Sealed Knowledges: A Critical Approach to the Usage of LLMs as Search Engines

Abstract

This research examines the implications of the usage of large language models (LLMs) as search engines on knowledge. Drawing on feminist theories of knowledge, I argue that LLMs used to generate direct answers to search engine inquiries both rely on and reinforce a disembodied and non-situated view of knowledge. This, it is argued, can lead to a "sealing"of non-dominant knowledges. Through this sealing of knowledges, marginalized voices may be heard even less than before. Lastly, drawing on the works of feminist theorists such as Donna Haraway and Sara Ahmed, the research proposes that doubting the outputs of LLMs can function as a feminist intervention that resists the marginalization and sealing of certain knowledges and perspectives through the usage of LLMS as chatbots. This research as part of a wider discourse on the usage of LLMs as search engines is crucial considering the current trend of major search engine providers to integrate LLMs for the production of direct answers into their search engines. © 2023 Owner/Author.