Could AI Leapfrog the Web? Evidence from Teachers in Sierra Leone

Daniel Bj\"orkegren, Jun Ho Choi, Divya Budihal, Dominic Sobhani, Oliver Garrod and Paul Atherton
Authors registered in the RePEc Author Service: Daniel Björkegren

Papers from arXiv.org

Abstract: Only 37% of sub-Saharan Africans use the internet, and those who do seldom rely on traditional web search. A major reason is that bandwidth is scarce and costly. We study whether an AI-powered WhatsApp chatbot can bridge this gap by analyzing 40,350 queries submitted by 529 Sierra Leonean teachers over 17 months. Each month, more teachers relied on AI than web search for teaching assistance. We compare the AI responses to the top results from google.com.sl, which mostly returns web pages formatted for foreign users: just 2% of pages originate in-country. Also, each web page consumes 3,107 times more bandwidth than an AI response on average. As a result, querying AI through WhatsApp is 98% less expensive than loading a web page, even including AI compute costs. In blinded evaluations, an independent sample of teachers rate AI responses as more relevant, helpful, and correct answers to queries than web search results. These findings suggest that AI can provide cost-effective access to information in low-connectivity environments.

Date: 2025-02, Revised 2025-12
New Economics Papers: this item is included in nep-afr and nep-ict
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/2502.12397 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2502.12397

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().