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…
The Minimum Viable Scientific Record
The open science movement does not lack a shared vision. Decades of declarations, statements of principle, and calls to action have failed to put that vision into practice. This essay proposes a minimum viable scientific record (MVR) that would make the open science vision possible, and asks funders to make operating on it a condition of their money.
The Alien Space of Science: Sampling Coherent but Cognitively...
Scientific discovery is constrained not only by what is true, but by what is cognitively available to the researchers currently exploring a field. Many directions are coherent in light of the...
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.
Science has been in a “replication crisis” for a decade. Have we learned anything?
Bad papers are still published. But some other things might be getting better.
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
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
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