Photos and videos
Angel T-H Chung retweeted
Jun 1
Nobel Prize winning economist Kenneth Arrow wrote about "learning by doing" decades ago. He knew that productivity and expertise improve through experience.
The messy, repetitive works is often where you learn the patterns that eventually become judgment. Knowledge can be taught, but judgement is built through lived experience.
The first draft you rewrite. The customer call you listen to. The bug you fix and fix again. The factory floor you walk.
Small decisions you make every day teach you judgement. And, judgement is the thing everyone wants from senior people in the workplace. If we automate away every entry-level task without replacing the learning loop, we are removing a part of the process that creates experts.
The goal should be to use AI to accelerate learning, remove friction, and give people better tools to build expertise faster.
haverford.edu/sites/default/…
Thanks @Fortune & @tbove4 for sharing this story. Link in the comments.
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Angel T-H Chung retweeted
Apr 30
Places to look for ambitious, creative, rigorous health AI:
Sierra Leone, Thailand, Rwanda.
A short comment in @Nature nature.com/articles/d41586-0…
Don't miss the main course: amazing new paper by @AngelTHChung
@obastani @hamsabastani
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Angel T-H Chung retweeted
Apr 30
Our years-long collaboration with Sierra Leone is out in @Nature today! We improve allocation of essential medicines in Sierra Leone's Free Healthcare Initiative by an estimated 19% for ~2 million pregnant women and young children. To achieve this, we deployed a computationally tractable "decision-aware" forecasting stochastic optimization pipeline at scale -- a topic of considerable recent interest in the OR/CS communities.
This project has been an incredibly long and challenging path to fruition, made possibly only by @AngelTHChung's tireless efforts, @obastani's brilliance and the support of our coauthors in the Sierra Leone administration. None of us worked on this primarily to write a research paper, so this was an extra happy outcome.
This work was generously supported by @WhartonAIAI, @Wharton Mack Institute for Innovation Management & Global Initiatives.
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Angel T-H Chung retweeted
Mar 29
The research team (including @hamsabastani who is on X) found that letting students just use AI resulted in them using it to accidentally shortcut learning
But both that study and a separate RCT found that AIs prompted to act as a tutor improved learning papers.ssrn.com/sol3/papers.…
Mar 28
Wharton researchers gave nearly 1,000 high school math students access to ChatGPT during practice problems
Result: chatGPT is the perfect trap.
Look at the red bars.
Students with ChatGPT crushed their practice sessions.
The basic ChatGPT group solved more problems and those on the "tutor" version did even more.
Now look at the gray bars. That's the exam.
No AI allowed.
The ChatGPT group scored 17% worse than kids who practiced with zero technology.
And the fancy tutor version?
No better than working alone.
The researchers called AI a "crutch."
When they analyzed what students actually typed into ChatGPT, most of them just wrote - “What’s the answer?”
The kicker: students who used ChatGPT believed it hadn't hurt their learning.
They were confidently wrong.
This is the AI trap in education.
Outsourcing your thinking.
Of course, lots of half-baked AI literacy curricula being rolled out in schools now
Let’s of course ignore that basic literacy (the ability to read) is possible for <50% of 8th graders
Source: Bastani et al. (2025), "Generative AI Can Harm Learning," PNAS
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Angel T-H Chung retweeted
Mar 17
🚨🚨 Excited to share our first *positive* results on AI in education!
Most AI tutor work focuses on making the chatbot better. We suggest another lever: deciding what students should practice next to improve learning.
We combine an LLM tutor with reinforcement learning to personalize problem sequencing using signals from student-chatbot interactions and solution attempts.
We tested this in a 5-month randomized field experiment in a Python course across 10 high schools in Taipei. All students had the same course material and the same AI tutor. The only difference was adaptive vs. fixed problem sequencing.
Result: across 770 students, adaptive sequencing improved performance on an in-person final exam taken without AI assistance by 0.15 SD, with larger effects for beginners. Our evidence suggests the gains came from stronger engagement and more productive AI use.
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Angel T-H Chung retweeted
Mar 17
AI really can help education: Randomized controlled experiment on high school students found a GPT-4o powered tutor that personalized problems for students raised final test scores by .15 SD, "equivalent to as much as six to nine months of additional schooling by some estimates"
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27 Mar 2024
Excited to share our work w/ @hamsabastani and @obastani as my debut post at X!
26 Mar 2024
Learn how @Wharton PhD student, @AngelTHChung, leveraged machine learning to help the government of Sierra Leone distribute limited medical aid to the communities who need it most, as we continue to highlight Wharton Women in Analytics.
whr.tn/43ChQhO
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Angel T-H Chung retweeted
26 Mar 2024
Check out the awesome work @AngelTHChung has been doing to improve health supply chains in Sierra Leone! Recent deployment improved patient access to essential meds by ~20%!
26 Mar 2024
Learn how @Wharton PhD student, @AngelTHChung, leveraged machine learning to help the government of Sierra Leone distribute limited medical aid to the communities who need it most, as we continue to highlight Wharton Women in Analytics.
whr.tn/43ChQhO
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