Vyhledávání informací v době generativní umělé inteligence

With the growing popularity of conversational artificial intelligence systems, these tools are increasingly used as a source of information. This bachelor’s thesis focuses on comparing the reliability of provided information and the user effort required to obtain it when using selected AI systems in comparison with an internet search engine. The theoretical part describes the principles of how internet search engines operate and the challenges associated with online information retrieval. It further outlines the fundamentals of artificial intelligence, including its subfields, the principles of large language models, and the risks associated with generative AI. The practical part is based on testing ChatGPT, Google Gemini, Microsoft Copilot, and the Google search engine using a set of twenty queries divided into four categories: current information, factual queries, legislative queries, and consumer-related queries. The responses were subsequently evaluated in terms of accuracy and the effort required to obtain them. The results indicate that the Google search engine achieves higher reliability, which is associated with greater user effort. In contrast, artificial intelligence systems generally require less user effort, although their responses tend to be less reliable.