Influence Analysis of Generative AI Usage Factors on Software Developers
Influence Analysis of Generative AI Usage Factors on Software Developers |
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© 2024 by IJETT Journal | ||
Volume-72 Issue-12 |
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Year of Publication : 2024 | ||
Author : Rizki Permana, Ahmad Nurul Fajar |
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DOI : 10.14445/22315381/IJETT-V72I12P117 |
How to Cite?
Rizki Permana, Ahmad Nurul Fajar, "Influence Analysis of Generative AI Usage Factors on Software Developers," International Journal of Engineering Trends and Technology, vol. 72, no. 12, pp. 183-195, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I12P117
Abstract
The growth of the Artificial Intelligence (AI) ecosystem has recently become increasingly crowded with the birth of generative AI technology, which has rapidly triggered changes in the way people communicate, create and do their daily work. Generative AI can help software development complete lines of code, write suggestions according to the correct writing structure, and even provide questions and answers according to the discussed context. However, according to McKinsey & Company in a survey in 2023, although the use of generative AI in the technology industry is relatively high compared to other industries, regular use for work needs is recorded at only 14% [1]. Despite many benefits and potential, generative AI has risks that are no less great, namely regarding security factors such as data bias, dependency and violations related to privacy data and leaks of company confidential information. So, how do software developers in Indonesia accept the presence of generative AI technology? This study involved respondents from various companies involved in the software development cycle and used the PLS-SEM model to investigate the Technology Acceptance Model (TAM). The results of SEM revealed that only a few variables had significant relationship direction, such as Intention to Use towards Actual System Usage, Perceived Ease of Use towards Perceived Usefulness, Perceived Security towards Intention to Use and Perceived Usefulness towards Intention to Use.
Keywords
Generative AI, GPT, Security, TAM, Software developer.
References
[1] Michael Chui et al., The State of AI in 2023: Generative AI’s Breakout Year, McKinsey and Company, 2023.
[Google Scholar] [Publisher Link]
[2] Philipp Hacker, Andreas Engel, and Marco Mauer, “Regulating ChatGPT and other Large Generative AI Models” Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, New York, United States, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Cindy Mutia Annur, “Survey: ChatGPT is the Most Used AI Application in Indonesia,” Media Network Catadata, 2023.
[Google Scholar] [Publisher Link]
[4] Ahmad Churi, Indonesian AI Technology Market Potential, Fourth Largest, It Works, 2024. [Online]. Available: https://www.itworks.id/67444/potensi-pasar-teknologi-ai-indonesia-terbesar-keempat.html
[5] Partha Pratim Ray, “Chatgpt: A Comprehensive Review on Background, Applications, Key Challenges, Bias, Ethics, Limitations and Future Scope,” Internet of Things and Cyber-Physical Systems, vol. 3, pp. 121-154, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Andreas Stavridis, and Axel Drugge, “The Rise of Intelligent System Development a Qualitative Study of Developers View on AI in Software Development Processes,” Student Thesis, Department of Informatics, 2023.
[Google Scholar] [Publisher Link]
[7] Adam Hörnemalm, “ChatGPT as a Software Development Tool the Future of Development,” Master Thesis, Department of Applied Physics and Electronics, Umeå University, 2023.
[Google Scholar] [Publisher Link]
[8] Ameya Shastri Pothukuchi, Lakshmi Vasuda Kota, and Vinay Mallikarjunaradhya, “Impact of Generative AI on the Software Development Life Cycle (SDLC),” International Journal of Creative Research Thoughts, vol. 11, no. 8, pp. b287-b291, 2023.
[Google Scholar] [Publisher Link]
[9] Emerson Murphy-Hill et al., “What Predicts Software Developers’ Productivity?” IEEE Transactions on Software Engineering, vol. 47, no. 3, pp. 582-594, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Fred D. Davis, “User Acceptance of Information Systems: The Technology Acceptance Model (TAM),” University of Michigan, School of Business Administration, Division of Research, no. 529, pp. 1-33, 1987.
[Google Scholar] [Publisher Link]
[11] Arief Wibowo, “Study of Information System User Behavior Using the Technology Acceptance Model (TAM) Approach,” Proceedings: National Conference on Information Systems, Yogyakarta, vol. 9, 2008.
[Google Scholar] [Publisher Link]
[12] Sukhpal Singh Gill et al., “Transformative effects of ChatGPT on modern education: Emerging Era of AI Chatbots,” Internet of Things and Cyber-Physical Systems, vol. 4, pp. 19-23, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Sukhpal Singh Gill, and Rupinder Kaur, “ChatGPT: Vision and Challenges,” Internet of Things and Cyber-Physical Systems, vol. 3, pp. 262-271, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Bernard Marr, “A Short History of ChatGPT: How We Got to Where We Are Today,” Forbes, 2023.
[Google Scholar] [Publisher Link]
[15] Nhan Nguyen, and Sarah Nadi, “An Empirical Evaluation of GitHub Copilot's Code Suggestions,” Proceedings of the 19th International Conference on Mining Software Repositories, New York, United States, pp. 1-5, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Shinta Nurul, Shynta Anggrainy, and Siska Aprelyani, “ Factors Affecting Information System Security: Information Security, Information Technology and Network (Literature Review Sim),” Economic Journal of Information Systems Management, vol. 3, no. 5, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Joe Hair et al., “An Updated and Expanded Assessment of PLS-SEM in Information Systems Research,” Industrial Management & Data Systems, vol. 117, no. 3, pp. 442-458, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Rizky Nur Cholifah, “Pengaruh Perceived Usefulness, Perceived Ease of Use Dan Trust Terhadap Intention to Use,” Bachelor's Thesis, Faculty of economics and business, UIN Jakarta, 2020.
[Google Scholar] [Publisher Link]
[19] Stefan Wagner, and Melanie Ruhe, “A Systematic Review of Productivity Factors in Software Development,” Arxiv Preprint, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Afrizal Tahar et al., “Perceived Ease of Use, Perceived Usefulness, Perceived Security and Intention to Use E-Filing: The Role of Technology Readiness,” The Journal of Asian Finance, Economics and Business, vol. 7, no. 9, pp. 537-547, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Muthia Primayunita, Indonesian Programmer Salary 2023: Promising Career Opportunities, Dicoding Blog, 2023. [Online]. Available: https://www.dicoding.com/blog/gaji-programmer-indonesia-2023-peluang-karier-menjanjikan/
[22] Imam Ghozali, Structural Equation Modeling: Metode Alternatif Dengan Partial Least Square (PLS), Diponegoro University Publishing Agency, 2008.
[Google Scholar] [Publisher Link]
[23] Willy Abdillah, and Jogiyanto Hartono, “Partial Least Square (PLS) Alternatif Structural Equation Modeling (SEM) Dalam Penelitian Bisnis,” Yogyakarta: Andi Publishers, vol. 22, pp. 103-150, 2015.
[Google Scholar]
[24] M. Mehdi Kholoosi, M. Ali Babar, and Roland Croft, “A Qualitative Study on Using ChatGPT for Software Security: Perception vs. Practicality,” arXiv preprint, 2024.
[CrossRef] [Google Scholar] [Publisher Link]