind the sleek interface of artificial intelligence lies a vast network of extraction—of minerals, of labor, of data, of meaning. From lithium mines in Nevada to e-waste dumps in the Global South, AI systems are materially grounded in deeply unequal infrastructures. They are not just powered by code, but by centuries-old ideologies of control, colonialism, and capitalism. This review explores the human and ecological toll of AI’s supply chain and urges a shift from the language of ethics to a critical interrogation of AI’s power.