When the Scoreboard Becomes the Game, It’s Time to Recalibrate Research Metrics - The Scholarly Kitchen

Today's guest post discusses research metrics and their relationship to research integrity, inclusivity, and long-term impact.

On Taste, Effort & Curiosity - again

When AI collapses how long it takes to ship, what’s left is judgment, experimentation, and knowing what not to build.

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.

Visualize Value — Ideas, made visible

An ongoing practice of turning ideas into images. Visual ideas about work, markets, technology, culture, and human behavior by Jack Butcher.

Deep research requires a slower pace than tech industry work

Anyone working in an industry for a while will become accustomed to that culture—its processes, its norms, its values, its tacit knowledge. Much of this is incredibly valuable, of course, but these ideas can also represent constraints. There are some important impedances here between tech industry culture and research culture. In particular, tech culture is calibrated to a much faster pace. This can lead to impatience or early abandonment when confronting problems which require a researcher’s pace.

Deep research requires a slower pace than tech industry work

Anyone working in an industry for a while will become accustomed to that culture—its processes, its norms, its values, its tacit knowledge. Much of this is incredibly valuable, of course, but these ideas can also represent constraints. There are some important impedances here between tech industry culture and research culture. In particular, tech culture is calibrated to a much faster pace. This can lead to impatience or early abandonment when confronting problems which require a researcher’s pace.

A sampling model of social judgment.

Why Reading Matters - Cal Newport

Last week, Rose Horowitch published a splashy Atlantic article titled ​“The End of Reading is Here.”​ (Ironically, given the subject matter, it weighed in at ... Read more

Beware of samples! A cognitive-ecological sampling approach to judgment biases.

No Longer No Sense of an Ending

This is my first feature piece on Contents Magazine, about harnessing the properties of hypertext and the Web for superior reader experiences and business results.

The Conversation: In-depth analysis, research, news and ideas from leading academics and researchers.

Curated by professional editors, The Conversation offers informed commentary and debate on the issues affecting our world. Plus a Plain English guide to the latest developments and discoveries from the university and research sector.

danmcquillan (@danmcquillan@kolektiva.social) on Twitter / X

Fisher/Jameson said "It's easier to imagine the end of the world than the end of capitalism". And yet, that act of imagining alternatives is urgent; if AI tells us nothing else, it tells us that capitalism is actively imagining the end of us.— danmcquillan (@danmcquillan@kolektiva.social) (@danmcquillan) August 30, 2026

Landslide / Holdfast

Notes on what’s happening to our ability to collectively know things, and a look ahead to what this community is especially well positioned to do to support and revitalize our info ecosystems and the humans inside them.