In the twenty-first century, humanity is reaching new heights of scientific understanding—and at ...
Guest post: If you’re going to critique science, be scientific about it
Loren K. Mell Editor’s note: This post responds to a Feb. 13 article in The Atlantic, “The Scientific Literature Can’t Save Us Now,” written by Retraction Watch cofounders Adam Marcus and Ivan Oran…
Hyperproblems: New Ways of Doing and Communicating Science - Hyperproblems
Hyperproblems: Hyperproblems are scientific challenges whose scale, complexity, novelty and interdependence overwhelm traditional research models, requiring…
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.
Without a theory of intelligence
The history of science — and of progress — is a series of benefits that are direct results of new tools.
What stories should we tell about scientific progress now?
In search of the mysterious fruits of basic science
Markus J. Buehler on Twitter / X
After decades at MIT studying how nature builds - from spider silk to bone to nacre - I've become convinced of something: the biggest barrier to scientific progress isn't knowledge, it's connection. The insights we need already exist, scattered across millions of papers and… pic.twitter.com/EHUomaFyPj— Markus J. Buehler (@ProfBuehlerMIT) March 10, 2026
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...
Speculations on the Future of the Scientific Method
The following essay was published 20 years ago (January, 2006) on my blog The Technium. I edited the intro here, but the speculations are basically unchanged.
The Current Crisis: What's Happening to Science in America
Metascience for whom? A question as old as science.
Before we fix science, we need to ask who built it!
Maybe scientific progress isn’t slowing, after all
A new paper takes aim at the claim that science has become less disruptive
This is why @atproto.science is so relevant rn This compilation of essays indicates that scientists are most frustrated by insufficient “community tools and resources... Essential infrastructure for sharing, maintaining and building on existing work and data is also badly underdeveloped." >
What Scientists Said: Results from Astera's First Essay Competition
asterainstitute.substack.com