Techno-solutionism

“techno-solutionism,” the simplification of complex societal problems into apps and algorithms. Ed-Tech’s Inequalities “Technological solutionism” is the related tendency to identify simple answers — in all domains, not just the tech sector — “before the questions have been fully asked” or the problems fully articulated. Take, for example: “the Internet has changed everything about how […]

The Distribution of Users’ Computer Skills: Worse Than You Think

Across 33 rich countries, only 5% of the population has high computer-related abilities, and only a third of people can complete medium-complexity tasks.

When did Computer Science Theory Get so Hard?

I posted on  When did Math get so hard?  a commenter pointed out that one can also ask  When did Computer Science Theory Get so Hard? For t...

Difficulty is about trust and communication, not ‘hard’ vs. ‘easy’

Why game designers and players talk about difficulty very differently

Experts Argue Whether Computers Could Reason, and if They Should (Published 1977)

Computer world is in midst of fundamental dispute over question of computer intelligence since MIT Prof Joseph Weizenbaum wrote book arguing that machines can never be made to reason like people and should not be; Weizenbaum por (M)

The Missing Discipline in Computer Science

On Teaching Computer Scientists to Ask “Why”

Hey, Computer Scientists! Stop Hating on the Humanities

Opinion: Computer science departments need to teach coders more than just how to code.

All you need is data and functions

It's really easy to tend towards complexity as engineers. I think on some level, we love complexity. There are obviously bad types of complexity, but I think there are other types of it that we seek out, because there's something satisfying about wrapping your head around it; and I think a lot of that kind of complexity ends up in our programming languages.

Closing the Loop: The Importance of External Engagement in Computer Science Research

Computer scientists tend to work by separating the essence of a problem from its environment, solving it in an abstract form, and then figuring out how to make the abstract solution work in the real world. For example, there is an enormous body of work on solving searching and sorting problems and in general it applies to finding and rearranging things regardless of whether they live in memory, on disk, or in a filing cabinet.

Feminist Computer Science Education: "'Women in Computing' As Problematic": A Summary

I've long been interested in why, despite so much organized effort, there percentage of women in CS has been so stagnant. One hypothesis I h...

How to be a wise optimist about science and technology?

I believe the central problem of the 21st century is how civilization co-evolves with science and technology. As our understanding of the world deepens, it enables technologies that confer ever more power to both improve and damage the world. There's currently much public discussion of this in the context of artificial superintelligence (ASI). However, it's a fundamental recurring challenge, affecting areas including climate change, genetic engineering, nanotechnology, geoengineering, brain-computer interfaces, and many more. How can we best benefit from science and technology, while supplying safety sufficient to ensure a healthy, flourishing civilization?

Learn To Code, It’s Harder Than You Think

TL;DR: All the evidence shows that programming requires a high level of aptitude that only a small percentage of the population possess. The...

The Irrational Decision: How We Gave Computers the Power to Choose for Us | Critical AI | Duke University Press

Jathan Sadowski is an associate professor in the Faculty of Information Technology at Monash University in Melbourne, Australia. He is the author of two books on technology and capitalism, Too Smart (2020) and The Mechanic and the Luddite (2025). He also cohosts the podcast This Machine Kills.

The Social Dilemma Fails to Tackle the Real Issues in Tech

The Netflix documentary replicates Silicon Valley’s biggest shortcomings.

Why Computers Won’t Make Themselves Smarter

We fear and yearn for “the singularity.” But it will probably never come.