A Taxonomy of AI Experiments
We introduce a taxonomy of artificial intelligence (AI) experiments. Our taxonomy produces four types of AI experiments: conceptual AI experiments, stylized AI
π₯³ Stoked to share that our paper with Christina Strobel, "A Taxonomy of Al Experiments," has been accepted at the Journal of Behavioral and Experimental Economics!
Huge thanks to Christina for collab and to the reviewers for extremely helpful feedback!
papers.ssrn.com/sol3/papers....
#EconSky
16.01.2026 16:47 β π 2 π 1 π¬ 1 π 0
My Game Christmas Tree. What's on yours?
23.12.2025 13:41 β π 0 π 0 π¬ 0 π 0
If you are on the market and it feels tough, know this. You are amazing. You have come this far, be proud of yourself. Rejection hurts, but you are not your rejection. Know your worth, shine your light.
14.12.2025 11:24 β π 1 π 0 π¬ 0 π 0
Congratulations!!
11.12.2025 15:19 β π 1 π 0 π¬ 0 π 0
This tip will be helpful for anyone who uses Beamer-made slides (or any PDF slides in fact) with a dual-screen setup, where the slides are projected on a big screen from a laptop in extended display mode. And who cares about their neck.
aalexee.com/post/2025-11...
02.11.2025 11:23 β π 0 π 0 π¬ 0 π 0
Plugging in the duck race numbers, n=6000, k=100, m=3, we get about a 5% chance of winning.
We didnβt win, but on the plus side it was the most rubber ducks Iβve ever seen π¦
20.10.2025 18:32 β π 0 π 0 π¬ 0 π 0
Clearly, what changes here is the number of non-winning combinations. If you buy m tickets, then this number is "n-m choose k". And then we compute the probability of winning as before, although it does not simplify nicely.
20.10.2025 18:32 β π 0 π 0 π¬ 1 π 0
Letβs start slow. Suppose there are four tickets (A,B,C,D). But now assume that you bought tickets A and B. There are still six possible combinations of two tickets: AB, AC, AD, BC, BD, CD. But now five of them lead to a prize, hence the probability of winning is 5β6.
20.10.2025 18:32 β π 0 π 0 π¬ 1 π 0
What if you bought more than one ticket, though? What is the probability of having at least one ticket win? It cannot be simply the sum of probabilities of a single ticket winning.
20.10.2025 18:32 β π 0 π 0 π¬ 1 π 0
Applying the formula to the duck race, we get a probability of winning, p = 100β6000, about 2%.
20.10.2025 18:32 β π 0 π 0 π¬ 1 π 0
Then the number of winning combinations is the difference between the total number of combinations and the number of non-winning combinations. After some algebra, it turns out that the probability of winning is simply k/n.
20.10.2025 18:32 β π 0 π 0 π¬ 1 π 0
But what is the number of winning combinations? It seems that it is easier to find the number of non-winning combinations. This is just the total number of combinations of k elements that do not include our ticket: "n-1 choose k".
20.10.2025 18:32 β π 0 π 0 π¬ 1 π 0
It is easy to see the pattern. If there are n tickets in total and k randomly chosen tickets win, the total number of possibilities, which is the number of combinations of k elements from the set of n elements, is simply "n choose k".
20.10.2025 18:32 β π 0 π 0 π¬ 1 π 0
Now suppose there are 4 tickets (A,B,C,D). Again, you have A, two tickets win.
Possible pairs are: AB, AC, AD, BC, BD, CD.
You win in three pairs, hence the chance of winning is 1/2
20.10.2025 18:32 β π 0 π 0 π¬ 1 π 0
Suppose there are 3 tickets (A,B,C). You have A. Two tickets win.
All possible pairs are AB, AC, BC.
You win in two cases, hence the probability of winning is 2/3.
20.10.2025 18:32 β π 0 π 0 π¬ 1 π 0
If 1 ticket wins out of 6,000, and you bought 3 tickets, your chance of winning is 3/6000.
But what if 100 tickets win? Thatβs less obvious. Let's build intuition through simple examples
20.10.2025 18:32 β π 0 π 0 π¬ 1 π 0
π¦ Last weekend, Regensburg hosted a duck race. 6,000 rubber ducks drifting through a canal. Each duck corresponds to a lottery ticket. The first 100 ducks to finish win prizes. We bought 3 tickets. What are our odds of winning?
β‘οΈ Read more: aalexee.com/post/2025-10...
20.10.2025 18:32 β π 0 π 0 π¬ 1 π 0
Thanks so much for the support!
15.10.2025 10:03 β π 1 π 0 π¬ 0 π 0
The (Statistical) Power of Incentives | Journal of the Economic Science Association | Cambridge Core
The (Statistical) Power of Incentives
Thrilled to see my paper "The (Statistical) Power of Incentives" out at the Journal of the Economic Science Association. π₯³
Read it here (open access) π dx.doi.org/10.1017/esa....
#Econsky
10.10.2025 19:39 β π 8 π 3 π¬ 0 π 1
Inspired by this amazing graphic that I found at a ramen place in Brno
19.09.2025 15:46 β π 0 π 0 π¬ 0 π 0
How to participate in an ESA meeting
Step 1. Attend plenary talks
Step 2. Attend sessions
Step 3. Attend social events
Step 4. Meet new people and catch up with old friends
Step 5. Oh no, the conference is over
Step 6. Lie down
Step 7. Try not to cry
Step 8. Cry a lot
@ecscienceassoc.bsky.social
19.09.2025 15:46 β π 0 π 0 π¬ 1 π 0
Big thanks to @fialalenka.bsky.social and @i4replication.bsky.social for the replication games in Brno. It was fun. We loved the songs! π€
08.09.2025 06:03 β π 5 π 1 π¬ 0 π 0
π Huge thanks to @milosfisar.bsky.social and the team at @econmuni.bsky.social for a fantastic @ecscienceassoc.bsky.social meeting in Brno
#econsky
06.09.2025 19:13 β π 2 π 0 π¬ 0 π 0
iOS autocorrects βtexβ as βTexβ
It autocorrects βxetexβ as βXeTeXβ
It does not autocorrect βlatexβ
Can you guess what it autocorrects as βlistedβ?
π€
08.08.2025 08:13 β π 1 π 0 π¬ 0 π 0
The (Statistical) Power of Incentives
I study the optimal design of monetary incentives in experiments where incentives are a treatment variable. I propose a novel framework called the Budget Minimi
π Excited to share that my paper "The (Statistical) Power of Incentives" has been accepted at the Journal of the Economic Science Association! @ecscienceassoc.bsky.social
Thanks to everyone who helped me on this journey.
ssrn.com/abstract=408...
#EconSky
30.07.2025 16:11 β π 2 π 0 π¬ 0 π 0
Remember, your .tex file is just text. Use any editor you like. Dedicated LaTeX editors are great for typesetting, but you can use other editors.
Share your LaTeX writing tips below! π
14.07.2025 16:14 β π 0 π 0 π¬ 0 π 0
Personalize. Choose a font you love (not just a default), and find a theme that feels right.
14.07.2025 16:14 β π 0 π 0 π¬ 1 π 0
Next, adjust your editor's line width. A narrower column (80 chars) is way easier to read than a full-screen line.
14.07.2025 16:14 β π 0 π 0 π¬ 1 π 0
First, ditch the split-screen. Close that PDF preview while you're writing. Focus on the words, not the layout.
14.07.2025 16:14 β π 0 π 0 π¬ 1 π 0
Professor, Researcher, Behavioral Scientist.
Pompeu Fabra University, Barcelona School of Economics, Barcelona School of Management.
Associate Professor, CEU Vienna & Senior Researcher, University of Vienna
Want to learn this and that, and wait, that tooβ¦
Researcher in Economics (CNRS, CIRED). π³οΈβπ
Animal welfare, diets, experiments.
Γlu CNRS 37.
Postdoc @ Tilburg University. Research Interests: Labor and Gender. Primarily use field and lab experiments. Website: https://yukitakahashi1.github.io
Assistant Professor at Masaryk University
Experimental and Behavioral Economics | Fraud and Destructive Behavior in Competitive Settings & Social Norms
Website: https://sites.google.com/view/jonathanstaebler
Assistant prof. at the University of Leeds. Focus on economic experiments on behaviour + environment + health. Fan of black cats and ravens.
https://sites.google.com/view/imussio/
Economist at UToledo. π¦πΊ Bayesian Econometrics for economic experiments and Behavioral Economics
Free online book on this stuff here: https://jamesblandecon.github.io/StructuralBayesianTechniques/section.html
https://sites.google.com/site/jamesbland/
He/his
Risk and uncertainty, Feyenoord supporter in short Beh. Econ Ph.D. at Erasmus University Rotterdam and @tinbergeninstitute.bsky.social. Always had a hard time deciding so I am studying decision making. π¨π΄
https://sites.google.com/view/drgonzalez-jimenez
Professor at UiS Business School. Lives in π³π΄ #FinSky #EconSky
Experimental finance and economics
Professor @ University of Stavanger
https://sites.google.com/view/olgarud
Researcher @cnrs.bsky.social
& Econ. Prof. @IESEG
. Director of iRisk research center. Assoc. researcher at CMCC
. Interests: #risk & #uncertainty, #climatechange
Behavioral Economist at WZB & SOEP/DIW Berlin | open science | metascience | street photography
https://sites.google.com/site/leventneyse
Lab^2
https://labsquare.net
I am a behavioral/experimental economist at Alabama
Roll Tide!
Associate Professor at the University of Birmingham β Neuroeconomics, Decision Neuroscience, and Behavioral Economics β Previously at the University of Zurich and Ohio State β #StandWithUkraine
Professor at Rotman, University of Toronto. Economics of digital technology and AI.
Econometrician, piano-player, and football freestyler
I am an Economist leveraging the assignment mechanism in the field to test theory and help non-profits, govts, and anyone who will listen! My goal is to (hopefully!) change the world for the better. My picture is with my oldest son!
Assistant Professor of Economics at Lehigh and Pitt alum. Interested in behavioral, experiments, and labor.
Behavioral economist, studying information & attention @ UC San Diego