Chatbots: a critical look into the future of the academia
Keywords:
ChatGPT, AI generative models, academia, ethical and moral restraintsAbstract
Like every other societal domain, science faces yet another reckoning caused by a bot called ChatGPT (Chat Generative Pre-Trained Transformer). ChatGPT was introduced in November 2022 to produce messages that seem like they were written by humans and are conversational. With the release of the latest version of ChatGPT called GPT-4, and other similar models such as Google Bard, Chatsonic, Collosal Chat, these chatbots combine several (about 175 billion) neural networks pre-trained on large Language Models (LLMs), allowing them to respond to user promptings just like humans. GPT-4 for example can admit its mistakes and confront false assumptions thanks to the dialogue style, which also enables it to write essays and to keep track of the context of a discussion while it is happening. However, users may be deceived by the human-like text structure of the AI models to believe that it came from a human origin[1]. These chatbot models could be better, even though they generate text with a high level of accuracy. Occasionally, they produce inappropriate or wrong responses, resulting in faulty inferences or ethical issues. This article will discuss some fundamental strengths and weaknesses of this Artificial intelligence (AI) system concerning scientific research. Keywords: ChatGPT, AI generative models, academia, ethical and moral restraints DOI: 10.25165/j.ijabe.20241702.9075 Citation: Okaiyeto S A, Mujumdar A S, Sutar P P, Liu W, Bai J W, Xiao H W. Chatbots: a critical look into the future of the academia. Int J Agric & Biol Eng, 2024; 17(2): 287–288.References
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[2] van Dis E A M, Bollen J, Zuidema W, van Rooij R, Bockting C L. ChatGPT: five priorities for research, Nature, 2023; 614(7947): 224-226. DOI: 10.1038/D41586-023-00288-7
[3] Buriak J M, Akinwande D, Artzi N, Brinker C J, Burrows C, Chan W C W, et al. Best practices for using ai when writing scientific manuscripts. ACS Nano, 2023; 17(5): 4091−4093. DOI: 10.1021/ACSNANO.3C01544
[4] Park M, Leahey E, Funk R J. Papers and patents are becoming less disruptive over time. Nature, 2023; 613: 138–144. doi: 10.1038/s41586-022-05543-x
[5] Karim R. ChatGPT: Old AI problems in a new guise, new problems in disguise. Monash University, 2023. Available at: https://lens.monash.edu/@politics-society/2023/02/13/1385448/chatgpt-old-ai-problems-in-a-new-guise-new-problems-in-disguise
[6] Stokel-Walker C, Noorden R V. The promise and peril of generative AI. Nature, 2023; 614: 214-216.
[7] Charo R A. Yellow lights for emerging technologies: All-or-none regulatory systems are not adequate for revolutionary innovations. Science, 2015; 349(6246): 384-385.
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Published
2024-05-21
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Okaiyeto, S. A., Mujumdar, A. S., Sutar, P. P., Liu, W., Bai, J., & Xiao, H. (2024). Chatbots: a critical look into the future of the academia. International Journal of Agricultural and Biological Engineering, 17(2), 287–288. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/9075
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