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Paradigm Challenge  /  Economics

Unlike regular government programs that get messy as they grow, AI-run projects actually work way better the bigger they get.

Most social policies suffer from a 'voltage drop' when moving from a small test to the real world. However, because algorithms improve with more data, scaling an educational AI to a larger population made it 2.5 times more effective than the initial controlled trial results indicated.

Original Paper

The Economics of Algorithmic Personalization: Evidence from an Educational Technology Platform

Keshav Agrawal, Susan Carleton Athey, Ayush Kanodia, Shanjukta Nath, Emil Palikot

SSRN  ·  6425002

Can personalized recommendations improve engagement in educational technology? We design, test, and scale a collaborative filtering system for Freadom, an English-learning app for Indian children. A randomized controlled trial (RCT) with 7,750 students shows that personalization, deployed in a single content section, increases engagement by 60% in that section and by 14% app-wide. We then exploit an eligibility threshold in a regression discontinuity design (RDD) to track effects over five month