研究生成式AI如何改变现代信息获取方式
Characterizing the Evolving Landscape of Modern Information Seeking
- 结合在线众包、实验与神经信号，分析信息获取行为变化
- 发现用户偏好更智能的交互界面，认知负担随系统复杂度上升
- 适合关注人机交互、认知计算与个性化搜索设计的研究者
信息寻求（IS）过程随技术演进而不断变化。生成式AI（GenAI）的兴起带来了更多交互界面、更复杂的交互方式以及更强的系统能力，推动现代信息寻求模式发生转变。本博士研究系统性地刻画了这一演变过程，采用在线众包调查实验、理论信息寻求框架以及包含神经生理信号的实验室实验等机制，重点分析由GenAI驱动的信息寻求行为变化。研究揭示了当前用户对搜索界面的偏好特征及信息获取中的认知努力水平。成果可为未来个性化、认知感知型信息系统的研发提供依据。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。