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...

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

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.

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...

Seminar series Information about the Department of Methodology seminar series

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/...

poster that reads 'seminar series, 21 nov 2-3pm, professor adel daoud

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.

Event - Nuffield College Oxford University

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/...)

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

Deep question--and as a social scientist, I am not sure what candidate I would suggest. Is the social world too dependent on context or are there hard facts? e.g., take @rensec.bsky.social suggestion: would education produce the same outcome if a person lived in the Stone Age?

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 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-...

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

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

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