CHATGPT USAGE: A LINGUIST’S PERSPECTIVE
Abstract
The article discusses a popular computer program that simulates human conversation: ChatGPT. Chatbots with integrated natural language processing (NLP) can appear to understand questions and respond in a manner that seems knowledgeable. Developed similarly to computer-assisted translation tools, the developers moved from rule-based architecture to AI-supported tools using NLP and machine learning (ML) to power seemingly more intelligent conversations (e.g. Apple’s Siri, Google Assistant, Samsung’s Bixby and Amazon’s Alexa). ChatGPT, according to the common wisdom, stands out from other virtual assistants and has the potential to improve the way we interact with technology. Based on several queries conducted with ChatGPT to test its usefulness, we give an analysis of the results, which is followed by a discussion of the pros and cons of its use, with an emphasis on its usage in the educational context, in which students and teachers should be aware of the possibilities and limitations of LLMs.
Keywords: AI; ChatGPT; DeepL; LLM; machine learning; machine translation; SDL Trados.
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References
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Coeckelbergh, M. (2020). AI ethics. Cambridge: MIT Press.
Denning, P. J., & Tedre, M. (2019). Computational thinking. Cambridge: MIT Press.
Doanh, D. C., Dufek, Z., Ejdys, J., Ginevičius, R., Korzyński, P., Mazurek, G., Paliszkiewicz, J., Wach, K., & Ziemba, E. (2023). Generative AI in the manufacturing process: Theoretical considerations. Engineering Management in Production and Services, 15(4), 76–89. https://doi.org/10.2478/emj-2023-0029
Dumrak, J., & Zarghami, S. A. (2023). The role of artificial intelligence in lean construction management. Engineering, Construction and Architectural Management. In print. https://doi.org/10.1108/ECAM-02-2022-0153
Efe, A. (2022). The impact of artificial intelligence on social problems and solutions: An analysis on the context of digital divide and exploitation. Yeni Medya, 2022(13), 247–264. https://doi.org/10.55609/yenimedya.1146586
Frankfurt, H. G. (2005). On bullshit. Princeton University Press.
Frankfurt, H. G. (2006). On truth. Princeton University Press.
Gao, Y., & Liu, H. (2023). Artificial intelligence-enabled personalization in interactive marketing: A customer journey perspective. Journal of Research in Interactive Marketing, 17(5), 663–680. https://doi.org/10.1108/JRIM-01-2022-0023
Gerbu, T. (2023). Stopping harmful AI systems. The World Ahead 2024. The Economist Press.
Jaiwant, S. V. (2023). The changing role of marketing: Industry 5.0 – The game changer. In A. Saini, & V. Garg (Eds.), Transformation for sustainable business and management practices: Exploring the spectrum of industry 5.0. (pp. 187–202). Emerald Publishing. https://doi.org/10.1108/978-1-80262-277-520231014
Janssen, M., Brous, P., Estevez, E., Barbosa, L. S., & Jankowski, T. (2020). Data governance: Organizing data for trustworthy artificial intelligence. Government Information Quarterly, 37(3), https://doi.org/10.1016/j.giq.2020.101493
Kaczmarek, A. (2023). ChatGPT: The revolutionary bullshit parrot. Retrieved December 29, 2023 from https://www.reasonfieldlab.com/post/chatgpt-the-revolutionary-bullshit-parrot
Karinshak, E., & Jin, Y. (2023). AI-driven disinformation: A framework for organizational preparation and response. Journal of Communication Management, 27(4), 539–562. https://doi.org/10.1108/JCOM-09-2022-0113
Kelleher, J. D. (2019). Deep learning. MIT Press.
Kumar, A., Krishnamoorthy, B., & Bhattacharyya, S. S. (2023). Machine learning and artificial intelligence-induced technostress in organizations: A study on automation-augmentation paradox with socio-technical systems as coping mechanisms. International Journal of Organizational Analysis. Ahead of print. https://doi.org/10.1108/IJOA-01-2023-3581
Liu, S., Wright, A. P., Patterson, B. L., Wanderer, J. P., Turer, R. W., Nelson, S. D., McCoy, A. B., Sittig D. F., & Wright A. Assessing the value of ChatGPT for clinical decision support optimization. medRxiv [Preprint]. 2023 Feb 23:2023.02.21.23286254. doi:10.1101/2023.02.21.23286254
Minsky, M. (1988). The society of mind. Simon & Schuster.
McKinsey (2023). The economic potential of generative AI: The next productivity frontier. Retrieved January 2, 2024 from https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier
Murdoch, S. (2007). IQ: A smart history of a failed idea. John Wiley & Sons, Inc.
Pagallo, U., Ciani Sciolla, J., & Durante, M. (2022). The environmental challenges of AI in EU law: Lessons learned from the Artificial Intelligence Act (AIA) with its drawbacks. Transforming Government: People, Process and Policy, 16(3), 359–376. https://doi.org/10.1108/TG-07-2021-0121
Peres, R., Schreier, M., Schweidel, D., & Sorescu, A. (2023). On ChatGPT and beyond: How generative artificial intelligence may affect research, teaching, and practice. International Journal of Research in Marketing, 40(2), 269–275 https://doi.org/10.1016/j.ijresmar.2023.03.001
Poibeau, T. (2017). Machine translation. MIT Press.
Rawashdeh, A. (2023). The consequences of artificial intelligence: An investigation into the impact of AI on job displacement in accounting. Journal of Science and Technology Policy Management. In print. https://doi.org/10.1108/JSTPM-02-2023-0030
Schweidel, D. A., Reisenbichler, M., Reutterer, T., & Zhang, K. (2023). Leveraging AI for content generation: A customer equity perspective. In K. Sudhir, & O. Toubia, (Eds.), Artificial intelligence in marketing (“Review of Marketing Research”, Vol. 20), (pp. 125–145). Emerald Publishing. https://doi.org/10.1108/S1548-643520230000020006
Scriven, M. (2023). AI goes to work. The World Ahead 2024. The Economist Press.
Shanbhogue, R. (2023). The adoption decision. The World Ahead 2024. The Economist Press.
Sieja, M., & Wach, K (2023). Revolutionary artificial intelligence or rogue technology? The promises and pitfalls of ChatGPT. International Entrepreneurship Review, 9(4), 101–115. https://doi.org/10.15678/IER.2023.0904.07
Sundaresan, S., & Zhang, Z. (2022). AI-enabled knowledge sharing and learning: Redesigning roles and processes. International Journal of Organizational Analysis, 30(4), 983–999. https://doi.org/10.1108/IJOA-12-2020-2558
Turing, A. (1950). Computing machinery and intelligence. Mind. 49, 433–460. https://doi.org/10.1093%2Fmind%2FLIX.236.433
Wamba-Taguimdje, S.-L., Fosso Wamba, S., Kala Kamdjoug, J. R., & Tchatchouang Wanko, C. E. (2020). Influence of artificial intelligence (AI) on firm performance: The business value of AI-based transformation projects. Business Process Management Journal, 26(7), 1893–1924. https://doi.org/10.1108/BPMJ-10-2019-0411
Zhang, F., Pan, Z., & Lu, Y. (2023). AIoT-enabled smart surveillance for personal data digitalization: Contextual personalization-privacy paradox in smart home. Information and Management, 60(2), 103736, https://doi.org/10.1016/j.im.2022.103736
Published
2024-08-24
How to Cite
Rižnar, I. (2024). CHATGPT USAGE: A LINGUIST’S PERSPECTIVE. PALIMPSEST / ПАЛИМПСЕСТ, 9(17), 191-200. Retrieved from https://js.ugd.edu.mk/index.php/PAL/article/view/6760
Section
МЕТОДИКА НА НАСТАВАТА / TEACHING METHODOLOGY
