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.
An End-to-End View of AI Safety
In this blog, Rachel Coldicutt OBE, Executive Director, Careful Industries discusses our newly published literature review on the safe adoption of artificial intelligence in engineered systems.
Artificial intelligence tools expand scientists’ impact but contract science’s focus
Nature - Artificial intelligence boosts individual scientists’ output, citations and career progression, but collectively narrows research diversity and reduces collaboration, concentrating...
From Genius Science to Scenius Science - Cosmik Labs
Why personal AI tools might not be all we need to revolutionize science
Strengthening biosecurity in the era of AI
AI is reshaping biology, unlocking breakthroughs while raising new risks. Learn how smarter safeguards can strengthen biosecurity without slowing innovation.
A Safe Path to Open Weights
Strategic openness can strengthen AI safety and support broader access as defenses and safety science mature.
Kimi K3: The open-weights escalation
The global implications on the AI ecosystem.
Inside the Dirty, Dystopian World of AI Data Centers
The race to power AI is already remaking the physical world.
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.
Cosmik Updates: February 2026 - Cosmik Labs
@atproto.science @cosmik.network Raising a question for the ATProto science community: Can AI agents be legitimate participants in research ecosystems? What would make their outputs trustworthy?
Ecology is not yet ready for AI—and why that matters
Ecology is not yet ready for AI—and why that matters
Designing AI for Disruptive Science
Why scaling AI won’t automatically lead to paradigm shifts.
Artificial intelligence and illusions of understanding in scientific research
Scientists are enthusiastically imagining ways in which artificial intelligence (AI) tools might improve research. Why are AI tools so attractive and what are the risks of implementing them across the research pipeline? Here we develop a taxonomy of scientists’ visions for AI, observing that their appeal comes from promises to improve productivity and objectivity by overcoming human shortcomings. But proposed AI solutions can also exploit our cognitive limitations, making us vulnerable to illusions of understanding in which we believe we understand more about the world than we actually do. Such illusions obscure the scientific community’s ability to see the formation of scientific monocultures, in which some types of methods, questions and viewpoints come to dominate alternative approaches, making science less innovative and more vulnerable to errors. The proliferation of AI tools in science risks introducing a phase of scientific enquiry in which we produce more but understand less. By analysing the appeal of these tools, we provide a framework for advancing discussions of responsible knowledge production in the age of AI.
AI has supercharged scientists—but may have shrunk science
Analysis of 41 million papers finds that although AI expands individual impact, it narrows collective scientific exploration
AI agents pose untold risk to humanity. We must act to prevent that future | David Krueger
The pieces are falling into place for autonomous artificial intelligence. We must stop unregulated development
