Ecology is not yet ready for AI—and why that matters
The ecology of AI risk
Understanding the risk from applications of artificial intelligence (AI) is a critical part of creating AI governance strategies. Building on the idea of studying AI using ecological and evolutionary perspectives, we propose a novel approach for assessing risk from AI using indicators derived from theoretical ecology models. We illustrate our methods by deriving 3 indicators from population and ecosystem models originating from theoretical ecology. We conclude with a discussion of limitations of our analysis and considerations for improving AI governance policy.
Environmental Cost of Artificial Intelligence: Carbon, Water, and Land Footprints
AI’s rapid growth drives huge energy, water, and land use, raising environmental and equity challenges across its global infrastructure.
Environmental Cost of Artificial Intelligence: Carbon, Water, and Land Footprints
AI’s rapid growth drives huge energy, water, and land use, raising environmental and equity challenges across its global infrastructure.
AI FOR EPISTEMICS & COORDINATION
Civilization and technology have radically improved the human condition. Nonetheless, the world sometimes goes in directions which essentially nobody would prefer — e.g., nuclear arms races, unexpected financial crashes, predatory marketing, or ubiquitous political misinformation.
Kimi K3: The open-weights escalation
The global implications on the AI ecosystem.
AI for Science & Safety Nodes - Request for Proposals
Artificial intelligence is accelerating the pace of discovery across science and technology. But today’s AI ecosystem risks centralizing compute, talent, and decision-making power – concentrating capabilities in ways that could undermine both innovation and safety.
Import AI 475: Swarm scaling; Google DeepMind watermarks biology; and the AI science economy
Who chooses what AI gets to do?
AI is turning research into a scientific monoculture
Generative AI deserves scientific attention. But the rush to study it is producing a feedback loop of topical and methodological convergence, flattening scientific imagination and crowding out the pluralism needed to keep research adaptive, resilient, and intellectually generative.
AI Agents Landscape & Ecosystem (January 2026): Complete Interactive Map
Explore the comprehensive AI agents landscape map / ecosystem for January 2026. Compare AI Agents across categories, pricing, and capabilities. Updated daily with new autonomous agents, AI assistants, and emerging solutions.
AI’s climate impact is much smaller than many feared
New findings challenge the widespread belief that AI is an environmental villain. By analyzing U.S. economic data and AI usage across industries, researchers discovered that AI’s energy consumption—while significant locally—barely registers at national or global scales. Even more surprising, AI could help accelerate green technologies rather than hinder them.
Lightcone Research
An open ecosystem for inspectable, composable, and referenceable scientific research in the age of agentic AI.
Bridging the gap: inequalities that divide those who can and cannot create sustainable outcomes with AI
The widespread use of AI technologies impacts individuals, organisations, and societies in ways that warrant more comprehensive investigation. Inequalities in benefiting from AI advancements may le...
