Clinicians and Scientists: Turn to AI, Not into AI

Abstract

Artificial intelligence (AI) is rapidly reshaping research across disciplines. In tasks as diverse as automating literature reviews and decoding complex datasets, AI has become central to modern inquiry. However, its rise has also prompted critical questions regarding human judgment, ethics, and dependence on machine outputs. Although AI increases efficiency, it cannot replace the creativity, intuition, and moral responsibility that underpin credible research. The challenge is therefore not to surrender human intellect to algorithms but to cultivate a partnership between them.

References

[1] Philip Chen CL, Zhang C-Y. Data-intensive applications, challenges, techniques and technologies: a survey on Big Data. Inf Sci 2014; 275: 314-47. [DOI: 10.1016/j.ins.2014.01.015]

[2] Li X, Guo Y. Paradigm shifts from data-intensive science to robot scientists. Sci Bull 2025; 70(1): 14-8. [PMID: 39389869 DOI: 10.1016/j.scib.2024.09.029]

[3] Ocana A, Pandiella A, Privat C, Bravo I, Luengo-Oroz M, et al. Integrating artificial intelligence in drug discovery and early drug development: a transformative approach. Biomark Res 2025; 13(1): 42. [PMID: 40087789 DOI: 10.1186/s40364-025-00758-2]

[4] Xu R, Sun Y, Ren M, Guo S, Pan R, et al. AI for social science and social science of AI: a survey. Inf Process Manag 2024; 61(3): 103665. [DOI: 10.1016/j.ipm.2024.103665]

[5] Alhur AA, Khlaif ZN, Hamamra B, Hussein E. Paradox of AI in higher education: qualitative inquiry into AI dependency among educators in Palestine. JMIR Med Educ 2025; 11: e74947. [PMID: 40953310 DOI: 10.2196/74947]

[6] Lin Z. Techniques for supercharging academic writing with generative AI. Nat Biomed Eng 2024; 9(4): 426-31. [PMID: 38499642 DOI: 10.1038/s41551-024-01185-8]

[7] von Eschenbach WJ. Transparency and the black box problem: why we do not trust AI. Philos Technol 2021; 34(4): 1607-22. [DOI: 10.1007/s13347-021-00477-0]

[8] Merhi MI. An evaluation of the critical success factors impacting artificial intelligence implementation. Int J Inf Manag 2023; 69: 102545. [DOI: 10.1016/j.ijinfomgt.2022.102545]

[9] Balasubramaniam N, Kauppinen M, Rannisto A, Hiekkanen K, Kujala S. Transparency and explainability of AI systems: from ethical guidelines to requirements. Inf Software Technol 2023; 159: 107197. [DOI: 10.1016/j.infsof.2023.107197]

[10] Nguyen KV. The use of generative AI tools in higher education: ethical and pedagogical principles. J Acad Ethics 2025; 23(3): 1435-55. [DOI: 10.1007/s10805-025-09607-1]

[11] Stöhr C, Ou AW, Malmström H. Perceptions and usage of AI chatbots among students in higher education across genders, academic levels and fields of study. Comput Educ Artif Intell 2024; 7: 100259. [DOI: 10.1016/j.caeai.2024.100259]

[12] Balalle H, Pannilage S. Reassessing academic integrity in the age of AI: a systematic literature review on AI and academic integrity. Soc Sci Humanit Open 2025; 11: 101299. [DOI: 10.1016/j.ssaho.2025.101299]

[13] Dabis A, Csáki C. AI and ethics: investigating the first policy responses of higher education institutions to the challenge of generative AI. Humanit Soc Sci Commun 2024; 11(1): 1006. [DOI: 10.1057/s41599-024-03526-z]

[14] Funa AA, Gabay RAE. Policy guidelines and recommendations on AI use in teaching and learning: a meta-synthesis study. Soc Sci Humanit Open 2025; 11: 101221.

[15] Lin Z. Towards an AI policy framework in scholarly publishing. Trends Cogn Sci 2024; 28(2): 85-8. [PMID: 38195365 DOI: 10.1016/j.tics.2023.12.002]

[16] Moorhouse BL, Yeo MA, Wan Y. Generative AI tools and assessment: guidelines of the world’s top-ranking universities. Comput Educ Open 2023; 5: 100151. [DOI: 10.1016/j.caeo.2023.100151]

[17] Xu Y, Liu X, Cao X, Huang C, Liu E, et al. Artificial intelligence: a powerful paradigm for scientific research. Innovation 2021; 2(4): 100179. [DOI: 10.1016/j.xinn.2021.100179]

[18] Lockhart ENS. Creativity in the age of AI: the human condition and the limits of machine generation. J Cult Cogn Sci 2024; 9(1): 83-8. [DOI: 10.1007/s41809-024-00158-2]

[19] Velagaleti S, Choukaier D, Nuthakki R, Lamba V, Sharma V, et al. Empathetic algorithms: the role of AI in understanding and enhancing human emotional intelligence. J Electr Syst 2024; 20(3s): 2051-60. [DOI: 10.52783/jes.1806]

[20] Runco MA. AI can only produce artificial creativity. J Creativity 2023; 33(3): 100063. [DOI: 10.1016/j.yjoc.2023.100063]

[21] Jiang T, Sun Z, Fu S, Lv Y. Human-AI interaction research agenda: a user-centered perspective. Data Inf Manag 2024; 8(4): 100078. [DOI: 10.1016/j.dim.2024.100078]

[22] Zong Z, Guan Y. AI-driven intelligent data analytics and predictive analysis in industry 4.0: transforming knowledge, innovation, and efficiency. J Knowl Econ 2024; 16(1): 864-903. [DOI: 10.1007/s13132-024-02001-z]

[23] Bzdok D, Nichols TE, Smith SM. Towards algorithmic analytics for large-scale datasets. Nat Mach Intell 2019; 1(7): 296-306. [DOI: 10.1038/s42256-019-0069-5]

[24] Akinnagbe OB. Human-AI collaboration: enhancing productivity and decision-making. Int J Educ Manag Technol 2024; 2(3): 387-417. [DOI: 10.58578/ijemt.v2i3.4209]

[25] Ting CK . Driving AI innovation through computational intelligence [Editor’s remarks]. IEEE Comput Intell Mag 2025; 20(1): 2-3. [DOI: 10.1109/MCI.2024.3504892]

[26] Zhai C, Wibowo S, Li LD. The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: a systematic review. Smart Learn Environ 2024; 11(1): 28. [DOI: 10.1186/s40561-024-00316-7]

[27] Hanna MG, Pantanowitz L, Jackson B, Palmer O, Visweswaran S, Pantanowitz J, et al. Ethical and bias considerations in artificial intelligence/machine learning. Mod Pathol 2025; 38(3): 100686. [PMID: 39694331 DOI: 10.1016/j.modpat.2024.100686]

[28] Wei X, Kumar N, Zhang H. Addressing bias in generative AI: challenges and research opportunities in information management. Inf Manag 2025; 62(2): 104103. [DOI: 10.1016/j.im.2025.104103]

[29] Paul J. Privacy and data security concerns in AI. 2024.

[30] Elali FR, Rachid LN. AI-generated research paper fabrication and plagiarism in the scientific community. Patterns 2023; 4(3): 100706. [DOI: 10.1016/j.patter.2023.100706]