A question for premium AI subscribers. From July 7, Anthropic moves Fable 5, one of its strongest models, behind paid usage credits on top of the Max fee. Paying for the top tier should include the best model. Include Fable 5 in Max. Repost if you agree. #AI #ClaudeAI

One-day workshop at Chalmers on 5 June: Principled Statistics in the Age of AI (PSAI26). Speakers: Xiao-Li Meng (keynote, Harvard), Joshua Bon, Cory McCartan, Fredrik Johansson, Ashkan Panahi. Free, registration by 29 May → jameshbailie.github.io/PSAI26/

CW: suicide. Honoured to be Guest Editing—with @saurabhkhanna.bsky.social—a Special Issue at ACM-TSC in tribute of my intellectual hero, Aaron Swartz, who died by suicide in 2013 at 26 after extreme prosecutorial overreach. While attempting to expand access to knowledge. CfP: tinyurl.com/4znbk4y2.

PhD opening at Chalmers / AI and Global Development Lab: Earth Observation, Data Science, and AI for poverty estimation. Deep learning on Sentinel-2 imagery, benchmarked against Pléiades and Landsat, with AI-explainability. Deadline 13 June 2026. www.chalmers.se/en/about-cha...

Postdoc opening at Chalmers / AI and Global Development Lab: Data Science & Statistics. Estimating poverty from satellite imagery of African communities; causal inference and prediction-powered inference for policy evaluation. Deadline 27 May 2026. www.chalmers.se/en/about-cha...

Calling social-computing folks: ICSC 2026 submissions are open. Nuffield College, Oxford 3–4 Sept 2026 (workshop 2 Sept) submission deadline 25 May 2026 Computational demography, LLMs, media analytics, digital inclusion, open science. Springer CCIS proceedings. icsc-conf.github.io/2026/call.html

A rare opportunity position! careersearch.stanford.edu/jobs/program...

Program Director in Dean of Research, Stanford, California, United States

SCHOOL/UNIT DESCRIPTION:Since its creation in 1954, researchers associated with the Center for Advanced Study in the Behavioral Sciences (CASBS) at...

careersearch.stanford.edu

Most of what a scientist does never makes it into a paper — choosing problems, building teams, using AI well, knowing when to let go. I'm starting a Substack about that messy middle. One essay every other week. First one is up: adeldaoud.substack.com/p/the-invisi...

The Invisible Half of the Job

Why I’m starting a working notebook in public — about research, AI, teams, and the things that don’t fit into a journal article.

adeldaoud.substack.com

Looking forward to giving a presentation on the planetary causal inference paradigm at Department of Methodology, LSE, today. Join us if you are around. www.lse.ac.uk/methodology/...

Seminar series

Information about the Department of Methodology seminar series

lse.ac.uk

Sign up for this week's Seminar Series with @adeldaoud.bsky.social 💡 21 Nov, 2 - 3pm 🌎Planetary Causal Inference: combining computer vision and earth observation to analyse disparities in health and living conditions among neighbourhoods in Africa, 1990 to date www.eventbrite.com/e/department...

Exciting opportunity! Our AI and Global Development Lab is looking to fill a new position. Check out our research first at www.aidevlab.org for suitability. Then, hurry, the job ad has a deadline approaching soon: lnkd.in/dbSUxibq.

If you are in the vicinity of Oxford University, join me today at 4 pm for my talk at Nuffield College. Title: "Planetary Causal Inference: combining computer vision and earth observation to..." Link to event details: [Sociology Seminar at Nuffield College](www.nuffield.ox.ac.uk/news-events/...)

Event - Nuffield College Oxford University

nuffield.ox.ac.uk

Are you interested in using earth observation data and deep learning for estimating poverty in Africa, poverty specifically? Then apply to this research engineer position at AI and Global Development Lab. More info about our research at www.aidevlab.org . Deadline is 7th Nov. lnkd.in/ePX7VT-K

ML wealth maps from space 🛰️ are great, but suffer from "shrinkage" bias, which waters down policy impact results (causal inference). We developed correction methods that fix this bias *without* new data. arxiv.org/abs/2508.01341 #CausalInference #DataForGood #AI #PovertyMapping #EarthObservation

Topic @adeldaoud.bsky.social and I were discussing today at lunch at #ic2s2 and want to ask here: What are the “known facts” in the social sciences? Which relationships between at least two social variables have been empirically found to have large effects and replicated by multiple groups?

Debiasing ML predictions for causal inference—no new labels needed. We propose Tweedie’s correction to fix shrinkage enabling “one map, many trials.” arxiv.org/abs/2508.01341 #CausalInference #MachineLearning #EarthObservation #PovertyMapping

Debiasing Machine Learning Predictions for Causal Inference Without Additional Ground Truth Data: "One Map, Many Trials" in Satellite-Driven Poverty Analysis

Machine learning models trained on Earth observation data, such as satellite imagery, have demonstrated significant promise in predicting household-level wealth indices, enabling the creation of high-...

arxiv.org

open.substack.com/pub/aiglobal...

Earth Observation Meets Adam Smith: Earth Observation AI in Policy Innovation for Global Development

by Connor Jerzak

open.substack.com