New Studies: How Commercial Forces Make Science Less Reliable

Can AI Replace Social Science Researchers?

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

Field Theory: AI as Social Science Question, Object & Tool

Uses of advanced artificial intelligence are changing how societies organize labor, govern, produce knowledge, and make meaning. In light of these developments, this essay argues that AI models, tools, and systems pose three interrelated imperatives for social science: they demand renewed attention to social theories of how technology, human experience, and social order are entangled; they require study as objects of inquiry in their own right; and they offer capabilities that may transform—or upend—the practice of social investigation itself. From Weber’s analysis of rationalization to Du Bois’s study of technology and inequality to contemporary scholarship on algorithmic governance, the essay examines what social science distinctively offers: the capacity to historicize the apparently unprecedented, to trace connections across scales, and to center those most affected by technological change. It identifies how algorithmic systems are remaking the distribution of opportunity and risk as a central task of social inquiry and asks what futures social science might help bring into being.

"AI" is Automated Inequality

Tech bros still dominate the discussions about so-called "AI" with false claims. Even most "AI"-critical researchers spend much of their time meticulously debunking (always only a subset of) claims, leaving vast areas of the economic consequences of "AI" unexplored. (Even the "AI"-evangelist Economi

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

Science Is Drowning in AI Slop

Peer review has met its match.

Charting AI’s Role in Scientific Discovery — Renaissance Philanthropy – A brighter future for all through science, technology, and innovation

Renaissance Philanthropy, with support from Google.org , is conducting a landscape study of AI integration in scientific research — and we want your perspective.

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...

70 years of AI hype

Quoting from Olivia Guest et al. (2025) "Against the Uncritical Adoption of AI Technologies in Academia."

The Age of Academic Slop is Upon Us

what happens when AI automates "normal science"?

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 is turning research into a scientific monoculture

Generative AI deserves scientific attention. But the rush to study it is producing a feedback loop of topical and methodological convergence, flattening scientific imagination and crowding out the pluralism needed to keep research adaptive, resilient, and intellectually generative.

Designing AI for Disruptive Science

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

AI FOR EPISTEMICS & COORDINATION

Civilization and technology have radically improved the human condition. Nonetheless, the world sometimes goes in directions which essentially nobody would prefer — e.g., nuclear arms races, unexpected financial crashes, predatory marketing, or ubiquitous political misinformation.

Is the scientific paper due to be replaced?

AI is pushing scientific publishing to the brink. For neuroscience, the crisis may be an opportunity to finally connect findings across subfields.