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This research systematically characterizes the evolving landscape of information seeking (IS) in the context of Generative AI, utilizing online crowdsourcing surveys, theoretical frameworks, and neurophysiological experiments. It highlights how modern IS processes have transformed due to new interfaces and complex interactions, revealing insights into user preferences and cognitive efforts involved in information retrieval. The findings underscore the need for personalized, cognition-aware IS systems that can adapt to these shifts in user behavior and expectations.
The rise of Generative AI has fundamentally altered how users seek information, revealing surprising shifts in interface preferences and cognitive engagement.
Information seeking (IS) evolves, as does the human IS process. Since the rise of Generative AI (GenAI), modern IS has shifted by introducing more interfaces, more complex interactions, and expanded system capabilities. We argue that these changes in modern IS should be systematically examined. This PhD research characterizes the changes in the modern IS process. We use mechanisms, including online crowdsourcing survey experiments, theoretical IS frameworks, and in-lab experiments with neurophysiological signals, to characterize the shifts in modern IS, especially those driven by GenAI. We offer insights into the current landscape of search interface preferences and the cognitive efforts involved in seeking information. We believe this PhD research will contribute to and inform future designs of personalized, cognition-aware IS systems.
