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

Papers from arXiv.org

Abstract: Although 85% of sub-Saharan Africa's population is covered by mobile broadband signal, only 37% use the internet, and those who do seldom use the web. The most frequently cited reason for low internet usage is the cost of data. We investigate whether AI can bridge this gap by analyzing 40,350 queries submitted to an AI chatbot by 469 teachers in Sierra Leone over 17 months. Teachers use AI for teaching assistance more frequently than web search. We compare the AI responses to the corresponding top search results for the same queries from the most popular local web search engine, google.com.sl. Only 2% of results for corresponding web searches contain content from in country. Additionally, the average web search result consumes 3,107 times more data than an AI response. Bandwidth alone costs \$2.41 per thousand web search results loaded, while the total cost of AI is \$0.30 per thousand responses. As a result, AI is 87% less expensive than web search. In blinded evaluations, an independent sample of teachers rate AI responses as more relevant, helpful, and correct than web search results. These findings suggest that AI-driven solutions can cost-effectively bridge information gaps in low-connectivity regions.

Date: 2025-02, Revised 2025-03
New Economics Papers: this item is included in nep-afr
References: Add references at 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 ().