Large Language Models vs. Search Engines: Evaluating User Preferences Across Varied Information Retrieval Scenarios

Understand

This study embarked on a comprehensive exploration of user preferences between Search Engines and Large Language Models (LLMs) in the context of various information retrieval scenarios.

• Conducted with a sample size of 100 internet users (N=100) from across the United States, the research delved into 20 distinct use cases ranging from factual searches, such as looking up COVID-19 guidelines, to more subjective tasks, like seeking interpretations of complex concepts in layman's terms.
• Participants were asked to state their preference between using a traditional search engine or an LLM for each scenario.
• This approach allowed for a nuanced understanding of how users perceive and utilize these two predominant digital tools in differing contexts.