|
|
The Influence of ChatGPT on Library & Information Services |
Zhang Zhixiong1,2,3(),Yu Gaihong1,Liu Yi1,Lin Xin1,2,Zhang Menting1,2,Qian Li1,2,3 |
1National Science Library, Chinese Academy of Sciences, Beijing 100190, China 2Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China 3Key Laboratory of New Publishing and Knowledge Services for Scholarly Journals, Beijing 100190, China |
|
|
Abstract [Objective] This paper aims to discuss the inspiration and influence of artificial intelligence (AI) technologies represented by ChatGPT on Literature & Information Service, and put forward suggestions for the Literature & Information Service field. [Methods] This paper explores the essence of the rapid breakthrough of AI technologies based on the evolution of AI, analyzes the impact on Literature & Information Service based on the technical capability of ChatGPT, and proposes suggestions for the development of the Literature & Information Service field to take full advantages and values of Literature & Information Service. [Results] Five insights from the rapid development of AI technology for Literature & Information Service are summarized. The impact of ChatGPT is elaborated on six aspects: data organization, knowledge service, information analysis, literature utilization, team construction and service priorities. Based on the characteristics of Literature & Information Service, nine suggestions are put forward. [Conclusions] The essence of the rapid breakthrough of AI technologies lies in the improvement of knowledge acquisition capability. Moreover, the success of ChatGPT proves that high-value corpus is the basis of all AI technologies. The Literature & Information Service field holds high-value data resources containing abundant human knowledge, which is of great importance and significance for AI technologies. ChatGPT focuses on content generation, while Literature & Information Service focuses on evidence-based work. Literature & Information Service should actively respond to and expand AI technologies to comply with the advancement of the era of AI and contribute the wisdom and solutions.
|
Received: 17 March 2023
Published: 13 April 2023
|
|
Fund:National Key R&D Program of China(2022YFF0711900);National Social Science Fund of China(21&ZD329) |
Corresponding Authors:
Zhang Zhixiong,ORCID:0000-0003-1596-7487, E-mail:zhangzhx@mail.las.ac.cn。
|
[1] |
OpenAI. ChatGPT: Optimizing Language Models for Dialogue[EB/OL]. [2022-11-30]. https://openai.com/blog/chatgpt/.
|
[2] |
Zhuo T Y, Huang Y, Chen C, et al. Exploring AI Ethics of ChatGPT: A Diagnostic Analysis[OL]. arXiv Preprint, arXiv:2301.12867.
|
[3] |
Tamkin A, Brundage M, Clark J, et al. Understanding the Capabilities, Limitations, and Societal Impact of Large Language Models[OL]. arXiv Preprint, arXiv:2102.02503.
|
[4] |
Gilson A, Safranek C, Huang T, et al. How Does ChatGPT Perform on the Medical Licensing Exams? The Implications of Large Language Models for Medical Education and Knowledge Assessment [OL]. medRxiv, DOI: https://doi.org/10.1101/2022.12.23.22283901.
doi: https://doi.org/10.1101/2022.12.23.22283901
|
[5] |
Kung T H, Cheatham M, Medinilla A, et al. Performance of ChatGPT on USMLE: Potential for AI-Assisted Medical Education Using Large Language Models[OL]. medRxiv, DOI: https://doi.org/10.1101/2022.12.19.22283643.
doi: https://doi.org/10.1101/2022.12.19.22283643
|
[6] |
张智雄, 钱力, 谢靖, 等. ChatGPT对科学研究和文献情报工作的影响[R]. 北京: 中国科学院文献情报中心, 国家科技文献图书中心, 2023.
|
[6] |
Zhang Zhixiong, Qian Li, Xie Jing, et al. The Impact of ChatGPT on Scientific Research and Library & Information Service[R]. Beijing: National Science Library, Chinese Academy of Sciences, National Science and Technology Digital Library, 2023.)
|
[7] |
James V. ChatGPT is 80% Effective at Identifying Alzheimer’s Disease, Study Shows[EB/OL]. [2022-12-27]. https://interestingengineering.com/innovation/chatgpts-ai-alzheimers-disease-diagnosis.
|
[8] |
Agbavor F, Liang H. Predicting Dementia from Spontaneous Speech Using Large Language Models[J]. PLOS Digital Health, 2022, 1(12): e0000168.
doi: 10.1371/journal.pdig.0000168
|
[9] |
James V. BuzzFeed Says It Will Use AI Tools from OpenAI to Personalize Its Content[EB/OL]. [2023-01-27]. https://www.theverge.com/2023/1/26/23572834/buzzfeed-using-ai-tools-personalize-generate-content-openai.
|
[10] |
Dominik S, Martin B, Carol H, et al. An Analysis of the Automatic Bug Fixing Performance of ChatGPT[OL]. arXiv Preprint, arXiv: 2301.08653.
|
[11] |
Miao F, Holmes W, Huang R, et al. AI and Education: A Guidance for Policymakers[M]. UNESCO Publishing, 2021.
|
[12] |
Goodfellow I, Bengio Y, Courville A. Deep Learning[M]. MIT Press, 2016.
|
[13] |
Elman J L. Finding Structure in Time[J]. Cognitive Science, 1990, 14(2):179-211.
doi: 10.1207/s15516709cog1402_1
|
[14] |
Hochreiter S, Schmidhuber J. Long Short-term Memory[J]. Neural Computation, 1997, 9(8): 1735-1780.
doi: 10.1162/neco.1997.9.8.1735
pmid: 9377276
|
[15] |
Radford A, Narasimhan K, Salimans T, et al. Improving Language Understanding by Generative Pre-training[EB/OL]. [2018-06-11]. .
|
[16] |
Brown T B, Mann B, Ryder N, et al. Language Models are Few-Shot Learners[OL]. arXiv Preprint, arXiv:2005.14165.
|
[17] |
OpenAI. Aligning Language Models to Follow Instructions[EB/OL]. [2022-01-27]. https://openai.com/blog/instruction-following/.
|
[18] |
Ouyang L, Wu J, Jiang X, et al. Training Language Models to Follow Instructions with Human Feedback[OL]. arXiv Preprint, arXiv:2203.02155.
|
[19] |
Kaplan J, McCandlish S, Henighan T, et al. Scaling Laws for Neural Language Models[OL]. arXiv Preprint, arXiv:2001.08361.
|
[20] |
Hoffmann J, Borgeaud S, Mensch A, et al. Training Compute-Optimal Large Language Models[OL]. arXiv Preprint, arXiv:2203.15556.
|
[21] |
Schulman J, Wolski F, Dhariwal P, et al. Proximal Policy Optimization Algorithms[OL]. arXiv Preprint, arXiv: 1707.06347.
|
[22] |
MIT Technology Review. Asia’s AI Agenda: AI and Human Capital[R]. Massachusetts: MIT Technology Review Insights, 2019.
|
[23] |
Gartner. Gartner Identifies the Top Strategic Technology Trends for 2022[EB/OL]. [2021-10-18]. https://www.gartner.com/en/newsroom/press-releases/2021-10-18-gartner-identifies-the-top-strategic-technology-trends-for-2022.
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|