The Ground Truth Institute

Rebuilding the Architecture of Science

Science built the modern world. It’s time to rebuild the world of science.

Can AI Replace Social Science Researchers?

No. No it can't. Come on, now.

Could AI slow science?

Confronting the production-progress paradox

Science Must Decentralize

Knowledge production doesn’t happen in a vacuum. Every great scientific breakthrough is built on prior work, and an ongoing exchange with peers in the field. That’s why we need to address the threat

From Genius Science to Scenius Science - Cosmik Labs

Why personal AI tools might not be all we need to revolutionize science

Kevin Weil 🇺🇸 on Twitter / X

💥 Today we’re introducing Prism—a free, AI-native workspace for scientists to write and collaborate on research, powered by GPT-5.2.Accelerating science requires progress on two fronts:1. Frontier AI models that use scientific tools and can tackle the hardest problems2.… pic.twitter.com/cnLysHixuQ— Kevin Weil 🇺🇸 (@kevinweil) January 27, 2026

Jason Shepherd on Twitter / X

I have quite a lot of thoughts on this..that won't fit in a tweet. Bottomline is that there are issues scientists in the US would love to improve - faster review, less grant writing, more stability and freedom to do risky science. The folks celebrating this doc are mostly../1 https://t.co/xlPAH9XYNC— Jason Shepherd (@JasonSynaptic) July 23, 2026

Civic, Citizen and Grassroots Science: Towards a Transformative Scientific Research Model | Request PDF

Request PDF | On Jan 1, 2013, Jessica McCallum Breen and others published Civic, Citizen and Grassroots Science: Towards a Transformative Scientific Research Model | Find, read and cite all the research you need on ResearchGate

Seth Bannon on Twitter / X

There are some exceptionally good ideas here for reforming and accelerating science.Some of my favorite proposals:Apply the scientific method to science funding (track applications, reviewers, funding decisions, and outcomes, then experimentally test which grantmaking methods… https://t.co/Q0JmqTBPYm— Seth Bannon (@sethbannon) July 22, 2026

The Bazaar of Scientific Knowledge | shishyko!

What if we didn't collapse all the knowledge from the scientific process into one paper?

Designing AI for Disruptive Science

Why scaling AI won’t automatically lead to paradigm shifts.

Introducing the Inaugural EU Cohort of the Big if True Science Accelerator — Renaissance Philanthropy – A brighter future for all through science, technology, and innovation (V2)

In June, we announced our partnership with SPRIND, Germany's Federal Agency for Breakthrough Innovation, to identify and develop the next generation of leaders to design new R&D challenges and other kinds of coordinated research programs to tackle humanity's most pressing challenges. La

The one science reform we can all agree on, but we're too cowardly to do

OR: the long overdue forest fire

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.