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
Field Notes: The Architecture of Rationalization - Aaron Ross Powell
Marginalia on the internet turning bad, platform extraction, and existential restlessness.
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.
Moral Deskilling and Upskilling in a New Machine Age: Reflections on the Ambiguous Future of Character
This paper explores the ambiguous impact of new information and communications technologies (ICTs) on the cultivation of moral skills in human beings. Just as twentieth century advances in machine automation resulted in the economic devaluation of practical knowledge and skillsets historically cultivated by machinists, artisans, and other highly trained workers (Braverman 1974), while also driving the cultivation of new skills in a variety of engineering and white collar occupations, ICTs are also recognized as potential causes of a complex pattern of economic deskilling, reskilling, and upskilling. In this paper, I adapt the conceptual apparatus of sociological debates over economic deskilling to illuminate a different potential for technological deskilling/upskilling, namely the ability of ICTs to contribute to the moral deskilling of human users, a potential that exists alongside rich but currently underrealized possibilities for moral reskilling and/or upskilling. I flesh out this general hypothesis by means of examples involving automated weapons technology, new media practices, and social robotics. I conclude that since moral skills are essential prerequisites for the effective development of practical wisdom and virtuous character, and since market and cultural forces are not presently aligned to bring about the more salutary of the ambiguous potentials presented here, the future shape of these developments warrants our close attention—and perhaps active intervention.
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
People Spend Too Much Time On Decisions with Equally Satisfying Outcomes
The pitfalls of analysis paralysis
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?
Mathematical methods and human thought in the age of AI
Artificial intelligence (AI) is the name popularly given to a broad spectrum of computer tools designed to perform increasingly complex cognitive tasks, including many that used to solely be the province of humans. As these tools become exponentially sophisticated and pervasive, the justifications for their rapid development and integration into society are frequently called into question, particularly as they consume finite resources and pose existential risks to the livelihoods of those skilled individuals they appear to replace. In this paper, we consider the rapidly evolving impact of AI to the traditional questions of philosophy with an emphasis on its application in mathematics and on the broader real-world outcomes of its more general use. We assert that artificial intelligence is a natural evolution of human tools developed throughout history to facilitate the creation, organization, and dissemination of ideas, and argue that it is paramount that the development and application of AI remain fundamentally human-centered. With an eye toward innovating solutions to meet human needs, enhancing the human quality of life and expanding the capacity for human thought and understanding, we propose a pathway to integrating AI into our most challenging and intellectually rigorous fields to the benefit of all humankind.
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.
The rationalists are not ok
Who, or what, are the rationalists? They are an internet-spawned sub-culture who ‘practice the art of rationality’. This means they spend lots of time thinking about topics like cognitive biases, Bayesian reasoning, probability and statistics, computer science, AI, decision theory, game theory, transhumanism, etc. Demographically they skew heavily toward STEM students from elite universities and tech guys in the bay area.
