The DOI matches its Crossref record; 90 of the 90 references it cites were found in a registry or an index.
Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration
Open accessAbstract
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.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The text we found for this paper looks like another document, so the self-check wasn’t run.
Citations
Cites
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
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
Advances in Neural Information Processing Systems 29
Teymur, O., Zygalakis, K., & Calderhead, B. (2016) · Cited by 13,881
Rudin, C. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0048-x · Cited by 10,561
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) · doi:10.35542/osf.io/5er8f · Cited by 7,552
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
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
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
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
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
Research works printed but not linked: 20
- Alkaissi H., 2023, Cureus, 15, 1
- Berg A., 2016, Finance & Development, 53, 10
- Bozkurt A., 2023, Asian Journal of Distance Education, 18, 1
- Bridy A., 2012, Stanford Technology Law Review, 5, 1
- Chan G. K., 2022, AI & Society, 1
- Deeks A., 2019, Columbia Law Review, 119, 1829
- Firat M., 2023, OSF Preprints, 1
- Flyverbom M., 2016, International Journal of Communication, 10, 110
- Gillotte J. L., 2019, UC Davis L Rev, 53, 2655
- Hu G., 2023, Accountability in Research, 1
- Kroll, J. A. (2015). Accountable Algorithms (Doctoral dissertation, Princeton University).
- Monarch R., 2021, Human-in-the-loop machine learning
- Murray M. D., 2023, Hastings Communications & Entertainment Law Journal, 45, 27
- Newell A., 1959, Proceedings of the International Conference on Information Processing, 256
- Ray S., 2023, Forbes
- Salakhutdinov R., 2010, Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 693
- Shubhendu S., 2013, International Journal of Scientific Engineering and Research, 1, 28
- Siau K., 2018, The Global Analyst, 7, 22
- Smolensky P., 1986, Parallel distributed processing, 194
- Su J., 2023, ECNU Review of Education, 1
Cited by
Sorted by citations
Items 401–500 of 1,004
Chen, Z., Sarkis, J., & Yıldızbaşı, A. (2025) · IEEE Engineering Management Review · doi:10.1109/emr.2025.3541542 · Cited by 9
How Does Generative AI Relate to Leisure Satisfaction and Awareness?
Li, Y., Ren, L., Zhang, H. Q., & Liu, H. (2025) · Leisure Sciences · doi:10.1080/01490400.2025.2467966 · Cited by 10
Application of GenAI in Clinical Administration Support
Taheri, A., Farhadi, A., & Zamanifar, A. (2025) · Springer eBooks · doi:10.1007/978-3-031-82963-5_4 · Cited by 11
Exploring University Staff’s Perceptions of Using Generative Artificial Intelligence at University
Whitbread, M., Hayes, C., Prabhakar, S., & Upsher, R. J. (2025) · Education Sciences · doi:10.3390/educsci15030367 · Cited by 9
Generative Artificial Intelligence in Education: Insights from Rehabilitation Sciences Students
Dekerlegand, R. L., Bell, A., Clancy, M. J., Pletcher, E. R., & Pollen, T. R. (2025) · Education Sciences · doi:10.3390/educsci15030380 · Cited by 9
Luo, G., Niu, C., Lu, L., Ling, W., & Huang, L. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13527-3 · Cited by 14
Lim, J. S., Lee, C., Shin, D., Kim, J., & Zhang, J. (2025) · Journal of Public Relations Research · doi:10.1080/1062726x.2025.2501552 · Cited by 13
Toward Generative AI–Driven Metadata Modeling: A Human–Large Language Model Collaborative Approach
Bagchi, M. (2025) · Library trends · doi:10.1353/lib.2025.a961196 · Cited by 22
Wu, G., He, Y., Cao, X., & Yuen, C. (2025) · IEEE Internet of Things Journal · doi:10.1109/jiot.2025.3579940 · Cited by 10
Web 3.0: A Survey on the Architectures, Enabling Technologies, Applications, and Challenges
Cao, B., Xiao, S., Shi, L. X., Wang, T., Chen, J., Wang, J., Ling, X., Xu, H., Zhang, S., & Liu, E. (2025) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2025.3589692 · Cited by 11
Bordas, A., Masson, P. L., & Weil, B. (2025) · Creativity and Innovation Management · doi:10.1111/caim.70013 · Cited by 10
Ratnam, K. K. Y. (2025) · Digital Health · doi:10.1177/20552076251362070 · Cited by 16
Canbeldek, M., Erol, A., Erol, M., & Budak, K. S. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2619035 · Cited by 12
Hodzic, S., Stević, A., & Matthes, J. (2026) · Technology in Society · doi:10.1016/j.techsoc.2026.103331 · Cited by 9
Hybrid work – a reconceptualisation and research agenda
Richter, A., & Richter, S. (2024) · i-com · doi:10.1515/icom-2023-0027 · Cited by 14
A MISLEADING GALLERY OF FLUID MOTION BY GENERATIVE ARTIFICIAL INTELLIGENCE
Kashefi, A. (2024) · Journal of Machine Learning for Modeling and Computing · doi:10.1615/jmachlearnmodelcomput.2024054191 · Cited by 10
Report on Artificial Intelligence and Blockchain ConvergencesPreprint
de la Roche, M., Voloder, E., Banerjee, A., Guerra, C., Dell'Accio, D. C., Budris, F., Arantes, G. M., Khattak, J., Wu, K.-T., Kajtazi, L., et al. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5023415 · Cited by 9
Lampropoulos, G., López-Belmonte, J., Pozo-Sánchez, S., & Marín-Marín, J.-A. (2026) · Advances in Computational Intelligence and Robotics · doi:10.4018/979-8-2600-0101-1.ch001 · Cited by 9
Generative Künstliche Intelligenz – die neue Ära der kreativen Maschinen
D’Onofrio, S. (2024) · HMD Praxis der Wirtschaftsinformatik · doi:10.1365/s40702-024-01069-0 · Cited by 9
GPT-VR Nexus: ChatGPT-Powered Immersive Virtual Reality Experience*
Chen, J., Lan, T., & Li, B. (2024) · IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) · doi:10.1109/vrw62533.2024.00383 · Cited by 8
Data Analytics with Large Language Models (LLM): A Novel Prompting Framework
Almheiri, S. M. A. A., Al-ansari, M., AlHashmi, J., Abdalmajeed, N., Jalil, M., & Ertek, G. (2024) · Lecture notes in operations research · doi:10.1007/978-3-031-61589-4_20 · Cited by 9
Heuser, M., & Vulpius, J. (2024) · Convergence The International Journal of Research into New Media Technologies · doi:10.1177/13548565241285742 · Cited by 8
Joshi, S. G., Tolloczko, C. H., Wenaas, S., Holm, O. J., & Langved, M. L. F. (2024) · Nordic Conference on Human-Computer Interaction · doi:10.1145/3679318.3685384 · Cited by 9
Chang, T., & Bau, D.-Y. (2025) · Library Hi Tech · doi:10.1108/lht-03-2024-0158 · Cited by 8
Yoon, S.-H., Yang, S.-B., & Lee, S.-H. (2025) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2025.101491 · Cited by 8
Large Language Models on Small Resource-Constrained Systems: Performance Analysis and Trade-Offs
Seymour, L., Kütükçü, B., & Baidya, S. (2025) · IEEE SoutheastCon · doi:10.1109/southeastcon56624.2025.10971638 · Cited by 11
Asad, M. M., & Ajaz, A. (2025) · The TQM Journal · doi:10.1108/tqm-09-2024-0357 · Cited by 14
Investigation Into the Identification of AI-Generated Short Dialectal Arabic Texts
Alharthi, H. (2025) · IEEE Access · doi:10.1109/access.2025.3568696 · Cited by 8
Incorporating ChatGPT into Hospitality and Tourism Education: A Comparative Student and AI Study
Xie, P. F. (2025) · Journal of Hospitality & Tourism Education · doi:10.1080/10963758.2025.2512430 · Cited by 9
Abels, C. M., Lopez-Lopez, E., Burton, J. W., Holford, D. L., Brinkmann, L. U. L., Herzog, S. M., & Lewandowsky, S. (2025) · Behavioral Science & Policy · doi:10.1177/23794607251347020 · Cited by 14
Lee, J. (2025) · Electronic Markets · doi:10.1007/s12525-025-00814-7 · Cited by 9
Tugarin, N., & van Husen, C. (2025) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2025.100357 · Cited by 11
The Role of ARCS Motivation in Predicting ChatGPT Adoption Based on UTAUT3 Framework
Parveen, K., Alghamdi, A. A., Samee, N. M. A., & Shafiq, M. (2025) · Journal of Educational Computing Research · doi:10.1177/07356331251362425 · Cited by 8
Zhang, F. (2025) · Online Information Review · doi:10.1108/oir-09-2024-0595 · Cited by 9
Gregg, K., Ryan, O., Katz, A., Huerta, M. V., & Sajadi, S. (2025) · Journal of Engineering Education · doi:10.1002/jee.70024 · Cited by 8
Exploring the Productivity of Generative AI-Powered Ad Campaigns: A Consumer Response Perspective
Yang, J. (2025) · Journal of Interactive Advertising · doi:10.1080/15252019.2025.2551598 · Cited by 12
Korayim, D., Bodhi, R., Alshaghdali, N. O., Galgotia, A., & Fierro, P. (2025) · Journal of Knowledge Management · doi:10.1108/jkm-03-2025-0365 · Cited by 10
LLM Hallucinations in Conversational AI for Customer Service: Framework and End-User Perceptions
Larsen, A. G., Skjuve, M. B., Følstad, A., & van As, N. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2580540 · Cited by 11
Gazit, T., Eitan, T., Gal, L., & Gradovitch, N. (2025) · Journal of Computer Assisted Learning · doi:10.1002/jcal.70162 · Cited by 10
Death of the Design Researcher? Creating Knowledge Resources for Designers Using Generative AI
van der Maden, W., van Beek, E., Halperin, B. A., Jääskeläinen, P., Kang, E., Kun, P., Lomas, D., Merritt, T. R., Lindley, J., Muller, M. J., et al. (2024) · Designing Interactive Systems Conference · doi:10.1145/3656156.3658398 · Cited by 9
Smart Media or Biased Media: The Impacts and Challenges of AI and Big Data on the Media Industry
Samuel-Okon, A. D. (2024) · Asian Journal of Research in Computer Science · doi:10.9734/ajrcos/2024/v17i7484 · Cited by 10
Public Service with Generative AI: Exploring Features and Applications
Aryfiyanto, H., & Alamsyah, A. (2024) · International Conference of Computer and Informatics Engineering (IC2IE) · doi:10.1109/ic2ie63342.2024.10747963 · Cited by 11
Application of ChatGPT for an English Learning Platform
Park, H.-Y. (2023) · STEM Journal · doi:10.16875/stem.2023.24.3.30 · Cited by 17
Onderi, H. N. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3373-0025-2.ch003 · Cited by 8
Razi, A., Bouzoubaa, L. A., Pessianzadeh, A., Seberger, J. S., & Rezapour, R. (2025) · Research Square · doi:10.21203/rs.3.rs-5686084/v1 · Cited by 14
Beyond Hallucination: Generative AI as a Catalyst for Human Creativity and Cognitive Evolution
Cai, W., & Gao, M. (2025) · ICCK Transactions on Emerging Topics in Artificial Intelligence · doi:10.62762/tetai.2025.657559 · Cited by 8
Yu, P., Lu, S., Long, Z., Chen, Y., Qian, J., & Shah, Z. A. (2023) · Advances in higher education and professional development book series · doi:10.4018/979-8-3693-0487-7.ch001 · Cited by 7
Zhang, X., Liu, Z., Cheng, Y., Wang, X., & Wang, Z. (2023) · IEEE ... International Conference on Data Mining workshops · doi:10.1109/icdmw60847.2023.00187 · Cited by 9
Generative AI and Price Discrimination in the Housing Market
Tanlamai, J., Khern-am-nuai, W., & Cohen, M. C. (2026) · Information Systems Research · doi:10.1287/isre.2024.1234 · Cited by 7
Artificial Intelligence, Finance, and Sustainability: An Overview
Sadati, A., Gramlich, D., & Walker, T. J. (2024) · Springer eBooks · doi:10.1007/978-3-031-66205-8_1 · Cited by 7
Mo, W., Singh, A., & Holloway, C. (2024) · International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) · doi:10.1145/3663548.3675609 · Cited by 8
Ruiz, P. G., & Domínguez-Lloria, S. (2024) · Arte individuo y sociedad · doi:10.5209/aris.99030 · Cited by 9
ChatGPT technology contribution in business innovation, policy and management
Alzoubi, Y. I., & Mishra, A. (2025) · Journal of Science and Technology Policy Management · doi:10.1108/jstpm-10-2023-0173 · Cited by 7
Company perspectives of generative artificial intelligence in industrial work
Aromaa, S., Heikkilä, P., Jurvansuu, M., Pehlivan, S., Väärä, T., & Jurmu, M. (2025) · Procedia Computer Science · doi:10.1016/j.procs.2025.01.085 · Cited by 8
Generative Artificial Intelligence-Guided User Studies: An Application for Air Taxi Services
Xiao, S.-D., Li, J., Fushimi, T., & Ochiai, Y. (2024) · Behaviour & Information Technology · doi:10.1080/0144929x.2025.2462265 · Cited by 6
Teaching Tip Incorporating AI Tools Into Database Classes
Zhang, X. (2025) · Journal of Information Systems Education · doi:10.62273/gkzi2477 · Cited by 9
The Rise of the Phygital Citizens
Kumari, P., Gupta, N., & Aeron, P. (2025) · Journal of Global Information Management · doi:10.4018/jgim.373320 · Cited by 8
Revisiting Technical Bias Mitigation Strategies
Mahamadou, A. J. D., & Trotsyuk, A. A. (2025) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-103123-095737 · Cited by 13
Schneider, S. M. (2025) · Social Epistemology · doi:10.1080/02691728.2025.2500030 · Cited by 11
Chandra, R., Chaudhari, A., & Rayavarapu, Y. (2025) · IEEE Access · doi:10.1109/access.2025.3585629 · Cited by 12
Barrot, J. S., & Aranda, M. R. R. (2025) · Technology Knowledge and Learning · doi:10.1007/s10758-025-09884-0 · Cited by 12
Zhang, Q., Li, L., Xu, C., Qi, Y., & Zhao, X. (2025) · The International Journal of Management Education · doi:10.1016/j.ijme.2025.101244 · Cited by 9
What Drives Patient Preferences for AI Chatbots Over Doctors? A Survey Study Using the O-S-O-R Model
Liu, Z., Zou, W., & Yang, S. (2025) · Health Communication · doi:10.1080/10410236.2025.2537814 · Cited by 10
Carvalho, I., Loureiro, S. M. C., Ivanov, S. H., Björk, P., & Seyitoğlu, F. (2025) · Journal of Hospitality and Tourism Insights · doi:10.1108/jhti-01-2025-0126 · Cited by 9
Artificial intelligence as a mentor in the graduate online classroom: opportunities and challenges
Kellam, H., Cortés, L. P., & Gilmore, T. (2025) · Artificial Intelligence in Education · doi:10.1108/aiie-10-2024-0034 · Cited by 9
Hadan, H., Mogavi, R. H., Zhang-Kennedy, L., & Nacke, L. E. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2549073 · Cited by 13
Chien, C. T., & Chien, C. H. (2025) · Applied Sciences · doi:10.3390/app151810123 · Cited by 7
WorkAI: A Toolkit for the Design of AI-driven Future of Work
Sadeghian, S., Bareikytė, M., Burkhardt, M., & Hassenzahl, M. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3757525 · Cited by 10
Assessing AI literacy of university students in Pakistan: a cross-sectional survey
Butt, F. S., Malik, A., & Mahmood, K. (2025) · Digital Library Perspectives · doi:10.1108/dlp-06-2025-0094 · Cited by 10
Qi, L., Cho, M., & Ko, E. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2560517 · Cited by 7
Albannai, N. A. A., Raziq, M. M., Bani-Melhem, S., & Moazzam, M. (2025) · Global Knowledge, Memory and Communication · doi:10.1108/gkmc-05-2025-0328 · Cited by 11
When AI takes the wheel: The effectiveness of AI versus human-generated content in tourism marketing
Li, C., Cao, Q., Hua, S., & Tao, C.-W. (2025) · Journal Of Vacation Marketing · doi:10.1177/13567667251393512 · Cited by 10
Wang, X., Zhong, W., Huang, K., & Liang, B. (2025) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2025.103009 · Cited by 13
Üretken Yapay Zekânın İşletmelerde Kullanımı: Fırsatlar ve Tehditler
Yastıoğlu, S. (2023) · Özgür Yayınları eBooks · doi:10.58830/ozgur.pub137.c1391 · Cited by 8
AI-Powered Code Review Assistant for Streamlining Pull Request Merging
Adapa, C., Avulamanda, S. S., Anjana, A., & Victor, A. C. (2024) · IEEE International Conference for Women in Innovation, Technology & Entrepreneurship (ICWITE) · doi:10.1109/icwite59797.2024.10503540 · Cited by 7
Loupasakis, M., Potamos, G., & Stavrou, E. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-61382-1_5 · Cited by 7
Zhang, Y., Zong, R., Shang, L., Yue, Z., Zeng, H., Liu, Y., & Wang, D. (2024) · ACM Collective Intelligence Conference (CI) · doi:10.1145/3643562.3672613 · Cited by 8
CEO AI orientation, human resources and green innovation: an attention-based view
Wang, X., & Wu, W. (2024) · Kybernetes · doi:10.1108/k-04-2024-0964 · Cited by 7
Donvir, A., Panyam, S., Paliwal, G., & Gujar, P. (2024) · International Conference on Engineering Management of Communication and Technology (EMCTECH) · doi:10.1109/emctech63049.2024.10741797 · Cited by 13
Bae, M.-J., Wang, J.-Y., Xue, H., Chong, S.-M., Kwon, O., & Ki, C. (2024) · International Journal of Fashion Design, Technology and Education · doi:10.1080/17543266.2024.2430585 · Cited by 8
Pandey, H. L., Bhusal, P. C., & Niraula, S. (2024) · Computers & composition/Computers and composition · doi:10.1016/j.compcom.2024.102892 · Cited by 12
Core competency framework and education plan for future talent in the era of generative AI
Choi, S. (2024) · The Journal of Korean Association of Computer Education · doi:10.32431/kace.2024.27.9.003 · Cited by 7
Shin, S., Sang, J., & Yoo, J. K. (2025) · Integrative Medicine Research · doi:10.1016/j.imr.2025.101216 · Cited by 7
A bibliometric analysis of literature published on ChatGPT and GPT
Safdar, M., Siddique, N., Gulzar, A., Adil, S. A., Yasin, H., & Khan, M. A. (2024) · Global Knowledge, Memory and Communication · doi:10.1108/gkmc-08-2023-0304 · Cited by 7
Raghu Raman, R., Nair, V. K., Dinesh, S., & Acharyulu, R. (2024) · Digital Government Research and Practice · doi:10.1145/3674846 · Cited by 7
Understanding the human element in scams: a multidisciplinary approach
Liu, X.-F., Ai, Y.-S., Jiang, L. C., Wang, X.-H., & Wu, Y. (2024) · Journal of IT Cases and Applications · doi:10.1080/15228053.2024.2439192 · Cited by 11
Blohm, I., Miranda, S., Ho, S. Y., & Leimeister, J. M. (2025) · Journal of Information Technology · doi:10.1177/02683962251340699 · Cited by 7
Lim, J. S., & Hong, N. (2025) · Health & New Media Research · doi:10.22720/hnmr.2025.00115 · Cited by 6
Li, X., & Awang, M. M. B. (2026) · European Journal of Education · doi:10.1111/ejed.70490 · Cited by 7
Digital technologies and human rights: challenges and opportunities
Stovpets, O. V., Borinshtein, Y., Yershova-Babenko, I. V., Козобродова, Д., Madi, H. I., & Honcharova, O. (2023) · Revista Amazonia Investiga · doi:10.34069/ai/2023.72.12.2 · Cited by 6
Crouzet, A., Lopez, N., Riss‐Yaw, B., Lepelletier, Y., & Demange, L. (2024) · Molecules · doi:10.3390/molecules29122716 · Cited by 6
Ethics and the use of generative AI in professional editing
Otmar, R., Michael, R., Mullins, S., & Day, K. (2024) · AI and Ethics · doi:10.1007/s43681-024-00521-7 · Cited by 6
Exploring ethical considerations in AI-driven cataloguing and classification with ChatGPT
Adewojo, A. A., & Amzat, O. B. (2024) · Business Information Review · doi:10.1177/02663821241264703 · Cited by 10
Lněnička, M., Rizun, N., Alexopoulos, C., & Saxena, S. (2024) · Journal of Science and Technology Policy Management · doi:10.1108/jstpm-11-2022-0196 · Cited by 6
The Effect of Prompt Types on Text Summarization Performance With Large Language Models
Borhan, I., & Bajaj, A. (2024) · Journal of Database Management · doi:10.4018/jdm.358475 · Cited by 7
Exploring Designer-Generative AI Collaborative Personas: A Case Study on ChatGPT
Huang, H. C., Lei, H., & Hsu, C.-C. (2024) · International Symposium on Visual Information Communication and Interaction (VINCI) · doi:10.1145/3678698.3687172 · Cited by 9
HFL-GAN: scalable hierarchical federated learning GAN for high quantity heterogeneous clients
Petch, L., Moustafa, A., Ma, X., & Yasser, M. (2024) · Applied Intelligence · doi:10.1007/s10489-024-05924-x · Cited by 7
Yao, L., Zhang, Q., & Deng, S. (2025) · Scientific Reports · doi:10.1038/s41598-025-98805-3 · Cited by 6
Artificial intelligence in media studies in Arab countries: a systematic review
Assad, A., Fyadh, M. A., Kaleel, A., & Gabr, M. (2025) · Discover Education · doi:10.1007/s44217-025-00520-8 · Cited by 6
Hidayatullah, H. I., Saifullah, M. T., Ghozali, M. T., & Aziz, A. (2025) · Neuroscience Informatics · doi:10.1016/j.neuri.2025.100213 · Cited by 9
Metadata
- 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
- 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
- Social Sciences › Business, Management and Accounting › Marketing › 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review