Investigating the Impacts of Generative AI on Information Seeking

This paper is an encore submission of our 2026 journal article “Expertise and Information Seeking in the Age of Generative AI: New Procedures, New Problematics” with an extended discussion for the CSCW 2026 “Broader Impacts of GenAI in Communication” Workshop on October 10, 2026. In the original article, we employ procedural rhetoric to analyze how generative AI chatbots leverage natural language signifiers of expertise and intelligence to influence users’ perception of their trustworthiness. In this submission, we extend our conversation in the CSCW community with the goal of cultivating a cross-disciplinary vocabulary for describing, analyzing, and mitigating the risks posed by the integration of generative AI into human communication practices. It is important to develop an understanding of how the procedures surrounding information-seeking practices are informed by users’ values, experiences, and expectations—and how these procedures might in future be altered by the emerging turn towards AI “experts” and authority.

Introduction. The process of gathering, evaluating, and applying new information is a shared human experience that goes back millennia. As information has been codified and collected in new ways (such as libraries, archives, websites, and databases), methods of information seeking have, accordingly, developed in tandem. Routine information seeking has historically involved the consultation of reputable sources, whether that be the local newspaper, a family doctor, or a trusted neighbor. While traditional forms of information seeking are now well understood, the advent of generative AI has introduced new complexities and considerations for information seeking in many different contexts. Indeed, for both scholars and the broader public, information seeking is being drastically reconfigured, in particular by the emergence of generative AI chatbots. Generative AI chatbots, built on language model (LM) architectures, have begun to fulfill a variety of roles [1] for human users, ranging from schedulers and virtual assistants to tutors, coaches, counsellors, and confidantes. Indeed, Hirvonen et al.

Discussion / Conclusion. When the key concepts above coalesce, they lead us to some challenging questions: What effect will the new AI-enabled procedures for information seeking have on users (and knowledge construction writ large)? What does it mean to trust a chatbot with information seeking, to imbue it with the authority to find, filter, and assemble information? What happens when decision-making is outsourced to a chatbot that cannot have true experience or direct knowledge in the world it claims to understand? These questions are a central stake in the future of information seeking and communication practices more broadly. The CSCW workshop [34] highlights relevant examples to consider here. Whether working in tandem with human expert consultation or independently, generative AI users are shifting away from the search-and-recall method wherein the onus is on the user to find, consume, and comprehend information of varying levels of difficulty, relevance, and reliability.