Assessing the Predictive Capabilities of Chatgpt and Generative Artificial Intelligence in Anticipating Realities and Events
DOI:
https://doi.org/10.69996/66212e29Keywords:
Generative Artificial Intelligence, Chatgpt, Predictive CapabilitiesAbstract
This review provides an overview of the inquiry into the predictive capacities of ChatGPT and generative artificial intelligence (AI) in forecasting forthcoming realities and events. The study examines the fundamental mechanisms of language models, scrutinizes their applications across diverse domains, evaluates ethical and accuracy considerations, and explores the potential and challenges of deploying ChatGPT and generative AI in predictive contexts. The outcomes underscore the significant promise of ChatGPT and generative AI for forecasting, contingent on factors such as data quality, training, and contextual relevance. This research advocates prudent and strategic utilization of ChatGPT and generative AI in prediction scenarios
References
[1] J.G. Borger, A.P. Ng, H. Anderton, G.W. Ashdown, M. Auld et al., “Artificial intelligence takes center stage: exploring the capabilities and implications of ChatGPT and other AI‐assisted technologies in scientific research and education,” Immunology and Cell Biology, 2023.
[2] A. Bozkurt, J. Xiao, S. Lambert, A. Pazurek, H. Crompton et al., “Speculative futures on ChatGPT and generative artificial intelligence (AI): A collective reflection from the educational landscape,” Asian Journal of Distance Education, vol.18, no.1, 2023.
[3] P. Budhwar, S. Chowdhury, G. Wood, H. Aguinis, G.J. Bamber et al., “Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT,” Human Resource Management Journal, vol.33, no.3, pp.606-659, 2023.
[4] Y. K. Dwivedi, N. Kshetri, L. Hughes, E.L. Slade, A. Jeyaraj et al., “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy,” International Journal of Information Management, vol.71, pp.102642, 2023.
[5] M.Gupta, C. Akiri, K. Aryal, E. Parker and L. Praharaj, “From ChatGPT to ThreatGPT: Impact of generative AI in cybersecurity and privacy,” IEEE Access, 2023.
[6] M. Javaid, A. Haleem and R.P. Singh, “ChatGPT for healthcare services: An emerging stage for an innovative perspective,” BenchCouncil Transactions on Benchmarks, Standards and Evaluations, vol.3, no.1, 100105, 2023.
[7] D.K. Kanbach, L. Heiduk, G. Blueher, M. Schreiter and A. Lahmann, “The GenAI is out of the bottle: generative artificial intelligence from a business model innovation perspective,” Review of Managerial Science, pp.1-32, 2023.
[8] S.I. Kehinde, C. Moses, T. Borishade, S.I. Busola, N. Adubor et al., “Evolution and innovation of hedge fund strategies: a systematic review of literature and framework for future research,” Acta Innovations, 2023.
[9] M. Khan and M.N. Chaudhry, “Artificial Intelligence and the Future of Impact Assessment,” Available at SSRN 4519498, 2023.
[10] J. Kocoń, I. Cichecki, O. Kaszyca, M. Kochanek, D. Szydło et al., “ChatGPT: Jack of all trades, master of none,” Information Fusion, no.101861, 2023.
[11] A. Korkmaz, C. Aktürk and T. Talan, “Analyzing the User's Sentiments of ChatGPT Using Twitter Data,” Iraqi Journal For Computer Science and Mathematics, vol.4, no.2, pp.202-214, 2023.
[12] W.M.Lim, A. Gunasekara, J.L. Pallant, J. I. Pallant and E. Pechenkina, “Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators,” The International Journal of Management Education, vol.21, no.2, pp.100790, 2023.
[13] J. Liu, C. Wang and S. Liu, “Utility of ChatGPT in clinical practice,” Journal of Medical Internet Research, vol.25, no.e48568, 2023.
[14] S. Mohamadi, G. Mujtaba, N. Le, G. Doretto and D.A. Adjeroh, “Chatgpt in the age of generative ai and large language models: A concise survey,” arXiv preprint arXiv:2307.04251, 2023.
[15] N.Y. Motlagh, M. Khajavi, A. Sharifi and M. Ahmadi, “The Impact of Artificial Intelligence on the Evolution of Digital Education: A Comparative Study of OpenAI Text Generation Tools including ChatGPT, Bing Chat, Bard, and Ernie,” arXiv preprint arXiv:2309.02029, 2023.
[16] S. Nikolic, S. Daniel, R. Haque, M. Belkina, G.M. Hassan et al., “ChatGPT versus engineering education assessment: a multidisciplinary and multi-institutional benchmarking and analysis of this generative artificial intelligence tool to investigate assessment integrity,” European Journal of Engineering Education, pp.1-56, 2023.
[17] M.S. Rahaman, M. T. Ahsan, N. Anjum, H.J.R. Terano and M.M. Rahman, “From ChatGPT-3 to GPT-4: a significant advancement in ai-driven NLP tools,” Journal of Engineering and Emerging Technologies, vol.2, no.1, pp.1-11, 2023.
[18] V. Ratten and P. Jones, “Generative artificial intelligence (ChatGPT): Implications for management educators,” The International Journal of Management Education, vol.21, no.3, pp.100857, 2023.
[19] C.K. Tiwari, M.A. Bhat, S.T. Khan, R. Subramaniam and M.A.I. Khan, “What drives students toward ChatGPT? An investigation of the factors influencing adoption and usage of ChatGPT,” Interactive Technology and Smart Education, 2023.
Published
Issue
Section
License
Copyright (c) 2025 Journal of Sensors, IoT & Health Sciences (JSIHS,ISSN: 2584-2560)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Fringe Global Scientific Press publishes all the papers under a Creative Commons Attribution-Non-Commercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/) license. Authors have the liberty to replicate and distribute their work. Authors have the ability to use either the whole or a portion of their piece in compilations or other publications that include their own work. Please see the licensing terms for more information on reusing the work.
