Science Needs Scientists

And Scientists Need Science

Without a theory of intelligence

The history of science — and of progress — is a series of benefits that are direct results of new tools.

The Scientific Contribution Graph: Automated Literature-based Technological Roadmapping at Scale

Sir Isaac Newton famously wrote, “If I have seen further, it is by standing on the shoulders of giants”. Scientific contributions are rarely developed in isolation, but build upon prior contributions, such as problem framings, experimental methods, and empirical findings. Understanding these prerequisite relationships is important for studying scientific progress, and for automated scientific discovery systems that must reason about which existing capabilities can be used to develop new ones (e.g. Lu et al., 2024; Jansen et al., 2025b; Baek et al., 2025).

The Engine of Scientific Discovery: How New Methods and Tools Spark Major Breakthroughs

Abstract. How do we spark new scientific discoveries? Why do some breakthroughs seem even accidental? And most importantly, how can we accelerate them and

How and When to Involve Crowds in Scientific Research - The Book

This book explores how millions of people can significantly contribute to scientific research. Discover main elements, authors, and who this book is for and why.

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 as Collective Sensemaking

What is Science?

Science as Collective Sensemaking

What is Science?

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…

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...

Rebuilding the Architecture of Science

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

Can anyone fix science?

Science has always been in crisis. This is fine.

Science Communication as a Collective Intelligence Endeavor: A Manifesto and Examples for Implementation

Effective science communication is challenging when scientific messages are informed by a continually updating evidence base and must often compete against misinformation. We argue that we need a new program of science communication as collective intelligence—a collaborative approach, supported by technology. This would have four key advantages over the typical model where scientists communicate as individuals: scientific messages would be informed by (a) a wider base of aggregated knowledge, (b) contributions from a diverse scientific community, (c) participatory input from stakeholders, and (d) better responsiveness to ongoing changes in the state of knowledge.

Push-button science

Technological advances change not only what we can learn as scientists, but also how science is conducted. Here we explore how automation and outsourcing are affecting the act of doing science.