







How the computer revolution shaped our conception of rationality—and why human problems require solutions rooted in human intuition, morality, and judgment
“Computers enable fantasies” – On the continued relevance of Weizenbaum’s warnings
“The computer has long been a solution looking for problems—the ultimate technological fix which insulates us from having to look at problems.” – Joseph Weizenbaum (1983) Trying to kee…

Abeba Birhane on Twitter / X
a classic case of “the human mind is afforded less complexity than is owed, and the computer is afforded more wisdom than is due.” Baria and Cross (2021)that "vibe" is at the core of what makes us human. it defies formalization and datafication https://t.co/AXELAqlYcq— Abeba Birhane (@Abebab) February 17, 2024
E.W. Dijkstra Archive: On the cruelty of really teaching computing science (EWD 1036)
The second part of this talk pursues some of the scientific and educational consequences of the assumption that computers represent a radical novelty. In order to give this assumption clear contents, we have to be much more precise as to what we mean in this context by the adjective "radical". We shall do so in the first part of this talk, in which we shall furthermore supply evidence in support of our assumption.
The mistake we all make... and the simple experiment that reveals it
Your answer reveals how you see the world – and the common error that hampers our decision making. In an extract from his new book, psychologist Richard Nisbett reveals the ‘mindware’ to help us think smarter
The marketplace of rationalizations
Recent work in economics has rediscovered the importance of belief-based utility for understanding human behaviour. Belief ‘choice’ is subject to an important constraint, however: people can only bring themselves to believe things for which they can find rationalizations. When preferences for similar beliefs are widespread, this constraint generates rationalization markets, social structures in which agents compete to produce rationalizations in exchange for money and social rewards. I explore the nature of such markets, I draw on political media to illustrate their characteristics and behaviour, and I highlight their implications for understanding motivated cognition and misinformation.

The hidden ‘rules of the game’ that dictate how we navigate the world | Psyche Videos
How free are we really, if human behaviour embodies the complex, intertwined webs of society and history?

Thinking—Fast, Slow, and Artificial: How AI is Reshaping Human Reasoning and the Rise of Cognitive Surrender
People increasingly consult generative artificial intelligence (AI) while reasoning. As AI becomes embedded in daily thought, what becomes of human judgment? We
Computer power and human reason : from judgment to calculation
xii, 300 pages : 24 cm; Includes bibliographical references and index

Bret Victor - The Future of Programming
I think this talk gives lots of food for thought. Are we too entrenched in our ways, to think in other/better ways?

Algorithm appreciation: People prefer algorithmic to human judgment
Even though computational algorithms often outperform human judgment, received wisdom suggests that people may be skeptical of relying on them (Dawes, 1979). Counter to this notion, results from six experiments show that lay people adhere more to advice when they think it comes from an algorithm than from a person. People showed this effect, what we call algorithm appreciation, when making numeric estimates about a visual stimulus (Experiment 1A) and forecasts about the popularity of songs and romantic attraction (Experiments 1B and 1C). Yet, researchers predicted the opposite result (Experiment 1D). Algorithm appreciation persisted when advice appeared jointly or separately (Experiment 2). However, algorithm appreciation waned when: people chose between an algorithm’s estimate and their own (versus an external advisor’s; Experiment 3) and they had expertise in forecasting (Experiment 4). Paradoxically, experienced professionals, who make forecasts on a regular basis, relied less on algorithmic advice than lay people did, which hurt their accuracy. These results shed light on the important question of when people rely on algorithmic advice over advice from people and have implications for the use of “big data” and algorithmic advice it generates.
A large-scale investigation of everyday moral dilemmas
Abstract. Questions of right and wrong are central to daily life, yet scientific understanding of everyday moral dilemmas is limited. We conducted a data-d

The Future of AI
The Parents’ Paradox: AI, Ethics, and the Limits of Machine Morality This post is based on a talk I gave at The AI & Automation Conference in London on February 25, 2026, and my slides. A…

A Behavioral Model of Rational Choice
Abstract. Introduction, 99. — I. Some general features of rational choice, 100.— II. The essential simplifications, 103. — III. Existence and uniqueness of

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)