The internet search engine of the future will be powered by artificial intelligence. One can already choose from a host of AI-powered or AI-enhanced search engines—though their reliability often still leaves much to be desired. However, a team of computer scientists at the University of Massachusetts Amherst recently published and released a novel system for evaluating the reliability of AI-generated searches.
Called "eRAG," the method is a way of putting the AI and search engine in conversation with each other, then evaluating the quality of search engines for AI use. The work is published as part of the Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval.
"All of the search engines that we've always used were designed for humans," says Alireza Salemi, a graduate student in the Manning College of Information and Computer Sciences at UMass Amherst and the paper's lead author.
"They work pretty well when the user is a human, but the search engine of the future's main user will be one of the AI Large Language Models (LLMs), like ChatGPT. This means that we need to completely redesign the way that search engines work, and my research explores how LLMs and search engines can learn from each other."
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