The Impact of Open-Source Software on Artificial Intelligence
DOI:
https://doi.org/10.46754/jmsi.2023.12.006Keywords:
Open-Source Software, Proprietary Software, Artificial Intelligence, AI Libraries and ToolsAbstract
Open-Source Software (OSS) can be defined as application or tools that is developed by its own community. The idea of OSS development comes from Richard Stallman where stands the freedom of using software for free. After successfully launched The GNU project, Richard Stallman established Free Software Foundation to fight the big technology companies from monopolize the tech-economy during that time. As results, many OSS (e.g., Apache, Linux OS, etc.) are developed and still being used till today. Nowadays, OSS covers many sectors such as software development, 3D rendering, mobile applications, Artificial Intelligence (AI) and many more. This paper will review the basic information of OSS along with its history, Advantages and disadvantages of OSS, the impact of OSS to the industries and AI as well as its challenges.
References
Ehioghae, E., & Idowu, S. (2021). Open-source software in emerging technologies for economic growth. ITEGAM- Journal of Engineering and Technology for Industrial Applications (ITEGAM-JETIA), 7(27), 63-69. https://doi.org/10.5935/jetia.v7i27.730
Höst, M., & Oručević-Alagić, A. (2011). A systematic review of research on open source software in commercial software product development. Information and Software Technology, 53(6), 616-624. https://doi.org/10.1016/j.infsof.2010.12.009
Xing, M. (2011). Open source software and R&D competition in software industries. Procedia Engineering, 15, 1377–1381. https://doi.org/10.1016/j.proeng.2011.08.255
Goedeken, E. A. (2015). History with an impact: The most cited articles in the journal of library history and its successors over the past fifty years. Information and Culture, 50(2), 285-314. University of Texas Press. http://doi.org/10.7560/IC50301
Kavanagh, P. (2004). I Open Source Software: Definitions and History [Online]. Available in http://www.gnu.org/
Dell’Era, C., Di Minin, A., Ferrigno, G., Frattini, F., Landoni, P., & Verganti, R. (2020). Value capture in open innovation processes with radical circles: A qualitative analysis of firms’ collaborations with Slow Food, Memphis, and Free Software Foundation. Technological
Forecasting and Social Change, 158, 120128. https://doi.org/10.1016/j.techfore.2020.120128
M. Gael Le, .“2.2 The GNU project,” 2005. Accessed: Dec. 13, 2023. [Online]. Available: https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=07d2e5208664d740ce649f29cf6ff68186e9a6f5[8] Williams, S. (2010). Free as in freedom (2.0): Richard Stallman and the free software revolution. Free Software Foundation.
Von Krogh, G., & Von Hippel, E. (2006). The promise of research on open source software. Management Science, 52(7), 975-983. https://doi.org/10.1287/mnsc.1060.0560
Nelson, M., Sen, R., & Subramaniam, C. (2006). Understanding open source software: A research classification framework. Communications of the Association for Information Systems, 17, 266-288. https://doi.org/10.17705/1CAIS.01712
Zhang, C., & Lu, Y. (2021). Study on artificial intelligence: The state of the art and future prospects. Journal of Industrial Information Integration, 23, 100224. https://doi.org/10.1016/j.jii.2021.100224
Nathan, T. S. S., Kavithambika, S., & Palanichamy, N. V. (2023). Artificial intelligence in agriculture. In An anthology of agricultural research (pp.126-134). https://www.researchgate.net/publication/368543766_Artificial_Intelligence_in_Agriculture
Ku Chhaya, K. A., & Sarode, R. D. (2020). Advantages and disadvantages of artificial intelligence and machine learning: A literature review. International Journal of Library & Information Science (IJLIS), 9(1), 30-36. https://iaeme.com/Home/issue/IJLIS?Volume=9&Issue=1
Bhattacharya, S., Czejdo, B., Agrawal, R., Erdemir, E., & Gokaraju, B. (2018). Open source platforms and frameworks for artificial intelligence and machine learning. Conference Proceedings - IEEE SoutheastCon, 2018, St. Petersburg, FL, USA (pp. 1-4). https://doi.
org/10.1109/SECON.2018.8479098
R. Ghioni, M. Taddeo, and L. Floridi, “Electronic copy available,” 2022. Accessed: Dec. 13, 2023. [Online]. Available: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4272245
Bahamdain, S. S. (2015). Open source software (OSS) quality assurance: A survey paper. Procedia Computer Science, 56, 459-464. Elsevier. https://doi.org/10.1016/j.procs.2015.07.236
Zhonghua, Q., & Brocklehurst, M. (2003). What will it take for China to become a competitive force in offshore outsourcing? An analysis of the role of transaction costs in supplier selection. Journal of Information Technology, 18(1), 53-67. https://doi.org/10.1080/0268396031000077459
Martikkala, A., David, J., Lobov, A., Lanz, M., & Ituarte, I. F. (2021). Trends for low-cost and open-source IoT solutions development for industry 4.0. Procedia Manufacturing, 55, 298-305. Elsevier. https://doi.org/10.1016/j.promfg.2021.10.042
Khandelwal, A. (2020). Impact of open source software in research. http://dx.doi.org/10.46890/SL.2020.v01i08.002
Dayaratna, A. (2019). How open source is the key to innovation, productivity, collaboration, and transparency within the digital enterprise. IDC. https://assets.ctfassets.net/wfutmusr1t3h/2ZmFv5YNb3pyErnXcCaxrn/7f828ee74aa920eb9adaca267093d9f2/_
downloads_IDC.Report.-.How.open.source.is.the.key.to.innovation.pdf
Theben, A., & Gunderson, L. (2021). Challenges and limits of an open source approach to artificial intelligence policy department for economic, scientific and quality of life policies directorate-general for internal policies [Online]. Available: http://www.europarl.europa.eu/
supporting-analyses
Välimäki, M. (2003). Dual licensing in open source software industry affiliation: Researcher at the Helsinki Institute for Information Technology [Online]. Available: http://ssrn.com/abstract=1261644Electroniccopyavailableat:https://ssrn.com/abstract=1261644Electroniccopyavailableat:http://ssrn.com/abstract=1261644Electroniccopyavailableat:https://ssrn.com/abstract=1261644
Van Smaalen, K., Kutob, L., Griffith, C., Mosunjac, M., & Hanley, K. (2019). Distribution of surgical specimen results for Paps PST63 practice habits and adherence to LAST recommendations to resolve discrepancies between cervical biopsies and LEEP/ConeSpecimens [Online]. Available: http://mde-lab.aegean.gr.
S. Bhattacharya, B. Czejdo, E. Erdemir, R. Agrawal, and B. Gokaraju, “Open Source Platforms and Frameworks for Artificial Intelligence and Machine Learning,” 2018. Accessed: Dec. 13, 2023. [Online]. Available: https://www.researchgate.net/publication/328179850_Open_
Source_Platforms_and_Frameworks_for_Artificial_Intelligence_and_Machine_Learning
Theben, A., & Gunderson, L. (2021). Challenges and limits of an open source approach to artificial intelligence policy department for economic, scientific and quality of life policies directorate-general for internal policies [Online]. Available in http://ww.europarl.europa.eu/
supporting-analyses
Ehioghae E., & Idowu, S. (2021). Open-source software in emerging technologies for economic growth. ITEGAM- Journal of Engineering and Technology for Industrial Applications (ITEGAM-JETIA), 7(27), 63-69. https://doi.org/10.5935/jetia.v7i27.730
Downloads
Published
Issue
Section
License
Copyright (c) 2023 Journal of Mathematical Sciences and Informatics
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
