When, What, and how should generative artificial intelligence explain to Users?

被引:0
|
作者
Jang, Soobin [1 ]
Lee, Haeyoon [2 ]
Kim, Yujin [3 ]
Lee, Daeho [1 ,2 ,3 ]
Shin, Jungwoo [4 ,5 ]
Nam, Jungwoo [6 ]
机构
[1] Sungkyunkwan Univ, Dept Appl Artificial Intelligence, Seoul, South Korea
[2] Sungkyunkwan Univ, Dept Interact Sci, Seoul, South Korea
[3] Sungkyunkwan Univ, Sch Convergence, Seoul, South Korea
[4] Kyung Hee Univ, Dept Ind & Management Syst Engn, Yongin, South Korea
[5] Kyung Hee Univ, Dept Big Data Analyt, Seoul, South Korea
[6] Sungkyunkwan Univ, Dept Human Artificial Intelligence Interact, Seoul, South Korea
基金
新加坡国家研究基金会;
关键词
Generative AI; Conversational user interface; Explainable AI; Conjoint analysis; SERVICES;
D O I
10.1016/j.tele.2024.102175
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
With the commercialization of ChatGPT, , generative artificial intelligence (AI) has been applied almost everywhere in our lives. However, even though generative AI has become a daily technology that anyone can use, most non-majors need to know the process and reason for the results because it can be misused due to lack of sufficient knowledge and misunderstanding. Therefore, this study investigated users' preferences for when, what, and how generative AI should provide explanations about the process of generating and the reasoning behind the results, using conjoint method and mixed logit analysis. The results show that users are most sensitive to the timing of providing eXplainable AI (XAI), and that users want additional information only when they ask for explanations during the process of using generative AI. The results of this study will help shape the XAI design of future generative AI from a user perspective and improve usability.
引用
收藏
页数:14
相关论文
共 50 条
  • [21] Towards Understanding the Interplay of Generative Artificial Intelligence and the Internet
    Martinez, Gonzalo
    Watson, Lauren
    Revirieg, Pedro
    Alberto Hernandez, Jose
    Juare, Marc
    Sarka, Rik
    EPISTEMIC UNCERTAINTY IN ARTIFICIAL INTELLIGENCE, EPI UAI 2023, 2024, 14523 : 59 - 73
  • [22] Generative artificial intelligence and the challenges to adding value ethically
    Wamba, Samuel Fosso
    Queiroz, Maciel M.
    Randhawa, Krithika
    Gupta, Gaurav
    TECHNOVATION, 2025, 144
  • [23] Comparing the Ideation Quality of Humans with Generative Artificial Intelligence
    Joosten J.
    Bilgram V.
    Hahn A.
    Totzek D.
    IEEE Engineering Management Review, 2024, 52 (02): : 153 - 164
  • [24] Ensuring useful adoption of generative artificial intelligence in healthcare
    Jindal, Jenelle A.
    Lungren, Matthew P.
    Shah, Nigam H.
    JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2024, 31 (06) : 1441 - 1444
  • [25] Generative Artificial Intelligence and Legal Decision-making
    Cardoso, Andre Guskow
    Chan, Elizabeth
    Quintao, Luisa
    Pereira, Cesar
    GLOBAL TRADE AND CUSTOMS JOURNAL, 2024, 19 (11-12): : 710 - 730
  • [26] A review of ophthalmology education in the era of generative artificial intelligence
    Heinke, Anna
    Radgoudarzi, Niloofar
    Huang, Bonnie B.
    Baxter, Sally L.
    ASIA-PACIFIC JOURNAL OF OPHTHALMOLOGY, 2024, 13 (04):
  • [27] Generative Artificial Intelligence: Current Trends, Issues, and Challenges
    Vyas, Piyush
    Vyas, Gitika
    IT PROFESSIONAL, 2025, 27 (01) : 20 - 26
  • [28] Social Dangers of Generative Artificial Intelligence: Review and Guidelines
    Yang, Alan T.
    Yang, Andrew T.
    PROCEEDINGS OF THE 25TH ANNUAL INTERNATIONAL CONFERENCE ON DIGITAL GOVERNMENT RESEARCH, DGO 2024, 2024, : 654 - 658
  • [29] Generative Artificial Intelligence for the Visualization of Source Code as Comics
    Heidrich, David
    Schreiber, Andreas
    Theis, Sabine
    HUMAN INTERFACE AND THE MANAGEMENT OF INFORMATION, PT II, HIMI 2024, 2024, 14690 : 35 - 49
  • [30] The Impact of Generative Artificial Intelligence on Education: A Comparative Study
    Elmourabit, Zohair
    Retbi, Asmaa
    El Faddouli, Nour-Eddine
    PROCEEDINGS OF THE 23RD EUROPEAN CONFERENCE ON E-LEARNING, ECEL 2024, 2024, 23/1 : 470 - 476