Theory Is All You Need: AI, Human Cognition, and Causal Reasoning

Felin, Teppo and Holweg, Matthias, Theory Is All You Need: AI, Human Cognition, and Causal Reasoning (February 24, 2024). Strategy Science, volume 9, issue 4, 2024[10.1287/stsc.2024.0189], Available at SSRN: https://ssrn.com/abstract=4737265 or http://dx.doi.org/10.1287/stsc.2024.0189

Abstract: Scholars argue that artificial intelligence (AI) can generate genuine novelty and new knowledge and, in turn, that AI and computational models of cognition will replace human decision making under uncertainty. We disagree. We argue that AI’s data-based prediction is different from human theory-based causal logic and reasoning. We highlight problems with the decades-old analogy between computers and minds as input–output devices, using large language models as an example. Human cognition is better conceptualized as a form of theory-based causal reasoning rather than AI’s emphasis on information processing and data-based prediction. AI uses a probability-based approach to knowledge and is largely backward looking and imitative, whereas human cognition is forward-looking and capable of generating genuine novelty. We introduce the idea of data–belief asymmetries to highlight the difference between AI and human cognition, using the example of heavier-than-air flight to illustrate our arguments. Theory-based causal reasoning provides a cognitive mechanism for humans to intervene in the world and to engage in directed experimentation to generate new data. Throughout the article, we discuss the implications of our argument for understanding the origins of novelty, new knowledge, and decision making under uncertainty.

Orange wind sock

Hoboken Historical Museum

Hudson Yards as seen from Hoboken North

The Collapse of Substack: A content-creator talks about money [Scott Carney]

00:00 The False Promise of Substack
05:14 The "Bait and Switch"
10:20 The Reality of Subscription Fatigue
15:35 YouTube Finances & Transparency
18:56 The Shift to Sponsorships

Those with programming skills are best at vibe coding

China published the most uncomfortable paper on vibe coding.

ETH Zurich tested 100 developers in a controlled, commercial-grade vibe coding environment to see who actually succeeds.

The findings are brutal.

The researchers tracked computer science achievement, written… pic.twitter.com/hVKdE4GQGD

— Superman (@thesupermanmx) September 5, 2026

From the tweet:

The hype told us that learning to code is dead because language is all you need.

The data just proved the opposite.

To truly master the vibe, you still need to understand how the machine thinks.

Here's the paper, Computer Science Achievement and Writing Skills Predict Vibe Coding Proficiency.

Friday Fotos: Exotic flowers

Little blue flowers

The importance of work and the threat of AI

Ruxandra Teslo, Curing cancer won’t redeem AI, Ruxandra's Substack, Sept. 1, 2026.

A few weeks ago, a poll result began circulating on X: Americans now appear to be more hostile to the construction of data centers than to the construction of nuclear power plants. This is striking because for decades, the nuclear reactor has been the archetypal object of anti-abundance politics.

Looking at how nuclear power plants have become so hated is instructive. On many objective grounds, they are perfectly fine (actually, they are glorious): a low-cost, low-carbon emission form of energy. But a big part of what made nuclear power plants so hated was, of course, not based on empirical facts, but on the imaginative horror surrounding them. The association with the Cold War and nuclear bombs. The nuclear accidents: a great explosion, scorched and poisoned landscapes, mutant creatures lingering decades after the event, wandering through the ruins of the dystopian landscape. Nuclear power accumulated an entire symbolic vocabulary of fear that went far beyond its concrete risks and outshined its benefits.

On the face of it, the concerns around data centers are largely practical and they include, most prominently, worries over water usage or electricity consumption. Andy Masley and others have done great work rebutting some of these worries from a factual perspective; for example, in articles like “The AI water issue is fake”. But I suspect that debating these concerns at the object-level misses the deeper point. The practical objections to data centers often seem less like the real source of the hostility than respectable vessels for a more diffuse fear. Vague anxiety is hard to argue from, so the imagination gives it a body: water use, electricity demand and noise. Like nuclear plants before them, data centers are acquiring a mythology of their own: vast, windowless avatars of a deeper fear that the machines built inside them may one day render human beings unnecessary.

“Rendering humans unnecessary” is broad enough and it encompasses many different fears, so I want to focus on one of the most concrete instantiations of it: the fear of job loss. Anthropic’s 2026 Public Record survey of nearly 52,000 Americans revealed that 64% of the respondents said they were worried about A.I.-induced job loss, making it the single most common fear in every state. The words “job loss” might make it sound mostly about income, but I think this understates what’s at stake for most of the population. For work provides not only income, but agency, status, belonging and a sense of control over one’s life. So what underpins the fear here is not simply losing one’s paycheck, but rather the entire social role through which one has come to understand oneself. Existing polls support this interpretation. When Americans are asked whether they would prefer the response to A.I. to consist of creating good-paying jobs or providing direct income support via governmental programs, they overwhelmingly choose the jobs.

There’s much more at the link.

Citibikes on 14th St. in Hoboken

Respiration waveforms are closely coupled with the shape of neural oscillations

Eena Kosik-Rose, Guangyu Zhou, Andrew Sheriff, Joshua M. Rosenow, Stephan U. Schuele, Chima O. Oluigbo, Saige Anabel Teti, Mohamad Koubeissi, Md Rakibul Mowla, Ariane E. Rhone, Sukhbinder Kumar, Brian Dlouhy, Christina Zelano, Bradley Voytek, Cycle-by-cycle respiration waveforms are coupled with the shape of neural oscillations, Journal of Neuroscience 31 August 2026, e0731262026; DOI: 10.1523/JNEUROSCI.0731-26.2026

Abstract

Beyond sustaining life, breathing is a vital physiological rhythm that shapes cognition, perception, emotional regulation, and mental health. Breathing has a direct effect on neuronal excitability and is coupled to neural oscillations across a variety of brain regions. Notably, both respiration and neural oscillations are asymmetric and not perfectly rhythmic: for example, every breath has a different shape and duration, and is interspersed with variable pauses. Here, we examined the coupling between breathing and the brain by quantifying the nonsinusoidal features of each breath and comparing it to the shape of each corresponding neural oscillation cycle. By leveraging invasive human brain recordings from 16 participants (8 female, 8 male), we found respiration-neural waveform coupling on a breath-by-breath, cycle-by-cycle basis across limbic and cortical forebrain regions. For decades, the dominant perspective on cognition and mental health have focused on the brain, but recent work is highlighting the importance of brain-body interactions. Our results show that the coupling between breathing and neural activity is much richer than previously appreciated, and our approach opens new avenues for studying these peripheral-to-central nervous system interactions in a more robust, temporally precise manner.

Significance Statement

Breathing shapes brain activity, but prior work has characterized this coupling by aggregating across many breath cycles, leaving the fine-grained shape of individual breaths unexamined. Here, we show that the precise waveform shape of each breath is coupled to the shape of corresponding neural oscillation cycles in the human forebrain, on a breath-by-breath basis. Using invasive brain recordings from 16 epilepsy patients, we demonstrate that temporal and amplitude features of individual breaths are linked to the morphology of neural oscillations in limbic and cortical regions. This cycle-by-cycle respiratory-neural coupling reveals a richer and more temporally precise relationship between breathing and brain activity than previously appreciated.

Approaching Jersey City (August 2007)

Making it in the music business [Mary Spender]

YouTube page:

Mary Spender explores the role of privilege and economic background in the music industry. By analyzing how access to time and resources influences artistic development, this discussion examines the challenges independent musicians face when trying to build sustainable careers without established support systems.

Chapters
00:00 The Gift of Time
04:16 What Money Actually Buys
09:10 What I Actually Had
14:53 Envy
19:26 Was It Really Easier Before?
22:12 The Starving Artist Myth
25:10 What Does Success Actually Look Like?
27:55 Redefining Success
29:54 Stay in the Game
34:49 What Privilege Really Means

Square rigger on the Hudson

Patterns of light through a glass