Generative AI and ChatGPT: applications, challenges, and AI-human collaboration
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Artificial intelligence (AI) has elicited much attention across disciplines and industries (Hyder et al., Citation2019). AI has been defined as “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation” (Kaplan & Haenlein, Citation2019, p. 15). AI has gone through several development stages and AI winters. In the first two decades (i.e., 1950s and 1960s), AI demonstrated success which included programs such as General Problem Solver (Newell et al., Citation1959) and ELIZA (Weizenbaum, Citation1966). However, limitations in processing capacity and reduced spending on AI turned its development into stagnation. In recent years, AI has made a comeback with the introduction of AlphaGo in 2015 and ChatGPT in 2022. Following the release of the application named “Chat Generative Pre-trained Transformer” or ChatGPT by OpenAI in late 2022, AI has attracted worldwide attention.
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Generative adversarial networks
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2020) · Communications of the ACM · doi:10.1145/3422622 · Cited by 18,384 · see citing works
A fast learning algorithm for deep belief nets
Hinton, G. E., Osindero, S., & Teh, Y.-W. (2006) · Neural Computation · doi:10.1162/neco.2006.18.7.1527 · Cited by 16,336 · see citing works
Advances in Neural Information Processing Systems 29
Teymur, O., Zygalakis, K., & Calderhead, B. (2016) · Cited by 13,881 · see citing works
Rudin, C. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0048-x · Cited by 10,561 · see citing works
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326 · see citing works
Survey of Hallucination in Natural Language Generation
Ji, Z., Lee, N., Frieske, R., Yu, T., Su, D., Xu, Y., Ishii, E., Bang, Y. J., Madotto, A., & Fung, P. (2023) · ACM Computing Surveys · doi:10.1145/3571730 · Cited by 5,025 · see citing works
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., et al. (2023) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2023.102642 · Cited by 4,584 · see citing works
ELIZA—a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1966) · Communications of the ACM · doi:10.1145/365153.365168 · Cited by 4,452 · see citing works
Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., Maningo, J., et al. (2023) · PLOS Digital Health · doi:10.1371/journal.pdig.0000198 · Cited by 4,115 · see citing works
McClelland, J. L., Rumelhart, D. E., & AU (1987) · doi:10.7551/mitpress/5237.001.0001 · Cited by 3,315 · see citing works
What is AI Literacy? Competencies and Design Considerations
Long, D., & Magerko, B. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376727 · Cited by 3,241 · see citing works
How the machine “thinks”: Understanding opacity in machine learning algorithms
Burrell, J. (2016) · Big Data & Society · doi:10.1177/2053951715622512 · Cited by 3,196 · see citing works
Kaplan, A., & Haenlein, M. (2019) · Business Horizons · doi:10.1016/j.bushor.2018.08.004 · Cited by 3,140 · see citing works
Sallam, M. (2023) · Healthcare · doi:10.3390/healthcare11060887 · Cited by 3,126 · see citing works
Chatting and cheating: Ensuring academic integrity in the era of ChatGPT
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2190148 · Cited by 3,087 · see citing works
Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT
Cotton, D., Cotton, P., & Shipway, J. R. (2023) · doi:10.35542/osf.io/mrz8h · Cited by 3,079 · see citing works
Conceptualizing AI literacy: An exploratory review
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2021.100041 · Cited by 2,205 · see citing works
Digital divide research, achievements and shortcomings
van Dijk, J. A. G. M. (2006) · Poetics · doi:10.1016/j.poetic.2006.05.004 · Cited by 2,046 · see citing works
ChatGPT: five priorities for research
van Dis, E. A. M., Bollen, J., Zuidema, W., van Rooij, R., & Bockting, C. L. (2023) · Nature · doi:10.1038/d41586-023-00288-7 · Cited by 1,842 · see citing works
Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy
Shneiderman, B. (2020) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2020.1741118 · Cited by 1,743 · see citing works
Scheerder, A., van Deursen, A., & van Dijk, J. (2017) · Telematics and Informatics · doi:10.1016/j.tele.2017.07.007 · Cited by 1,471 · see citing works
ChatGPT is fun, but not an author
Thorp, H. H. (2023) · Science · doi:10.1126/science.adg7879 · Cited by 1,437 · see citing works
Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence
Cooper, G. (2023) · Journal of Science Education and Technology · doi:10.1007/s10956-023-10039-y · Cited by 1,263 · see citing works
Cascella, M., Montomoli, J., Bellini, V., & Bignami, E. (2023) · Journal of Medical Systems · doi:10.1007/s10916-023-01925-4 · Cited by 1,120 · see citing works
Bias in data‐driven artificial intelligence systems—An introductory survey
Ntoutsi, E., Fafalios, P., Gadiraju, U., Iosifidis, V., Nejdl, W., Vidal, M., Ruggieri, S., Turini, F., Papadopoulos, S., Krasanakis, E., et al. (2020) · WIREs Data Mining and Knowledge Discovery · doi:10.1002/widm.1356 · Cited by 1,043 · see citing works
Pavlik, J. V. (2023) · Journalism & Mass Communication Educator · doi:10.1177/10776958221149577 · Cited by 972 · see citing works
Synthetic data in machine learning for medicine and healthcare
Chen, R. J., Lu, M. Y., Chen, T. Y., Williamson, D. F. K., & Mahmood, F. (2021) · Nature Biomedical Engineering · doi:10.1038/s41551-021-00751-8 · Cited by 728 · see citing works
Recent Progress on Generative Adversarial Networks (GANs): A Survey
Pan, Z., Yu, W., Yi, X., Khan, A., Yuan, F., & Zheng, Y. (2019) · IEEE Access · doi:10.1109/access.2019.2905015 · Cited by 699 · see citing works
Role of Chat GPT in public health
Biswas, S. S. (2023) · Annals of Biomedical Engineering · doi:10.1007/s10439-023-03172-7 · Cited by 673 · see citing works
Design Guidelines for Prompt Engineering Text-to-Image Generative Models
Liu, V., & Chilton, L. B. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3501825 · Cited by 639 · see citing works
Governance of artificial intelligence
Taeihagh, A. (2021) · Policy and Society · doi:10.1080/14494035.2021.1928377 · Cited by 562 · see citing works
Artificial Intelligence (AI) Ethics: Ethics of AI and Ethical AI
Siau, K., & Wang, W. (2020) · Journal of Database Management · doi:10.4018/jdm.2020040105 · Cited by 533 · see citing works
Self-citationXu, W. M. (2019) · interactions · doi:10.1145/3328485 · Cited by 479 · see citing works
Ethical and social risks of harm from Language Models
Weidinger, L., Mellor, J., Rauh, M., Griffin, C., Uesato, J., Huang, P.-S., Cheng, M., Glaese, M., Balle, B., Kasirzadeh, A., et al. (2021) · arXiv · doi:10.48550/arxiv.2112.04359 · Cited by 477 · see citing works
Long-Term Trends in the Public Perception of Artificial Intelligence
Fast, E., & Horvitz, E. (2017) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v31i1.10635 · Cited by 467 · see citing works
Wang, W., & Siau, K. (2019) · Journal of Database Management · doi:10.4018/jdm.2019010104 · Cited by 452 · see citing works
Self-citationHuman-Centered Artificial Intelligence: Three Fresh Ideas
Shneiderman, B. (2020) · AIS Transactions on Human-Computer Interaction · doi:10.17705/1thci.00131 · Cited by 430 · see citing works
Köbis, N., & Mossink, L. D. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106553 · Cited by 406 · see citing works
Explanations as Mechanisms for Supporting Algorithmic Transparency
Rader, E., Cotter, K., & Cho, J. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173677 · Cited by 388 · see citing works
Defining organizational AI governance
Mäntymäki, M., Minkkinen, M., Birkstedt, T., & Viljanen, M. (2022) · AI and Ethics · doi:10.1007/s43681-022-00143-x · Cited by 378 · see citing works
ChatGPT: The End of Online Exam Integrity?
Susnjak, T. (2022) · arXiv · doi:10.48550/arxiv.2212.09292 · Cited by 370 · see citing works
Xu, W., Dainoff, M. J., Ge, L., & Gao, Z. (2023) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2022.2041900 · Cited by 363 · see citing works
Campbell, C., Plangger, K. A., Sands, S., & Kietzmann, J. (2021) · Journal of Advertising · doi:10.1080/00913367.2021.1909515 · Cited by 361 · see citing works
Human-Centered Artificial Intelligence and Machine Learning
Riedl, M. O. (2019) · Human Behavior and Emerging Technologies · doi:10.1002/hbe2.117 · Cited by 352 · see citing works
Large language models and the perils of their hallucinations
Azamfirei, R., Kudchadkar, S. R., & Fackler, J. C. (2023) · Critical Care · doi:10.1186/s13054-023-04393-x · Cited by 324 · see citing works
Will Humans-in-the-Loop Become Borgs? Merits and Pitfalls of Working with AI
Fügener, A., Grahl, J., Gupta, A., & Ketter, W. (2021) · MIS Quarterly · doi:10.25300/misq/2021/16553 · Cited by 322 · see citing works
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims
Brundage, M., Avin, S., Wang, J., Belfield, H., Krueger, G., Hadfield, G., Khlaaf, H., Yang, J., Toner, H., Fong, R., et al. (2020) · arXiv · doi:10.48550/arxiv.2004.07213 · Cited by 306 · see citing works
Susarla, A., Gopal, R. D., Thatcher, J. B., & Sarker, S. (2023) · Information Systems Research · doi:10.1287/isre.2023.ed.v34.n2 · Cited by 294 · see citing works
ChatGPT is not all you need. A state-of-the-art review of large generative AI models
Gozalo-Brizuela, R., & Garrido-Merchan, E. C. (2023) · arXiv · doi:10.48550/arxiv.2301.04655 · Cited by 245 · see citing works
Consumer Responses to AI-Generated Charitable Giving Ads
Arango, L., Singaraju, S. P., & Niininen, O. (2023) · Journal of Advertising · doi:10.1080/00913367.2023.2183285 · Cited by 243 · see citing works
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty
Bhatt, U., Antorán, J., Zhang, Y., Liao, Q. V., Sattigeri, P., Fogliato, R., Melançon, G., Krishnan, R., Stanley, J., Tickoo, O., et al. (2021) · Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society · doi:10.1145/3461702.3462571 · Cited by 225 · see citing works
Investigating Explainability of Generative AI for Code through Scenario-based Design
Sun, J., Liao, Q. V., Muller, M., Agarwal, M., Houde, S., Talamadupula, K., & Weisz, J. D. (2022) · 27th International Conference on Intelligent User Interfaces · doi:10.1145/3490099.3511119 · Cited by 219 · see citing works
Autonomy, Authenticity, Authorship and Intention in Computer Generated Art
McCormack, J., Gifford, T., & Hutchings, P. (2019) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-16667-0_3 · Cited by 218 · see citing works
Human-centered AI: The role of Human-centered Design Research in the development of AI
Auernhammer, J. M. K. (2020) · Proceedings of DRS · doi:10.21606/drs.2020.282 · Cited by 210 · see citing works
Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and Toxicity
Zhuo, T. Y., Huang, Y., Chen, C., & Xing, Z. (2023) · arXiv · doi:10.48550/arxiv.2301.12867 · Cited by 164 · see citing works
Carter, L. D., Liu, D., & Cantrell, C. (2020) · AIS Transactions on Human-Computer Interaction · doi:10.17705/1thci.00138 · Cited by 154 · see citing works
Assessing the regulatory challenges of emerging disruptive technologies
Taeihagh, A., Ramesh, M., & Howlett, M. (2021) · Regulation & Governance · doi:10.1111/rego.12392 · Cited by 133 · see citing works
Yang, Y., Siau, K. L., Xie, W., & Sun, Y. P. (2022) · Journal of Organizational and End User Computing · doi:10.4018/joeuc.308814 · Cited by 132 · see citing works
Self-citationArtificial Intelligence, Machine Learning, and Autonomous Technologies in Mining Industry
Hyder, Z., Siau, K. L., & Nah, F. F. (2019) · Journal of Database Management · doi:10.4018/jdm.2019040104 · Cited by 127 · see citing works
Self-citationExploring the future of nursing: Insights from the ChatGPT model
Gunawan, J. (2023) · Belitung Nursing Journal · doi:10.33546/bnj.2551 · Cited by 117 · see citing works
One-Shot Talking Face Generation from Single-Speaker Audio-Visual Correlation Learning
Wang, S., Li, L., Ding, Y., & Yu, X. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i3.20154 · Cited by 115 · see citing works
Intelligence Augmentation: Towards Building Human- machine Symbiotic Relationship
Zhou, L., Paul, S., Demirkan, H., Yuan, L., Spohrer, J., IBM, Zhou, M. X., Juji, Basu, J., & smartQED (2021) · AIS Transactions on Human-Computer Interaction · doi:10.17705/1thci.00149 · Cited by 111 · see citing works
Experiences in visual thinking
Lee, S.-A. (1982) · Design Studies · doi:10.1016/0142-694x(82)90080-1 · Cited by 110 · see citing works
Ozalp, H., Ozcan, P., Dinçkol, D., Zachariadis, M., & Gawer, A. (2022) · California Management Review · doi:10.1177/00081256221094307 · Cited by 107 · see citing works
A Survey of Big Data Security and Privacy Preserving
Fang, W., Wen, X. Z., Zheng, Y., & Zhou, M. L. (2016) · IETE Technical Review · doi:10.1080/02564602.2016.1215269 · Cited by 103 · see citing works
Economics of ChatGPT: A Labor Market View on the Occupational Impact of Artificial IntelligencePreprint
Zarifhonarvar, A. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4350925 · Cited by 99 · see citing works
“All around me are synthetic faces”: The mad world of AI-generated media
Whittaker, L., Kietzmann, T. C., Kietzmann, J., & Dabirian, A. (2020) · IT Professional · doi:10.1109/mitp.2020.2985492 · Cited by 90 · see citing works
Can ChatGPT Boost Artistic Creation: The Need of Imaginative Intelligence for Parallel Art
Guo, C., Lu, Y., Dou, Y., & Wang, F. (2023) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2023.123555 · Cited by 90 · see citing works
Awe‐inspiring advancements in AI: The impact of ChatGPT on the field of Organizational Behavior
Dasborough, M. T. (2023) · Journal of Organizational Behavior · doi:10.1002/job.2695 · Cited by 82 · see citing works
Intelligence Augmentation: Human Factors in AI and Future of Work
Paul, S., Yuan, L., Jain, H., Sporher, J., ISSIP.org, & Lifshitz-Assaf, H. (2022) · AIS Transactions on Human-Computer Interaction · doi:10.17705/1thci.00174 · Cited by 57 · see citing works
Boßelmann, C. M., Leu, C., & Lal, D. (2023) · Epilepsia · doi:10.1111/epi.17570 · Cited by 52 · see citing works
From principles to practices: the intertextual interaction between AI ethical and legal discourses
Cheng, L., & Liu, X. (2023) · International Journal of Legal Discourse · doi:10.1515/ijld-2023-2001 · Cited by 51 · see citing works
Cheap and Quick: Efficient Vision-Language Instruction Tuning for Large Language Models
Luo, G., Zhou, Y., Ren, T., Chen, S. L., Sun, X., & Ji, R. (2023) · neural information processing systems · doi:10.52202/075280-1288 · Cited by 50 · see citing works
Toward accountable human-centered AI: rationale and promising directions
Qadir, J., Islam, M., & Al-Fuqaha, A. I. (2022) · Journal of Information, Communication and Ethics in Society · doi:10.1108/jices-06-2021-0059 · Cited by 47 · see citing works
European Journal of Tourism Research
Barros, C. P. (2009) · European Journal of Tourism Research · doi:10.54055/ejtr.v2i1.24 · Cited by 47 · see citing works
Initial Images: Using Image Prompts to Improve Subject Representation in Multimodal AI Generated Art
Qiao, H., Liu, V., & Chilton, L. (2022) · Creativity and Cognition · doi:10.1145/3527927.3532792 · Cited by 46 · see citing works
Cheap and Quick: Efficient Vision-Language Instruction Tuning for Large Language ModelsPreprint
Luo, G., Zhou, Y., Ren, T., et al. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2305.15023 · Cited by 45 · see citing works
Detection of AI-Generated Synthetic Faces
Gragnaniello, D., Marra, F., & Verdoliva, L. (2022) · Advances in computer vision and pattern recognition · doi:10.1007/978-3-030-87664-7_9 · Cited by 38 · see citing works
Letiche, H., Loo, I. D., Cordery, C., & Moriceau, J. (2024) · Routledge eBooks · doi:10.4324/9781003371441 · Cited by 32 · see citing works
Creating AI Characters for Fighting Games Using Genetic Programming
Martínez-Arellano, G., Cant, R. J., & Woods, D. D. (2016) · IEEE Transactions on Computational Intelligence and AI in Games · doi:10.1109/tciaig.2016.2642158 · Cited by 30 · see citing works
Berechenbarkeit der Welt? Philosophie und Wissenschaft im Zeitalter von Big Data
Pietsch, W., Wernecke, J., & Ott, M. (2017) · Cited by 28 · see citing works
AI tools such as ChatGPT will disrupt hydrology, too
Halloran, L. J. S., Mhanna, S., & Brunner, P. (2023) · Hydrological Processes · doi:10.1002/hyp.14843 · Cited by 28 · see citing works
Reliability of AI-generated magnetograms from only EUV images
Liu, J., Wang, Y., Huang, X., Korsós, M. B., Jiang, Y., Wang, Y., & Erdélyi, R. (2021) · Nature Astronomy · doi:10.1038/s41550-021-01310-6 · Cited by 22 · see citing works
The University of North Carolina at Charlotte, Zhou, L., Rudin, C., Duke University, Gombolay, M., Georgia Institute of Technology, Spohrer, J., International Society of Service Innovation Professionals, Zhou, M., Juji, et al. (2023) · AIS Transactions on Human-Computer Interaction · doi:10.17705/1thci.00085 · Cited by 20 · see citing works
Compute to Tell the Tale: Goal-Driven Narrative Generation
Wong, Y., Fan, S., Guo, Y., Xu, Z., Stephen, K., Sheoran, R., Bhamidipati, A., Barsopia, V., Liu, J., & Kankanhalli, M. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3549202 · Cited by 16 · see citing works
ChatGPT and usurping academic authority
Gefen, D., & Arinze, O. B. (2023) · Journal of Information Technology Case and Application Research · doi:10.1080/15228053.2023.2186629 · Cited by 15 · see citing works
Automated Speech Generation from UN General Assembly Statements: Mapping Risks in AI Generated TextsPreprint
Aylett-Bullock, J., & Luengo-Oroz, M. A. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1906.01946 · Cited by 14 · see citing works
Legal and Regulatory Issues on Artificial Intelligence, Machine Learning, Data Science, and Big Data
Wan, W. Y., Tsimplis, M. N., Siau, K. L., Yue, W. T., Nah, F. F., & Yu, G. M. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-21707-4_40 · Cited by 10 · see citing works
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Flagged first, then by citations
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Sorted by citations
Zhai, C., Wibowo, S., & Li, L. D. (2024) · Smart Learning Environments · doi:10.1186/s40561-024-00316-7 · Cited by 1,567 · see citing works
Walter, Y. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00448-3 · Cited by 1,113 · see citing works
Generative AI in medical practice: in-depth exploration of privacy and security challenges
Chen, Y., & Esmaeilzadeh, P. (2024) · Journal of Medical Internet Research · doi:10.2196/53008 · Cited by 353 · see citing works
“The applications and challenges of generative AI in health care, including privacy issues and AI-human collaboration, are explored by Fui-Hoon et al [48].”
Generative AI Literacy: Twelve Defining Competencies
Annapureddy, R., Fornaroli, A., & Gatica-Perez, D. (2025) · Digital Government: Research and Practice · doi:10.1145/3685680 · Cited by 333 · see citing works
Amankwah-Amoah, J., Abdalla, S., Mogaji, E., Elbanna, A., & Dwivedi, Y. K. (2024) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2024.102759 · Cited by 305 · see citing works
Al Naqbi, H., Bahroun, Z., & Ahmed, V. (2024) · Sustainability · doi:10.3390/su16031166 · Cited by 302 · see citing works
Ferrara, E. (2024) · Journal of Computational Social Science · doi:10.1007/s42001-024-00250-1 · Cited by 296 · see citing works
Ruiz-Rojas, L. I., Salvador-Ullauri, L., & Acosta-Vargas, P. (2024) · Sustainability · doi:10.3390/su16135367 · Cited by 263 · see citing works
ChatGPT awareness, acceptance, and adoption in higher education: The role of trust as a cornerstone
Shahzad, M. F., Xu, S., & Javed, I. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00478-x · Cited by 274 · see citing works
Moorhouse, B. L., & Kohnke, L. (2024) · System · doi:10.1016/j.system.2024.103290 · Cited by 305 · see citing works
Kong, S. C., & Yang, Y. P. (2024) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2024.3392830 · Cited by 259 · see citing works
Shahzad, M. F., Xu, S., Lim, W. M., Yang, X., & Khan, Q. R. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e29523 · Cited by 205 · see citing works
Artificial Intelligence and the Transformation of Higher Education Institutions: A Systems Approach
Katsamakas, E., Pavlov, O. V., & Saklad, R. (2024) · Sustainability · doi:10.3390/su16146118 · Cited by 195 · see citing works
An expectancy value theory (EVT) based instrument for measuring student perceptions of generative AI
Chan, C. K. Y., & Zhou, W. (2023) · Smart Learning Environments · doi:10.1186/s40561-023-00284-4 · Cited by 192 · see citing works
Samala, A. D., Rawas, S., Wang, T., Reed, J. M., Kim, J., Howard, N.-J., & Ertz, M. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-12936-0 · Cited by 229 · see citing works
How organizations can innovate with generative AI
Holmström, J., & Carroll, N. (2024) · Business Horizons · doi:10.1016/j.bushor.2024.02.010 · Cited by 196 · see citing works
Ghimire, P., Kim, K., & Acharya, M. (2024) · Buildings · doi:10.3390/buildings14010220 · Cited by 175 · see citing works
Ghobakhloo, M., Fathi, M., Iranmanesh, M., Vilkas, M., Grybauskas, A., & Amran, A. (2024) · Journal of Manufacturing Technology Management · doi:10.1108/jmtm-12-2023-0530 · Cited by 168 · see citing works
Hao, X., Demir, E., & Eyers, D. R. (2024) · Technology in Society · doi:10.1016/j.techsoc.2024.102662 · Cited by 183 · see citing works
Gallent Torres, C., Zapata González, A., & Ortego Hernando, J. L. (2023) · RELIEVE - Revista Electrónica de Investigación y Evaluación Educativa · doi:10.30827/relieve.v29i2.29134 · Cited by 170 · see citing works
Generative Artificial Intelligence in Education: Advancing Adaptive and Personalized Learning
Guettala, M., Bourekkache, S., Kazar, O., & Harous, S. (2024) · Acta Informatica Pragensia · doi:10.18267/j.aip.235 · Cited by 190 · see citing works
Wang, Y., Wang, L., & Siau, K. L. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2316376 · Cited by 155 · see citing works
Self-citationGenerative artificial intelligence (GenAI) revolution: A deep dive into GenAI adoption
Kumar, A., Shankar, A., Hollebeek, L. D., Behl, A., & Lim, W. M. (2025) · Journal of Business Research · doi:10.1016/j.jbusres.2024.115160 · Cited by 169 · see citing works
Evaluating the impact of students' generative AI use in educational contexts
Wood, D., & Moss, S. (2024) · Journal of Research in Innovative Teaching & Learning · doi:10.1108/jrit-06-2024-0151 · Cited by 162 · see citing works
Storey, V. C., Yue, W. T., Zhao, J. L., & Lukyanenko, R. (2025) · Information Systems Frontiers · doi:10.1007/s10796-025-10581-7 · Cited by 176 · see citing works
Chuang, Y., Chiang, H.-L., & Lin, A.-P. (2025) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2025.102887 · Cited by 181 · see citing works
Yin, H., Zhang, Z., & Liu, Y. (2023) · Systems · doi:10.3390/systems11120566 · Cited by 131 · see citing works
Zheng, Y., Wang, Y.-B., Liu, K. S.-X., & Jiang, M. (2024) · Education and Information Technologies : Official Journal of the IFIP technical committee on Education · doi:10.1007/s10639-024-12763-3 · Cited by 133 · see citing works
Partarakis, N., & Zabulis, X. (2024) · Electronics · doi:10.3390/electronics13020269 · Cited by 154 · see citing works
Sai, S., Yashvardhan, U., Chamola, V., & Sikdar, B. (2024) · IEEE Access · doi:10.1109/access.2024.3385107 · Cited by 125 · see citing works
Almulla, M. A. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e32220 · Cited by 161 · see citing works
Long, S., Tan, J., Mao, B., Tang, F., Li, Y., Zhao, M., & Kato, N. (2025) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2025.3526606 · Cited by 127 · see citing works
Exploring the Role of Generative AI in Enhancing Language Learning: Opportunities and Challenges
Creely, E. (2024) · International Journal of Changes in Education · doi:10.47852/bonviewijce42022495 · Cited by 113 · see citing works
Enhancing active learning through collaboration between human teachers and generative AI
Pahi, K., Hawlader, S., Hicks, E., Zaman, A., & Phan, V. (2024) · Computers and Education Open · doi:10.1016/j.caeo.2024.100183 · Cited by 110 · see citing works
Lavidas, K., Voulgari, I., Papadakis, S., Athanassopoulos, S., Anastasiou, A., Filippidi, A., Komis, V., & Karacapilidis, N. I. (2024) · Information · doi:10.3390/info15060314 · Cited by 165 · see citing works
Integrating AI literacy into teacher education: a critical perspective paper
Daher, R. (2025) · Discover Artificial Intelligence · doi:10.1007/s44163-025-00475-7 · Cited by 106 · see citing works
ChatGPT: perspectives from human–computer interaction and psychology
Liu, J. (2024) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2024.1418869 · Cited by 99 · see citing works
Wijaya, T. T., Yu, Q., Cao, Y., He, Y., & Leung, F. K. S. (2024) · Behavioral Sciences · doi:10.3390/bs14111008 · Cited by 103 · see citing works
Bae, H., Hur, J., Park, J., Choi, G. W., & Moon, J. (2024) · Online Learning · doi:10.24059/olj.v28i3.4543 · Cited by 129 · see citing works
Bekele, H., & Raj, S. (2024) · Tourism Review · doi:10.1108/tr-07-2023-0509 · Cited by 98 · see citing works
Societal Impacts of Artificial Intelligence: Ethical, Legal, and Governance Issues
Qian, Y., Au, K.-S. L., & Nah, F. (2024) · Social impacts · doi:10.1016/j.socimp.2024.100040 · Cited by 82 · see citing works
Self-citationGenerative AI-enhanced human-AI collaborative conceptual design: A systematic literature review
Fang, C., Zhu, Y., Fang, L., Long, Y., Lin, H., Cong, Y., & Wang, S. J. (2025) · Design Studies · doi:10.1016/j.destud.2025.101300 · Cited by 107 · see citing works
Onatayo, D. A., Onososen, A. O., Oyediran, A. O., Oyediran, H., Arowoiya, V. A., & Onatayo, E. (2024) · Architecture · doi:10.3390/architecture4040046 · Cited by 119 · see citing works
Li, Y., & Lee, S. O. (2024) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-11-2023-1767 · Cited by 102 · see citing works
Wu, D., Zhang, S., Ma, Z., Yue, G. X.-G., & Dong, R. K. (2024) · Systems · doi:10.3390/systems12090332 · Cited by 127 · see citing works
Managing a ChatGPT-empowered workforce: Understanding its affordances and side effects
Retkowsky, J., Hafermalz, E., & Huysman, M. (2024) · Business Horizons · doi:10.1016/j.bushor.2024.04.009 · Cited by 90 · see citing works
Integrating Generative AI Into K-12 Curriculums and Pedagogies in India
Sharma, D. M., Ramana, K. V., Jothilakshmi, R., Verma, R., Maheswari, B. U., & Boopathi, S. (2023) · Advances in higher education and professional development book series · doi:10.4018/979-8-3693-0487-7.ch006 · Cited by 89 · see citing works
The mechanisms of AI hype and its planetary and social costs
Markelius, A., Wright, C., Kuiper, J., Delille, N., & Kuo, Y.-T. (2024) · AI and Ethics · doi:10.1007/s43681-024-00461-2 · Cited by 101 · see citing works
Jin, H. K., Lee, H. E., & Kim, E. (2024) · BMC Medical Education · doi:10.1186/s12909-024-05944-8 · Cited by 85 · see citing works
Revolutionizing Visuals: The Role of Generative AI in Modern Image Generation
Bansal, G., Nawal, A., Chamola, V., & Herencsar, N. (2024) · ACM Transactions on Multimedia Computing, Communications, and Applications · doi:10.1145/3689641 · Cited by 91 · see citing works
Co-creating with ChatGPT for tourism marketing materials
Zhang, Y., & Prebensen, N. K. (2024) · Annals of Tourism Research Empirical Insights · doi:10.1016/j.annale.2024.100124 · Cited by 103 · see citing works
Exploring the generative AI adoption in service industry: A mixed-method analysis
Gupta, R., & Rathore, B. (2024) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2024.103997 · Cited by 84 · see citing works
Fan, L., Deng, K., & Liu, F. (2025) · Scientific Reports · doi:10.1038/s41598-025-06930-w · Cited by 120 · see citing works
Balaskas, S., Tsiantos, V., Chatzifotiou, S., & Rigou, M. (2025) · Information · doi:10.3390/info16020082 · Cited by 81 · see citing works
Rethinking Plagiarism in the Era of Generative AI
Hutson, J. (2024) · Journal of Intelligent Communication · doi:10.54963/jic.v4i1.220 · Cited by 83 · see citing works
Enhancing academic integrity among students in GenAI Era:A holistic framework
Rasul, T., Nair, S., Kalendra, D., Balaji, M. S., Santini, F. D. O., Ladeira, W. J., Rather, R. A., Yasin, N., Rodriguez, R. V., Kokkalis, P., et al. (2024) · The International Journal of Management Education · doi:10.1016/j.ijme.2024.101041 · Cited by 82 · see citing works
A multifaceted vision of the human-AI collaboration: a comprehensive review
Puerta-Beldarrain, M., Gómez-Carmona, O., Sánchez-Corcuera, R., Casado-Mansilla, D., López-de-Ipiña, D., & Chen, L. (2025) · IEEE Access · doi:10.1109/access.2025.3536095 · Cited by 73 · see citing works
Self-citationUsing generative artificial intelligence (GenAI) in marketing: Development and practices
Chan, H., & Choi, T. (2025) · Journal of Business Research · doi:10.1016/j.jbusres.2025.115276 · Cited by 82 · see citing works
A comprehensive survey on integrating large language models with knowledge-based methods
Yang, W., Some, L., Bain, M., & Kang, B. H. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.113503 · Cited by 88 · see citing works
Pudasaini, S., Miralles-Pechuán, L., Lillis, D., & Llorens Salvador, M. (2025) · Journal of Academic Ethics · doi:10.1007/s10805-024-09576-x · Cited by 70 · see citing works
Opportunities and risks involved in using ChatGPT to create first grade science lesson plans
Powell, W. A., & Courchesne, S. (2024) · PLoS ONE · doi:10.1371/journal.pone.0305337 · Cited by 91 · see citing works
O’Dea, X., Tsz Kit Ng, D., O’Dea, M., & Shkuratskyy, V. (2026) · Policy Futures in Education · doi:10.1177/14782103241287401 · Cited by 69 · see citing works
(2023) · International Research Journal of Modernization in Engineering Technology and Science · doi:10.56726/irjmets45212 · Cited by 74 · see citing works
Ou, M., Zheng, H., Zeng, Y., & Hansen, P. (2024) · New Media & Society · doi:10.1177/14614448241293154 · Cited by 77 · see citing works
Generative AI in the Wild: Prospects, Challenges, and Strategies
Sun, Y., Jang, E., Ma, F., & Wang, T. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642160 · Cited by 64 · see citing works
Al-Busaidi, A. S., Raghu Raman, R., Hughes, L., Albashrawi, M. A., Malik, T., Dwivedi, Y. K., Alawi, T. A., Rizeiqi, M. A., Davies, G. H., Fenwick, M., et al. (2024) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2024.100630 · Cited by 85 · see citing works
Generative Artificial Intelligence and Language Teaching
Moorhouse, B. L., & Wong, K. M. (2025) · Cambridge University Press eBooks · doi:10.1017/9781009618823 · Cited by 80 · see citing works
Babaei, R., Cheng, S. S. M., Duan, R., & Zhao, S. (2025) · Journal of Sensor and Actuator Networks · doi:10.3390/jsan14010017 · Cited by 80 · see citing works
Traditional vs. AI-generated brand personalities: Impact on brand preference and purchase intention
Park, J., & Ahn, S. (2024) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2024.104009 · Cited by 65 · see citing works
Allison, J., Hwang, G., Mayer, R. E., Πέλλας, Ν., Karnalim, O., de Freitas, S., Ng, O., Huang, Y., Hooshyar, D., Seidman, R. H., et al. (2025) · Journal of Educational Computing Research · doi:10.1177/07356331251359964 · Cited by 71 · see citing works
Generative artificial intelligence and ELT
Moorhouse, B. L. (2024) · ELT Journal · doi:10.1093/elt/ccae032 · Cited by 57 · see citing works
Goktas, P. (2024) · Journal of Decision Systems · doi:10.1080/12460125.2024.2410042 · Cited by 56 · see citing works
Lan, G., Feng, X., Du, S., Song, F., & Xiao, Q. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13427-6 · Cited by 71 · see citing works
Bendoly, E., Chandrasekaran, A., Lima, M. D. R. F., Handfield, R., Khajavi, S. H., & Roscoe, S. (2023) · Decision Sciences · doi:10.1111/deci.12619 · Cited by 56 · see citing works
Chaka, C. (2024) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2024.7.1.14 · Cited by 56 · see citing works
Lye, C. Y., & Lim, L. (2024) · Education Sciences · doi:10.3390/educsci14060569 · Cited by 83 · see citing works
Guzman, A. L., & Lewis, S. C. (2024) · Emerging Media · doi:10.1177/27523543241289239 · Cited by 57 · see citing works
Emon, M. M. H., & Khan, T. (2025) · Review of Business and Economics Studies · doi:10.26794/2308-944x-2024-12-4-6-28 · Cited by 68 · see citing works
Generative AI, Why, How, and Outcomes: A User Adoption Study
Huy, L. V., Nguyen, T. H., Vo‐Thanh, T., Thịnh, N. H., & Dung, T. T. T. (2024) · AIS Transactions on Human-Computer Interaction · doi:10.17705/1thci.00198 · Cited by 54 · see citing works
Can generative AI reliably synthesise literature? exploring hallucination issues in ChatGPT
Adel, A., & Saleem, N. H. (2025) · AI & Society · doi:10.1007/s00146-025-02406-7 · Cited by 54 · see citing works
Artificial intelligence skills and their impact on the employability of university graduates
Ramos, H. C. P., Caro, O. C., Bardales, E. S., Huatangari, L. Q., Trigoso, J. A. C., Guevara, J. L. M., & Santos, R. C. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1629320 · Cited by 77 · see citing works
Rane, N. L. (2024) · International Journal of Artificial Intelligence and Machine Learning · doi:10.51483/ijaiml.4.1.2024.22-47 · Cited by 53 · see citing works
Wang, C., Li, S., Lin, N., Zhang, X., Han, Y., Wang, X., Liu, D., Tan, X., Pu, D., Li, K., et al. (2024) · Journal of Medical Internet Research · doi:10.2196/59435 · Cited by 53 · see citing works
Mapping Tomorrow’s Teaching and Learning Spaces: A Systematic Review on GenAI in Higher Education
Tillmanns, T., Filho, A. S., Rudra, S., Weber, P., Dawitz, J., Wiersma, E., Dudenaite, D., & REYNOLDS, S. L. (2025) · Trends in Higher Education · doi:10.3390/higheredu4010002 · Cited by 78 · see citing works
The impact of artificial intelligence on research efficiency
Madanchian, M., & Taherdoost, H. (2025) · Results in Engineering · doi:10.1016/j.rineng.2025.104743 · Cited by 79 · see citing works
Evolution of Learning: Assessing the Transformative Impact of Generative AI on Higher Education
Krause, S., Panchal, B. H., & Ubhe, N. (2025) · Frontiers of digital education. · doi:10.1007/s44366-025-0058-7 · Cited by 70 · see citing works
Yang, J., Wang, Y., Wang, X., Wang, X., Wang, X., & Wang, F. (2024) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2024.3349555 · Cited by 54 · see citing works
Large language models and generative AI in telehealth: a responsible use lens
Pool, J., Indulska, M., & Sadiq, S. W. (2024) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocae035 · Cited by 53 · see citing works
How could Generative AI support and add value to non-technology companies – A qualitative study
Modgil, S., Gupta, S., Kar, A. K., & Tuunanen, T. (2024) · Technovation · doi:10.1016/j.technovation.2024.103124 · Cited by 50 · see citing works
Wortel, C., Vanwesenbeeck, I., & Tomas, F. (2024) · Emerging Media · doi:10.1177/27523543241292096 · Cited by 50 · see citing works
Nia, M. F., Ahmadi, M., & Irankhah, E. (2025) · Frontiers in Dental Medicine · doi:10.3389/fdmed.2024.1456208 · Cited by 60 · see citing works
Generative AI in education: ChatGPT-4 in evaluating students’ written responses
Jauhiainen, J. S., & Guerra, A. G. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2024.2422337 · Cited by 63 · see citing works
Seven HCI Grand Challenges Revisited: Five-Year Progress
Stephanidis, C., Salvendy, G., Antona, M., Duffy, V. G., Gao, Q., Karwowski, W., Konomi, S., Nah, F. F., Ntoa, S., Rau, P. P., et al. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2450411 · Cited by 54 · see citing works
Self-citationGarg, A., Nisumba Soodhani, K., & Rajendran, R. (2025) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2025.100380 · Cited by 49 · see citing works
The Metaverse: Innovations and generative AI
Jauhiainen, J. S. (2024) · International Journal of Innovation Studies · doi:10.1016/j.ijis.2024.04.004 · Cited by 52 · see citing works
An Examination of Generative AI Response to Suicide Inquires: Content Analysis
Campbell, L. O., Babb, K., Lambie, G. W., & Hayes, B. (2025) · JMIR Mental Health · doi:10.2196/73623 · Cited by 48 · see citing works
Grand challenges in anticipating and responding to critical materials supply risks
Ku, A. Y., Alonso, E., Eggert, R. G., Graedel, T. E., Habib, K., Hool, A., Muta, T. O. R., Schrijvers, D., Espinoza, L. A. T., Vakhitova, T., et al. (2024) · Joule · doi:10.1016/j.joule.2024.03.001 · Cited by 47 · see citing works
Exploring the influence of ChatGPT on student academic success and career readiness
Dahri, N. A., Yahaya, N., & Al-Rahmi, W. M. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13148-2 · Cited by 63 · see citing works
Graphic Design Education in the Era of Text‐to‐Image Generation: Transitioning to Contents Creator
Hwang, Y., & Wu, Y. (2025) · International Journal of Art & Design Education · doi:10.1111/jade.12558 · Cited by 47 · see citing works
- Authors
- Fui-Hoon Nah, F., Zheng, R., Cai, J., Siau, K., & Chen, L.
- Affiliations
- City University of Hong Kong, Kowloon, Hong Kong SAR
- City University of Hong Kong (HK)
- Missouri University of Science and Technology (US)
- Venue
- Journal of Information Technology Case and Application Research
- Publisher
- Informa UK Limited
- Published
- 2023-07-03
- Volume
- 25
- Issue
- 3
- Pages
- 277-304
- ISSN
- 1522-8053 (ISSN-L)
- 2333-6897
- OpenAlex
- W4385071300
- Cited by
- 1,363
- References
- 86
- Citations by year
- 2026: 336 · 2025: 557 · 2024: 422 · 2023: 47 · 2022: 1
- FWCI
- 128.39
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Information Technology Case and Application Research (publishedVersion)
- Singapore Management University Institutional Knowledge (InK) (Singapore Management University) (submittedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- generative AI, ChatGPT, large language models, human-AI collaboration, history of artificial intelligence, AI winter, AlphaGo, artificial intelligence applications, AI challenges
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