Moral Economics: Book cover and jackets

 Getting a book out involves some tedium (e.g. trying to proofread the index) as well as many small excitements: here's the full book cover and jackets for Moral Economics:) 

 

 

 

Blurb I recently wrote (for a How-to on a familiar but surprising subject)

Like everything else in life, blurbs have editors, so not everything you write gets published.   

Some of the books I've read and blurbed might surprise you, such as this one (on a familiar subject, but a surprising one for a book):

You've Been Pooping All Wrong  by Dr. Trisha Pasricha (who I first encountered some years ago).

 Here's my blurb as it appears on the book's web page: 
“An entertaining and instructive book.”

  Here's the full blurb that I wrote

"Dr. Trisha Pasricha has written an entertaining and instructive book, in very plain language, about how our bodies turn inputs into outputs, along with tips on managing that. Along the way she writes equally clearly about the emerging, polysyllabic field of neurogastroenterology, which studies the lifelong, two-way conversation between brains and guts." 

 ##########

"My needs in life are simple, I want three things maybe four...a little love, just enough to eat, a warm place to sleep, and everything I write should be published"

Before I forget, coffee lowers risk of dementia

 Here's the good news, published yesterday in JAMA:

Coffee and Tea Intake, Dementia Risk, and Cognitive Function
Yu Zhang, MBBS1,2,3; Yuxi Liu, PhD2,3,4; Yanping Li, PhD1,2 et al,

JAMA, Published Online: February 9, 2026
doi: 10.1001/jama.2025.27259 

"Findings  In this prospective cohort study of 131 821 individuals from 2 cohorts with up to 43 years of follow-up, 11 033 dementia cases were documented. Higher caffeinated coffee intake was significantly associated with lower risk of dementia. Decaffeinated coffee intake was not significantly associated with dementia risk.

"Meaning  Higher caffeinated coffee intake was associated with more favorable cognitive outcomes. "

######

I figured I'd better pass along the news before I forget... 

Deadline tomorrow morning for Econometric Society conference on Economics and AI+ML

 Today's email announces a 9am Eastern time deadline tomorrow (that's 6am in California). And it looks like a fine conference.

FINAL CALL FOR PAPERS DEADLINE FEB. 10, 9:00 AM ET The 2026 ESIF Economics and AI+ML Meeting June 16 - 17, 2026 Reminder: authors can update their submitted papers until the submission period ends. The Econometric Society Interdisciplinary Frontiers (ESIF) conference on Economics and AI+ML will be hosted by Cornell University, in Ithaca NY, on June 16-17, 2026. The purpose of the meeting is to foster interaction of ideas and methodologies from the areas of Computer Science and Economics (broadly defined, but with emphasis on AI and ML). The conference will feature keynote lectures and parallel sessions, bringing together scholars from both fields. Important Dates Submissions open: November 3, 2025 Paper Submission Period: November 3, 2025 – February 10, 2026 Decision Notification Deadline: March 22, 2026 Registration Period (for presenters): March 22, 2026-April 5, 2026 Preliminary Program Announcement: April 26, 2026 Conference dates: June 16-17, 2026 Keynote Speakers David Blei, Columbia University Mingming Chen, Google Timothy Christensen, Yale University Annie Liang, Northwestern University Sendhil Mullainathan, MIT Aaron Roth, University of Pennsylvania Paper Submissions The deadline for submissions is February 10, 2026. Interested authors are encouraged to submit unpublished working papers or early drafts (more than 5 pages with results). Preference in the selection process will be given to complete papers. If you would like to submit a group of papers to be considered for the same session, please indicate the proposed session name in the comment section. While grouped submissions are welcome, please note that each paper will still be evaluated on its own merits. All papers and drafts must be submitted electronically in PDF format via the Oxford Abstracts submission platform.  Please use the appropriate submission link: Economist Track (Economics, Finance, Statistics, Marketing, Management) Computer Scientist track (Computer Science, Information Systems, and Operations Research/Operations Management) Submissions are open to all research that overlaps with both Economics and AI+ML. Each submission must select at least one content area from the drop-down menu. Note that the areas are partially overlapping; if in doubt, authors are advised to select those area(s) that best fit their paper. Also note that your submission details can be edited throughout the submission process up until the submission deadline of February 10, 2026. Please direct questions to esifaiml@gmail.com for more information, or visit the conference website. Program Committee Francesca Molinari and Eva Tardos (Cornell University; Co-Chairs) Nina Balcan, Carnegie Mellon University Sid Banerjee, Cornell University Dirk Bergemann, Yale University Martin Bichler, Technical University of Munich Larry Blume, Cornell University Emma Brunskill, Stanford University Flori Bunea, Cornell University Giacomo Calzolari, European Universitary Institute Denis Chetverikov, University of California Los Angeles Tim Christensen, Yale University Bruno Crepon, CREST Costis Daskalakis, MIT Sarah Dean, Cornell University Laura Doval, Columbia GSB David Easley, Cornell Maryam Farboodi, MIT Sloan Michal Feldman, Tel Aviv Christophe Gaillac, University of Geneva Avi Goldfarb, University of Toronto Rotman Jason Hartline, Northwestern Nicole Immorlica, Yale and MSR Jon Kleinberg, Cornell University Robert Kleinberg, Cornell University Anton Korinek, University of Virginia Elena Manresa, Princeton Mehryar Mohri, NYU, Google Xiaosheng Mu, Princeton University José Luis Montiel Olea, Cornell University Mallesh Pai, Rice David Parkes, Harvard David Pennock, Rutgers University Vianney Perchet, ENSAE Tuomas Sandholm, CMU Jon Schneider, Google Devavrat Shah, MIT Alex Slivkins, MSR Martin Spindler, Universität Hamburg Jörg Stoye, Cornell Vasilis Syrgkanis, Stanford Catherine Tucker, MIT Sloan

 

Danny Kahneman remembered by Gerd Gigerenzer

 Gerd Gigerenzer writes about Danny Kahneman and his work,  through the lens of Gigerenzer's own long and distinguished career criticizing and reinterpreting the biases and heuristics framework introduced by Kahneman and Tversky.

The  Legacy  of  Daniel  Kahneman:  A  Personal View  by GERD GIGERENZER    Erasmus Journal for Philosophy and Economics,Volume 18, Issue 1,Summer 2025, pp. 28–61https://doi.org/10.23941/ejpe.v18i1.1075

"Let me end with what may be Kahneman’s most important legacy: his willingness to engage in what he called “adversarial collaboration”. One can hardly overestimate the emotional strain it caused him. His openness to debate began with the three joint talks we had in the early 1990s and continued through the adversarial collaborations he initiated with several of his critics.

"Learning to separate the personal from the intellectual—to debate an issue without assuming malicious intentions on the other side—is one of the  most  virtuous  and  difficult  achievements  in  science.  The  history  of science is full of stories of those who failed to do so. Renaissance mathematicians once dueled over solutions to cubic equations, and Newton famously broke Leibnitz’s heart during their dispute over who invented calculus. That rivals eventually learned to speak to each other with respect, and even to cooperate, is a relatively recent development in the sciences (Daston 2023). "

##########

Side note: when I looked into the sentence "Renaissance mathematicians once dueled over solutions to cubic equations" I found that it didn't refer to guns or swords but rather to mathematical duels, which were exchanges of problems to see who could solve them, before open publication of methods became a scientific norm.

Interview in China (accompanying new edition of Who Gets What and Why)

 Southern People Weekly just published an interview about the new edition of the Chinese translation of my 2015 book Who Gets What and Why.  After talking about the book, they also asked questions about scientific work and Nobel prizes, and I'll include some of that below. (The English translation mostly renders "Roth" as "Ross," but in at least one place I am "Irwin Rothu.")

 Here's the link (in Chinese and in translation):

 正文
为什么“天上撒钱”不一定是好事？
南方人物周刊 2026-02-04 14:10

Why isn't "money falling from the sky" necessarily a good thing?
Southern People Weekly 2026-02-04 14:10
 

 Southern People Weekly: Although Nobel Prize-winning research often stems from studies conducted many years ago to see if it can withstand the test of time, in the long run, both the nationality distribution of laureates and the evolution of research topics reflect, to some extent, changes in the global economic power structure and intellectual trends. How do you view this interaction between "academics and the times"?

Ross: That's certainly true, both in the long and short term. After World War II, the United States' scientific research and university strength rose rapidly, leading the world and producing a large number of Nobel laureates. Among them were scholars who grew up in the United States, as well as scientists who were forced to migrate from Europe due to war and political circumstances.

Today, I have some concerns that the United States may be actively relinquishing this long-accumulated advantage—when outstanding scholars from around the world no longer feel comfortable and secure in American universities, they may choose to pursue their careers in China or Europe. Another noteworthy change is that, in the past, most economics professors at Peking University and Tsinghua University held doctorates from top American universities such as Princeton, MIT, or Harvard; now, an increasing number of professors are completing their doctoral education at Chinese universities. Overall, this is a good thing; more people dedicating themselves to scientific research benefits the world. I only hope that top American universities will continue to welcome scholars from all over the world.

Southern People Weekly: Every year when the Nobel Prize winners are announced, similar discussions erupt in China—despite its stellar economic performance, China still boasts a sparse number of Nobel laureates. A Chinese-American Nobel Prize judge, when discussing this phenomenon, stated that China's current evaluation system, centered on the number of papers and impact factors, objectively pushes research efforts towards already highly crowded and popular fields. The key to a breakthrough lies in identifying important research gaps and sustaining long-term, continuous investment. What advice do you have for young Chinese researchers?

Ross: There isn't just one way to do scientific research. Some people choose to tackle well-known, unsolved problems; they're running a "sprint." If you're not confident that you're smart enough to solve these well-known problems faster than others, then becoming famous through a sprint isn't for you.

Another path is to choose a job that requires long-term accumulation. I'm not referring to a marathon, which is still a race where speed is paramount, but rather to becoming a musician, which requires long-term creation and continuous exploration of new musical styles or genres to gain recognition.

Southern People Weekly: Your career path is the second one.

Ross: Yes, I've never considered myself smarter than anyone else. There wasn't much interest in matching theory early on, but I was very interested in it. My first paper on matching theory was initially submitted to an economics journal, titled "Matching Economics: Stability and Incentives." The journal's editor at the time was George Stigler, who was also the Nobel laureate in economics that year (1982).

He replied with a very polite letter, saying he had read the paper and found it "very interesting," but the only part of the entire article that could be considered economics was the word "economics" in the title. The paper discussed how to achieve stable matching through institutional arrangements in the absence of price adjustments and analyzed the incentives of participants. Stigler is one of the core economists of the Chicago School, known for his in-depth research on price theory. In his view, my paper did not constitute economic research.

So I published the paper in a mathematical operations research journal. Thirty years later, I won the Nobel Prize. During this time, matching theory gradually became part of economics, attracting more and more economists' attention. How could it not be (economics)? How people go to school, find jobs, and allocate kidney transplant resources are essentially matching problems. That (rejected) paper later became one of the papers cited in the Nobel Prize review.

Regardless of which path you choose, you should not make the Nobel Prize your research goal, because winning the prize itself is highly accidental.

Southern People Weekly: So, chasing a certain direction just because it seems important or popular may not necessarily bring you the success you want; similarly, you shouldn't give up your passion just because it's not popular or hasn't been recognized yet.

Ross: I often tell my graduate and doctoral students that you have to find a research area that is attractive enough to you. Because most days, you may not make any progress, but at the end of the day, you can still say to yourself, "Well, today was pretty interesting too." It is this enjoyment that draws you back to the work time and time again. ... you can't make something you dislike into something great.
...

Southern People Weekly: Some media outlets have summarized the Trump administration's trade strategy as using high-pressure threats, setting tight deadlines, and structured negotiation frameworks to leverage uncertainty and bargaining power to force concessions from the other side. From a game theory perspective, how do you evaluate this strategy?

Ross: I have some concerns that the current U.S. administration may not yet fully grasp the importance of being a reliable partner. Any long-term partnership, like a marriage, cannot involve daily discussions about "who does the dishes." True long-term cooperation means investing in the future at every moment, not just focusing on immediate gains. I fear we have overlooked this.

...

Southern People Weekly: Your academic journey also had its share of ups and downs—you dropped out of high school due to a lack of motivation, but successfully applied to university by taking weekend engineering courses at Columbia University; you failed your doctoral qualifying exam, but gained the appreciation of Bob Wilson (the American economist who won the Nobel Prize in Economics in 2020), thus avoiding an unexpected interruption to your academic career. Do these life experiences influence your views on "matching mechanisms"?

Ross: Absolutely. There's something "magical" about the PhD program: when we admit students, we base our decisions on their undergraduate performance—the only information we have when making admissions decisions. But when we "sell" them and help them find jobs, we base our decisions on the research they've done during their PhD studies.

In other words, we admit students based on their ability to learn existing knowledge and complete coursework, but evaluate and recommend them based on their ability to discover the unknown and create new knowledge. These two abilities are not entirely the same. Unfortunately, we don't have a good way to accurately predict how outstanding a person will become as a researcher based solely on their undergraduate performance. 

##############

Earlier interview:

Wednesday, December 24, 2025  Interview about the new edition of the Chinese translation of Who Gets What and Why

 

Are some applications of AI repugnant?

Here's a new HBS working paper on repugnance of A.I.

 Performance or Principle: Resistance to Artificial Intelligence in the U.S. Labor Market
By: Simon Friis and James W. Riley

Abstract
From genetically modified foods to autonomous vehicles, society often resists otherwise beneficial technologies. Resistance can arise from performance-based concerns, which fade as technology improves, or from principle-based objections, which persist regardless of capability. Using a large-scale U.S. survey quota-matched to census demographics and assessing 940 occupations (N = 23,570 occupation ratings), we disentangle these sources in the context of artificial intelligence (AI). Despite cultural anxiety about artificial intelligence displacing human workers, we find that Americans show surprising willingness to cede most occupations to machines. Given current AI capabilities, the public already supports automating 30% of occupations. When AI is described as outperforming humans at lower cost, support for automation nearly doubles to 58% of occupations. Yet a narrow subset (12%)—including caregiving, therapy, and spiritual leadership—remains categorically off-limits because such automation is seen as morally repugnant. This shift reveals that for most occupations, resistance to AI is rooted in performance concerns that fade as AI capabilities improve, rather than principled objections about what work must remain human. Occupations facing public resistance to the use of AI tend to provide higher wages and disproportionately employ White and female workers. Thus, public resistance to AI risks reinforcing economic and racial inequality even as it partially mitigates gender inequality. These findings clarify the “moral economy of work,” in which society shields certain roles not due to technical limits but to enduring beliefs about dignity, care, and meaning. By distinguishing performance- from principle-based objections, we provide a framework for anticipating and navigating resistance to technology adoption across domains. 

 

 

When AI use is morally repugnant

Researchers used a moral repugnance scale (1-7) to measure public resistance to automation across 940 occupations. They found widespread support for AI in some roles but others remain categorically off-limits, regardless of AI’s capabilities.

Occupation	Repugnance score
Clergy	5.91
Childcare workers	5.86
Marriage and family therapists	5.64
Administrative law judges, adjudicators, and hearing officers	5.62
Athletes and sports competitors	5.52
Biostatisticians	2.54
Switchboard operators, including answering service	2.52
Transportation planners	2.38
Search marketing strategists	2.31
File clerks	2.17

 

Moral Economics: back-cover blurbs

 I now know what blurbs will likely be on the back cover of Moral Economics when it comes out in May. They are by Peter Singer, Abhijit Banerjee & Esther Duflo, Claudia Goldin, and Paul Milgrom & Bob Wilson, all people whose work I admire more than I can say.

    “Alvin Roth received the Nobel Prize for work in economics that has saved thousands of lives. In Moral Economics, Roth applies his open-minded, evidence-based thinking to controversial issues at the intersection of markets and morals, where his way of thinking could save even more lives.”
    Peter Singer, author of Ethics in the Real World

    “A surprising large part of economics is about things money can't buy, for many good and bad and complicated reasons. This wonderful book by the leading scholar in that area of economics is something else that just money could never buy. It's a labor of love, a testament from a lifetime of thought and research.”
    Abhijit V. Banerjee and Esther Duflo, Nobel laureates and authors of Poor Economics

    “With clarity and compassion, Al Roth explores the transactions society cannot escape—surrogacy, the purchase of body parts, the sale of sex, and a host of ‘repugnant’ relationships. What should be regulated? What should be banned? What are the limits of using price in the marketplace? Be prepared to think in new ways and gain from the insights of a great market designer.”
    Claudia Goldin, Nobel laureate and author of Career and Family

    “From the right to sell a kidney to the cost of a surrogate birth, our sense of ‘right and wrong’ shapes the economy more than we realize. Nobel laureate Alvin Roth—the world's leading ‘philosopher-economist’—unpacks the hidden moral codes that govern our most intimate transactions. This is a clear-eyed guide to understanding where the market ends, where morality begins, and how we can design a world that honors both.”
    Paul Milgrom and Robert Wilson, Nobel laureates, Stanford University