Why personal AI tools might not be all we need to revolutionize science
AI Is a Waste of Time
The newest AI tools are accelerating basic research and scaring the general public. But many people are simply using them as toys.
Designing AI for Disruptive Science
Why scaling AI won’t automatically lead to paradigm shifts.
The Fork in the Road: AI Horseless Carriages or Collective Intelligence for Science - Cosmik Labs
Stop saying that AI is just a tool and it only matters how it is used
I’m tired of this phrase and this simple way of thinking about tools. This blog post is a wandering train of thought on the topic of what tools are and why it matters to be even slightly more mature in how we think about them.
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 for science: What can it do? Can it do things? Let’s find out!
A what we’re reading spotlight
Everybody needs a personal AI policy. Just ask Hank Green.
How can we reap AI’s benefits without melting our brains in the process?
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...
AI is not superhuman
What metaphor should drive the field of AI research?
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 experienced through AI co-created tools
AI co-created tools and social spaces as a new medium
Fulcrum - Leverage for Discovery
We place AI engineers with research labs working on hard scientific problems.
Science that Compounds: The Need for A New Substrate for Research in the Age of AI
This paper is a perspective from Lightcone Research, an open-source initiative building tooling for scientific research in the age of agentic AI.
Using X-Labs to Unleash AI-Driven Scientific Breakthroughs | IFP
How to adapt our science funding mechanisms to the unique infrastructure needs of large-scale AI projects
