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dc.titleScaling Up Counseling with AI: Evidence from a Nationwide Experiment
dc.contributor.authorAjzenman, Nicolás
dc.contributor.authorDel Toro Mijares, Ana Teresa
dc.contributor.authorElacqua, Gregory
dc.contributor.authorHermosilla, Catalina
dc.contributor.authorVeleda, Santiago Nicolas
dc.contributor.orgunitEducation Division
dc.coverageChile
dc.date.available2026-10-07T00:10:00
dc.date.issue2026-10-07T00:10:00
dc.description.abstractA central obstacle to scaling many interventions is implementer quality: as a program expands and the pool of implementers broadens, average quality falls. Conversation-based interventions (counseling, mentoring) are particularly sensitive to this constraint. LLMs offer a natural way out: personalized exchanges at zero marginal cost and uniform quality. We run a nationwide experiment in Chile (N42,000) designed to reduce teacher shortages by increasing applications to education majors. We compare an AI chatbot, Kai, with trained human counselors, both reaching high school seniors via WhatsApp. Among students with baseline interest in education (the interventions target), Kai significantly increases first-ranked education majors and the share of education majors in students choice sets; estimates in the human arm are smaller and not significant. Although the best human counselors are highly effective, Kai matches or outperforms roughly two- thirds of them. Its advantage lies in what we call “controlled variance”: it compresses the dispersion in quality observed across human implementers. Finally, text analysis reveals different interaction patterns across arms. Kai concentrates on factual content and scores higher on semantic coherence, while counselors score substantially higher on motivational and empathetic language.
dc.format.extent69
dc.identifier.doihttp://dx.doi.org/10.18235/0014549
dc.identifier.urlhttps://publications.iadb.org/publications/english/document/Scaling-Up-Counseling-with-AI-Evidence-from-a-Nationwide-Experiment.pdf
dc.language.isoen
dc.publisherInter-American Development Bank
dc.subjectEducation
dc.subjectArtificial Intelligence
dc.subjectEducational Institution
dc.subjectEconomy
dc.subjectHigh School
dc.subjectHigher Education
dc.subjectLabor Force
dc.subjectEvaluation
dc.subject.jelcodeD91 - Intertemporal Household Choice • Life Cycle Models and Saving
dc.subject.jelcodeI23 - Higher Education • Research Institutions
dc.subject.jelcodeI25 - Education and Economic Development
dc.subject.keywordsTeachers;teacher shortages;Sclae-up;behavioral interventions;AI chatbots;Generative AI
dc.typeWorking Papers
idb.identifier.pubnumberIDB-WP-01887
idb.operationRG-E2057
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