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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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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 ›
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