Maximilian Kasy

The robots who predict the future Three books unpack our infatuation with prediction, and what we lose when we outsource this task to machines.

Another nice review of "The Means of Prediction" in @technologyreview.com / @techreview:

www.technologyreview.com/2026/02/18/1...

(Also discussing lovely new books by @beenwrekt.bsky.social / @beenwrekt and @carissaveliz.bsky.social / @CarissaVeliz )

🔥 Just accepted for publication at AEJ:Policy 🔥

"Employing the unemployed of Marienthal:
Evaluation of a guaranteed job program"

maxkasy.github.io/home/files/p...

The robots who predict the future Three books unpack our infatuation with prediction, and what we lose when we outsource this task to machines.

Another nice review of "The Means of Prediction" in @technologyreview.com / @techreview:

www.technologyreview.com/2026/02/18/1...

(Also discussing lovely new books by @beenwrekt.bsky.social / @beenwrekt and @carissaveliz.bsky.social / @CarissaVeliz )

🔥 Just accepted for publication at AEJ:Policy 🔥

"Employing the unemployed of Marienthal:
Evaluation of a guaranteed job program"

maxkasy.github.io/home/files/p...

The robots who predict the future Three books unpack our infatuation with prediction, and what we lose when we outsource this task to machines.

Three books unpack our infatuation with prediction, and what we lose when we outsource this task to machines.

Worker activism in tech is back. It's starting with opposition to ICE, but I think it will spill over into other areas.

This thread will share what's happened recently and what I think might be next. As well as ways for folks to get involved if they want to.

“LLMs are not just labor-replacing and productivity-expanding, but can, in some circumstances at least, enable the production of totally new things.” @mattbruenig.bsky.social mattbruenig.com/2026/02/10/t... ht @mitchsaid.bsky.social

My slides for today's ML & Econ group meeting:

"Double descent,” and what linear regression can teach us about the coming collapse (?) of the AI bubble.

maxkasy.github.io/home/files/o...

(Based mainly on "Learning Theory from First Principles," chapter 12, www.di.ens.fr/%7Efbach/ltf... )

The Means of Prediction Check out this great listen on Audible.com. This is an audiobook version of this book. An eye-opening examination of how power—not technology—will define life with AI. AI is inescapable, from its...

📕 🔊 "The means of prediction" is now available as audiobook! 🔊 📕

www.audible.co.uk/pd/B0GL99H5J...

I wanted David Attenborough. didn’t work out, but still got a great voice actor who beats my midnight-jazz-radio-dj voice :)

Title: Machine learning, causal inference, and economics Speaker: Professor Maximilian Kasy (University of Oxford) Date: 27th Jan 2026 - 9:30 to 10:30 🗓️ Event: (CIFW05) Causal Machine Learning for… Prof. Maximilian Kasy | Machine learning, causal inference, and economics

Recording of my talk on
"Machine learning, causal inference, and economics"

www.youtube.com/watch?v=Qufn...

Very nice review of "The means of prediction" by @B_Eichengreen:

smartthinkingbooks.com/smart-thinki...

The means of prediction and the production function of AI
maxkasy.github.io/home/files/p...

Thoughts and comments welcome!

2/2

Now with correct links - forthcoming policy-papers and essays:

Individual property rights or collective democratic governance? Privacy in the age of AI
maxkasy.github.io/home/files/p...

Welfare for the 21st century: Basic income and job guarantee policies
maxkasy.github.io/home/files/p...

1/2

The means of prediction and the production function of AI
maxkasy.github.io/home/files/p...

Thoughts and comments welcome!

2/2

Now with correct links - forthcoming policy-papers and essays:

Individual property rights or collective democratic governance? Privacy in the age of AI
maxkasy.github.io/home/files/p...

Welfare for the 21st century: Basic income and job guarantee policies
maxkasy.github.io/home/files/p...

1/2

oops -
posting correct version momentarily, thanks!

(“one brain region for one character trait”). Hard to see a priori why that should be true for trained neural nets. Moreover, not clear why mechanisms should generalize between different nets.

I remain skeptical.
MI seems predicated on finding underlying computations that are neatly separable, modular or sparse, similar to the (failed) Mendelian paradigm in genetics (“one gene producing one observable trait”) or 19th century craniology

Mechanistic Interpretability for AI Safety -- A Review Understanding AI systems' inner workings is critical for ensuring value alignment and safety. This review explores mechanistic interpretability: reverse engineering the computational mechanisms and…

What is “mechanistic interpretability” (MI) of neural networks?
This paper gives a great introduction:
arxiv.org/abs/2404.14082

MI empirically explores “how neural networks work,” in a spirit similar to neuroscience - without the ethical constraints on manipulating living brains.

The Means of Prediction Check out this great listen on Audible.com. This is an audiobook version of this book. An eye-opening examination of how power—not technology—will define life with AI. AI is inescapable, from its...

📕 🔊 "The means of prediction" is now available as audiobook! 🔊 📕

www.audible.co.uk/pd/B0GL99H5J...

ICE Begins Buying ‘Mega’ Warehouse Detention Centers Across US Plans for such centers and jails in nearly two dozen communities have sparked protests over suitability, proximity to homes and schools.

Large scale conversion of warehouses into camps to concentrate migrants is taking place:

ICE Begins Buying ‘Mega’ Warehouse Detention Centers Across US Plans for such centers and jails in nearly two dozen communities have sparked protests over suitability, proximity to homes and schools.

Large scale conversion of warehouses into camps to concentrate migrants is taking place:

Iran in Revolt | Kayhan Valadbaygi Deep political-economic transformations are causing recurrent waves of unrest, with no long-term solution in sight.

What is the backdrop for recent protests in Iran?
Between concentration of economic power in semi-private foundations, intra-elite fractures, rising precarity, poverty, food and fuel prices, and state repression, this article provides excellent analysis:

Causal Machine Learning for the Social Sciences - Isaac Newton Institute Causal inference and machine learning are profoundly transforming the social sciences by enabling researchers to move beyond mere correlation to identify...

Looking forward to the workshop on “Causal Machine Learning for the Social Sciences” at the Newton Institute/Cambridge:
www.newton.ac.uk/event/cifw05/

I will discuss the big picture of possible research agendas at the intersection of ML, causality, and econ:
maxkasy.github.io/home/files/s...

Science personnel and funding gutted at astonishing scale in the US:

www.nature.com/immersive/d4...

Do you like charts? Oh yes you do. I've just published hundreds of them, as I do every year. www.nathanielbullard.com/presentations

Economics for Inclusive Prosperity Government Podcast · Updated Biweekly · We need an alternative vision of economics to replace failed neoliberalism and rising economic nationalism. In a world facing record inequality, climate peril, ...

Dani Rodrik and Suresh Naidu say economists need to adopt a broader view of prosperity, one that includes metrics of wellbeing like access to health, democratic participation, and a livable planet. Listen to the new Economics for Inclusive Prosperity podcast. #EfiP podcasts.apple.com/us/podcast/e...

Matt Walsh tweeted last year: "We've spent the last 25 years bringing "freedom" and "democracy" to countries around the globe while our own country has been systematically invaded and now our largest cities are run by foreigners and communists. If you want to know why I'm so avowedly non-interventionist, this is why." Then he tweeted today: ""This is a war for oil!!!!!" First of all, the "war" lasted like 90 minutes. Second, going to war to secure vital resources for your own people is totally legitimate. Why should we allow some third world communist shithole to control trillions of dollars worth of oil?"

Laura Loomer tweeted last year: "I’m America First, I don’t support “Regime Change”. I went on @Bannons_WarRoom to talk about Chinese aggression in Venezuela and why we need to designate the Muslim Brotherhood as a foreign Islamic terrorist organization." Then she tweeted yesterday: "Maduro has arrived at the DEA office in Manhattan. He was transported in an armored motorcade after being transported in a blindfold via helicopter & then by plane to New York after his compound in Caracas was raided by US Special Forces. Proud to be an American today! USA 🇺🇸"

Catturd tweeted last year: "Name one U.S. inspired regime change that hasn’t ended in absolute disaster." Then he tweeted yesterday: "Venezuela is now more free than New York City."

Will Chamberlain tweeted last year: "The Republican Party is no longer the party of regime change and endless wars If you want to be its standard-bearer that is a non-negotiable position" Then he tweeted yesterday: "I can think of few better uses of my tax dollars than black-bagging the head of a foreign narco-trafficking organization that enriches itself by addicting and poisoning my fellow Americans"

amazing how the entire machine can pivot within 24 hours. no need to slowly upsell the argument; just issue new marching orders

What is the intersection of machine learning, causal inference, and economics?
What are promising avenues for research at this intersection?

I just drafted a new talk exploring these questions:
maxkasy.github.io/home/files/s...

Thoughts and comments welcome!