In this blog post, Bella Raja reflects on her recent workshop at the Centre for Computing History in Cambridge, UK. She shares key highlights from the activities with primary and secondary students and reflects on the importance of embedding planetary justice concerns in early childhood AI education.

At the 2026 India AI Impact Summit in New Delhi, “Planet” appeared alongside People and Progress as a core pillar of the agenda. Yet meaningful discussion of AI’s environmental footprint remained largely absent. In this reflection, Lakshmee Vinayak Sharma examines how narratives of AI opportunity and sovereignty are accelerating data center expansion across the Global Majority while sidelining the material costs of hyperscale infrastructure–from water and energy demand to land use and governance transparency. The piece calls for AI policy debates to confront these planetary implications and incorporate environmental accountability into the future of AI governance.

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.