Blog
Insights, commentary, and updates from the replication community.
BITSS Annual Conference Takeaways
We presented our Second Meta Paper at the Berkeley Institute for Transparency in the Social Sciences (BITSS) Annual Conference on April 16th. Our presentation built on our First Meta Paper: assessing reproducibility and robustness in the social sciences.
May 25, 2026 · Derek Mikola
What Three UK Events Showed Me About the I4R Network
Last week, I4R felt less like an organization and more like a living research network. On Monday, researchers gathered in Cambridge. Two days later, another group met at University College London. The next day, we were at King’s College London. Different rooms, different participants, different local teams, but one shared purpose: to understand how AI is changing research.
May 22, 2026 · Juan P. Aparicio
A Sourdough Reminder About Decision Making Without Statistics
My mother and I troubleshoot her twice-weekly sourdough. It passes any reasonable test: it is bread. It is safe to eat. It is great buttered, toasted, sandwiched or crouton-ed. It keeps a couple of days. It is the delicious carb you want to eat.
May 21, 2026 · Derek Mikola
What is our place in the multiverse?
The notions of reproducibility and robustness are foundational to the work we do at the Institute for Replication. A related term that has been making the rounds recently is “multiverse analysis”, so I naturally had to look into it. The origin of the term can be traced back to S…
April 21, 2026 · Luna Fazio
Non-random coding errors
Just a normal conversation between researchers: A: I ran the test, the effect is negative and not significant. B: That must be wrong. I saw the graph, the effect clearly exists and is positive. A: I'll double check the code. Maybe person B is right:
April 14, 2026 · Lenka Fiala
The Citation Mills
When we talk about research transparency and credibility, the first thing that comes to mind is whether results are reproducible. We spend a great deal of time checking whether code runs correctly, carefully combing through it to catch even the smallest errors. When everything c…
April 7, 2026 · Ghina Abdul Baki
The AI Replication Engine: New Experiments, New Results, and the Road to Beta
When we first introduced the AI Replication Engine in November 2025 ( blog ), the goal was to build a system that could help automate research verification at scale. In February 2026 ( blog ), we shared the first benchmark results and showed that autonomous replication was alrea…
March 30, 2026 · Bruno Barbarioli
The Future of ROI-Based Philanthropy in the Age of AI
ROI-based philanthropy is entering a new phase. For a long time, the basic playbook was simple enough to feel sturdy: find a study with a promising result, use the reported effect size to estimate social benefit, compare that benefit to cost, and let the result help shape fundin…
March 25, 2026 · Juan Posada Aparicio