IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v19y2025i4s1751157725000896.html

Artificial intelligence in scientific research: Challenges, opportunities and the imperative of a human-centric synergy

Author

Listed:
  • Branda, Francesco
  • Ciccozzi, Massimo
  • Scarpa, Fabio

Abstract

This work offers a critical and evidence-based synthesis of the conceptual, methodological, and social implications of artificial intelligence (AI) in scientific research, significantly enriched by an informetric perspective. The analysis transcends descriptive overviews and simple cataloging of products, providing a deeper understanding of the opportunities AI presents, such as accelerated data analysis, hypothesis generation, and drug discovery. At the same time, crucial challenges that AI introduces are explored, including knowledge monocultures, algorithmic bias, reproducibility issues, and the impact on research integrity and evaluation. The original contribution of this paper lies in the integration of informetric analysis to quantify the influence of AI on the production and dissemination of scientific knowledge, highlighting both its potential as an analytical tool and the risk of bias in the academic record. The paper emphasizes the need for frameworks that harmonize technological capabilities with the irreplaceable ingenuity of human thought, promoting balanced collaboration between AI and researchers, where AI serves as a tool to increase productivity and human oversight ensures ethical rigor, critical evaluation, and creative exploration.

Suggested Citation

  • Branda, Francesco & Ciccozzi, Massimo & Scarpa, Fabio, 2025. "Artificial intelligence in scientific research: Challenges, opportunities and the imperative of a human-centric synergy," Journal of Informetrics, Elsevier, vol. 19(4).
    • Handle: RePEc:eee:infome:v:19:y:2025:i:4:s1751157725000896
    DOI: 10.1016/j.joi.2025.101727
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157725000896
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2025.101727?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Chitat Chan & Afifah Nurrosyidah, 2025. "Democratizing Artificial Intelligence for Social Good: A Bibliometric–Systematic Review Through a Social Science Lens," Social Sciences, MDPI, vol. 14(1), pages 1-27, January.
    2. Hanchen Wang & Tianfan Fu & Yuanqi Du & Wenhao Gao & Kexin Huang & Ziming Liu & Payal Chandak & Shengchao Liu & Peter Katwyk & Andreea Deac & Anima Anandkumar & Karianne Bergen & Carla P. Gomes & Shir, 2023. "Scientific discovery in the age of artificial intelligence," Nature, Nature, vol. 620(7972), pages 47-60, August.
    3. Hanchen Wang & Tianfan Fu & Yuanqi Du & Wenhao Gao & Kexin Huang & Ziming Liu & Payal Chandak & Shengchao Liu & Peter Katwyk & Andreea Deac & Anima Anandkumar & Karianne Bergen & Carla P. Gomes & Shir, 2023. "Publisher Correction: Scientific discovery in the age of artificial intelligence," Nature, Nature, vol. 621(7978), pages 33-33, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Evangelos Katsamakas & Oleg V. Pavlov & Ryan Saklad, 2024. "Artificial intelligence and the transformation of higher education institutions," Papers 2402.08143, arXiv.org.
    2. Francesco Venturini, 2025. "Generative AI and Income Growth: Early Evidence on Global Data," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 3, pages 31-46.
    3. Fabian Dvorak & Regina Stumpf & Sebastian Fehrler & Urs Fischbacher, 2024. "Generative AI Triggers Welfare-Reducing Decisions in Humans," Papers 2401.12773, arXiv.org.
    4. Kaishuai Liu & Shuai Liu, 2025. "Advances in Applied Mathematics in Computer Vision," Mathematics, MDPI, vol. 13(19), pages 1-5, September.
    5. Song Tong & Kai Mao & Zhen Huang & Yukun Zhao & Kaiping Peng, 2024. "Automating psychological hypothesis generation with AI: when large language models meet causal graph," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    6. Flavio Calvino & Luca Fontanelli, 2026. "Decoding AI: an early look at how French firms use AI," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 16(1), pages 51-93, March.
    7. Chen, Feng & Deng, Hongyu & Zhang, Xiaoying, 2024. "IG-ENT:A innovative ensemble approach for the flow prediction of main steam system in thermal power plant," Energy, Elsevier, vol. 313(C).
    8. Koehler, Maximilian & Sauermann, Henry, 2024. "Algorithmic management in scientific research," Research Policy, Elsevier, vol. 53(4).
    9. Jianfeng Yao & Cancong Zhao & Xuefan Hu & Yingshan Jin & Yanling Li & Liming Cai & Zhuofan Li & Fang Li & Fang Liang, 2025. "A Method for Estimating Tree Growth Potential with Back Propagation Neural Network," Sustainability, MDPI, vol. 17(4), pages 1-15, February.
    10. Fang Feng & Rongyan Zhu & Chunhui Wu & Jia Wei & Tinglan Huang & Mengmeng Wang, 2025. "Predicting Chinese Postgraduates’ Intention to Use Generative Artificial Intelligence in Academic Writing: A Sequential Exploratory Mixed-Method Study," SAGE Open, , vol. 15(4), pages 21582440251, December.
    11. Wu, Chuntao & Li, Haoran & Yuan, Bingbing, 2025. "AI-driven sustainable energy saving: Pathways for enhancing energy efficiency in Chinese listed firms," Applied Energy, Elsevier, vol. 401(PA).
    12. Siluo Yang & Longfei Li & Yujie Jin & Qian feng, 2025. "How does social media mention academic papers? Evidence from WeChat in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(8), pages 4621-4665, August.
    13. Yongyue Gong & Fengmei Ma & Heming Wang & Asaf Tzachor & Wenju Sun & Junming Zhu & Gang Liu & Heinz Schandl, 2025. "The evolution of research at the intersection of industrial ecology and artificial intelligence," Journal of Industrial Ecology, Yale University, vol. 29(2), pages 440-457, April.
    14. Giacomo Damioli & Vincent Van Roy & Daniel Vertesy & Marco Vivarelli, 2024. "AI as a new emerging technological paradigm: evidence from global patenting," DISCE - Working Papers del Dipartimento di Politica Economica dipe0038, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    15. Runhui Lin & Yalin Li & Wenchang Li & Ze Ji & Biting Li, 2025. "AI-enabled individual learning strategies and scientific innovation: a case from the field of computer science," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(7), pages 3651-3677, July.
    16. Alexander Braafladt & Alicia Sudol & Dimitri Mavris, 2026. "AI-driven adaptive analysis for finding emergent behavior in military capability design," The Journal of Defense Modeling and Simulation, , vol. 23(2), pages 255-270, April.
    17. Meng, Kai & Ba, Zhichao & Wang, Chunying & Li, Gang, 2025. "Unveiling intrinsic interactions of science and technology in artificial intelligence using a network portrait divergence approach," Journal of Informetrics, Elsevier, vol. 19(1).
    18. Anil R. Doshi & Oliver P. Hauser, 2023. "Generative artificial intelligence enhances creativity but reduces the diversity of novel content," Papers 2312.00506, arXiv.org, revised Mar 2024.
    19. Hui Li & Yichi Zhang & Zhaoxiong Wu & Zhe Wang & Tong Wu, 2025. "An Importance Sampling Method for Generating Optimal Interpolation Points in Training Physics-Informed Neural Networks," Mathematics, MDPI, vol. 13(1), pages 1-20, January.
    20. Naudé, Wim, 2024. "What They Don't Teach You about Artificial Intelligence at Business School: Stagnation, Oil, and War," IZA Discussion Papers 17306, IZA Network @ LISER.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:infome:v:19:y:2025:i:4:s1751157725000896. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.