Search still matters: information retrieval in the era of generative AI

被引:5
|
作者
Hersh, William [1 ,2 ]
机构
[1] Oregon Hlth & Sci Univ, Sch Med, Dept Med Informat & Clin Epidemiol, Portland, OR 97239 USA
[2] Oregon Hlth & Sci Univ, Sch Med, Dept Med Informat & Clin Epidemiol, BICC, 3181 SW Sam Jackson Pk Rd, Portland, OR 97239 USA
关键词
information storage and retrieval; generative artificial intelligence; large language models; ChatGPT; QUALITY;
D O I
10.1093/jamia/ocae014
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Objective: Information retrieval (IR, also known as search) systems are ubiquitous in modern times. How does the emergence of generative artificial intelligence (AI), based on large language models (LLMs), fit into the IR process? Process: This perspective explores the use of generative AI in the context of the motivations, considerations, and outcomes of the IR process with a focus on the academic use of such systems. Conclusions: There are many information needs, from simple to complex, that motivate use of IR. Users of such systems, particularly academics, have concerns for authoritativeness, timeliness, and contextualization of search. While LLMs may provide functionality that aids the IR process, the continued need for search systems, and research into their improvement, remains essential.
引用
收藏
页数:3
相关论文
共 50 条
  • [1] Pathology in the era of generative AI
    不详
    LANCET DIGITAL HEALTH, 2024, 6 (08): : e536 - e536
  • [2] Pathology in the era of generative AI
    The Lancet Digital Health
    The Lancet Digital Health, 2024, 6 (08):
  • [3] Generative Information Retrieval
    Najork, Marc
    PROCEEDINGS OF THE 46TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, SIGIR 2023, 2023, : 1 - 1
  • [4] Computing Education in the Era of Generative AI
    Denny, Paul
    Prather, James
    Becker, Brett A.
    Finnie-Ansley, James
    Hellas, Arto
    Leinonen, Juho
    Luxton-Reilly, Andrew
    Reeves, Brent N.
    Santos, Eddie Antonio
    Sarsa, Sami
    COMMUNICATIONS OF THE ACM, 2024, 67 (02) : 56 - 67
  • [5] Social Risks in the Era of Generative AI
    Liu, Xiaozhong
    Lin, Yu-Ru
    Jiang, Zhuoren
    Wu, Qunfang
    Proceedings of the Association for Information Science and Technology, 2024, 61 (01) : 790 - 794
  • [6] AI and information retrieval
    Anick, P
    ARTIFICIAL INTELLIGENCE REVIEW, 1996, 10 (5-6) : 375 - 379
  • [7] Understanding user switch of information seeking: From search engines to generative AI
    Zhou, Tao
    Li, Songtao
    JOURNAL OF LIBRARIANSHIP AND INFORMATION SCIENCE, 2024,
  • [8] Generative AI Changes the Search Landscape
    Ojala, Marydee
    Computers in Libraries, 2023, 43 (04) : 42 - 44
  • [9] Genetic Generative Information Retrieval
    Kulkarni, Hrishikesh
    Young, Zachary
    Goharian, Nazli
    Frieder, Ophir
    MacAvaney, Sean
    PROCEEDINGS OF THE 2023 ACM SYMPOSIUM ON DOCUMENT ENGINEERING, DOCENG 2023, 2023,
  • [10] Exploring the mutations of society in the era of generative AI
    Hubert Etienne
    Brent Mittelstadt
    Rob Reich
    John Basl
    Jeff Behrends
    Dominique Lestel
    Chloé Bakalar
    Geoff Keeling
    Giada Pistilli
    Marta Cantero Gamito
    AI and Ethics, 2025, 5 (1): : 1 - 1