Could AI Leapfrog the Web? Evidence from Teachers in Sierra Leone
This addresses the information access gap for teachers in low-connectivity regions, offering a cost-effective alternative to web search.
The study tackled the problem of low internet usage in sub-Saharan Africa due to high data costs by analyzing AI chatbot queries from teachers in Sierra Leone, finding that AI is 87% less expensive and rated more relevant and helpful than web search.
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.