نوع مقاله : مقاله علمی-پژوهشی
موضوعات
عنوان مقاله English
نویسندگان English
The proliferation of generative artificial intelligence, from healthcare to finance, underscores its transformative potential in addressing real-world challenges. The generative AI model is trained to act almost like a human. The conversational format allows the AI to answer follow-up questions, admit mistakes, challenge false premises, and reject inappropriate requests. Also, generative artificial intelligence provides huge opportunities for organizations that use this advanced technology strategically. Therefore, the current research was conducted with the aim of identifying the antecedents and consequences of the productive artificial intelligence tool using the fuzzy FCM method. The statistical population of the research is the experts in the field of information technology and artificial intelligence, among whom 10 people were selected as sample members using the purposeful sampling method and based on the principle of theoretical saturation. The tool for collecting information is an interview in the qualitative part and a questionnaire in the quantitative part. In this research, the content analysis method and coding with Atlas software were used to analyze the data in the qualitative part, and the content method and theoretical validity and intra-coder inter-coder reliability were used to check the validity and reliability of the data collection tool in the qualitative part. Its reliability was confirmed with a coefficient of 0.84. Also, the validity and reliability of the data collection tool in the quantitative part, content validity and retest reliability showed the confirmation of the reliability of the questionnaires. Also, the validity and reliability of the research questionnaire was measured by content and retest validity. The findings of the research show that the most important antecedent factors for the development of productive artificial intelligence are keeping pace with the fundamental changes in technology, the possibility of correcting organizational gaps, and facilitating the learning of employees. Also, the most important consequences of the formation of productive artificial intelligence are speeding up the implementation of processes, increasing efficiency and productivity, and the risk of privacy violations.
کلیدواژهها English
Acemoglu, Daron and David Autor, “Skills, tasks and technologies: Implications for employment and earnings,” in “Handbook of labor economics,” Vol. 4, Elsevier, 2011, pp. 1043–1171.
Ahmed, Sagashnejad, Ahmadi, Amirmohammed, Abedinzadeh, Fatemi, ... & Seyed Iman. (2024). Generative Artificial Intelligence: Multidisciplinary Perspectives on Opportunities, Challenges, and Implications for Research, Practice, and Policy. Science and Technology Policy, 17, 1-100 (In Persian).
Arrieta, A. B., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., Chatila, R., & Herrera, F. (2020). Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities, and challenges toward responsible AI. Information Fusion, 58, 82–115.
Autor, David, “Polanyi’s Paradox and the Shape of Employment Growth,” Working Paper w20485, National Bureau of Economic Research September 2014.
Banh, L., & Strobel, G. (2023). Generative artificial intelligence. Electronic Markets, 33(1), 63.
Beam, E.A. 2023. “Social media as a recruitment and data collection tool: Experimental evidence on the relative effectiveness of web surveys and chatbots.” Journal of Development Economics, 162: 103069
Brynjolfsson, E., Li, D., & Raymond, L. R. (2023). Generative AI at work (No. w31161). National Bureau of Economic Research.
Buberk, S., V. Chandrasekaran, R. Eldan, J. Henrke, E. Horvitz, E. Kamar, P. Lee, et al. 2023. “Sparks of artificial general intelligence: Early experiments with GPT-4.
Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran, J. R., Boselie, P., Cooke, F. L., Decker, S., DeNisi, A., Dey, P. K., Guest, D., Knoblich, A. J., Malik, A., Paauwe, J., Papagiannidis, S., Patel, C., Pereira, V., Ren, S., Rogelberg, S., Saunders, M. N. K., Tung, R. L., & Varma, A. (2023). Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. Human Resource Management Journal, 33(3), 606–659.
Chen, B., Wu, Z., & Zhao, R. (2023). From fiction to fact: the growing role of generative AI in business and finance. Journal of Chinese Economic and Business Studies, 21(4), 471-496.
Chuma, E. L., & de Oliveira, G. G. (2023). Generative AI for business decision-making: A case of ChatGPT. Management Science and Business Decisions, 3(1), 5-11.
Chuma, E. L., & de Oliveira, G. G. (2023). Generative AI for business decision-making: A case of ChatGPT. Management Science and Business Decisions, 3(1), 5-11.
Clarke, L. 2023. “Alarmed tech leaders call for AI research pause.” Science, 380: 120- 121.
Debnath, R., R. Bardhan, D.U. Shah, K. Mohaddes, M.H. Ramage, R.M. Alvarez, and B.K. Sovacool. 2022. “Social media enables people-centric climate action in the hard-to-decarbonise building sector.” Scientific Reports, 12: 19017.
Desouza, K. C., Dawson, G. S., & Chenok, D. (2020). Designing, developing, and deploying artificial intelligence systems: Lessons from and for the public sector. Business Horizons, 63(2), 205–213.
Dwivedi, Y.K., N. Kshetri, L. Hughes, E.L. Slade, A. Jeyaraj, A.K. Kar, A.M. Baabdullah. 2023. “’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,
Feuerriegel, S., Hartmann, J., Janiesch, C., & Zschech, P. (2024). Generative ai. Business & Information Systems Engineering, 66(1), 111-126.
Gupta, R., Nair, K., Mishra, M., Ibrahim, B., & Bhardwaj, S. (2024). Adoption and impacts of generative artificial intelligence: Theoretical underpinnings and research agenda. International Journal of Information Management Data Insights, 4(1), 100232.
Hansen, A.L., and S. Kazinnik. 2023. “Can ChatGPT decipher fedspeak?” SSRN.
Hashem, R., Ali, N., El Zein, F., Fidalgo, P., & Khurma, O. A. (2024). AI to the rescue: Exploring the potential of ChatGPT as a teacher ally for workload relief and burnout prevention. Research and Practice in Technology Enhanced Learning, 19, 023.
Hassanzadeh, M. (2022). Intelligent agents and facilities for knowledge management: Chatgpt and beyond. Sciences and Techniques of Information Management, 8(4), 7-22.
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577–586.
Jarrahi, M. H., Askay, D., Eshraghi, A., & Smith, P. (2023). Artificial intelligence and knowledge management: A partnership between human and AI. Business Horizons, 66(1), 87–99.
Kanbach, D., Heiduk, L., Blueher, G., Schreiter, M., & Lahmann, A. (2023). The GenAI is out of the bottle: Generative artificial intelligence from a business model innovation perspective. Review of Managerial Science. Available at https://doi.org/10.1007/s11846-023- 00696-z
Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25.
Katz, Lawrence F. and Kevin M. Murphy, “Changes in Relative Wages, 1963-1987: Supply and Demand Factors,” The Quarterly Journal of Economics, 1992, 107 (1), 35–78.
Korinek, A. 2023. “Language models and cognitive automation for economic research.” National Bureau of Economic Research Working Paper 30957.
Korzynski, P., G. Mazurek, A. Altmann, J. Ejdys, R. Kazlauskaite, J. Paliszkiewicz, K. Wach, and E. Ziemba. 2023. “Generative artificial intelligence as a new context for management theories: Analysis of ChatGPT.” Central European Management Journal, 38: 3-13.
Krakowski, S., Luger, J., & Raisch, S. (2023). Artificial intelligence and the changing sources of competitive advantage. Strategic Management Journal, 44(6), 1425–1452.
Linkon, A. A., Shaima, M., Sarker, M. S. U., Nabi, N., Rana, M. N. U., Ghosh, S. K., ... & Chowdhury, F. R. (2024). Advancements and Applications of Generative Artificial Intelligence and Large Language Models on Business Management: A Comprehensive Review. Journal of Computer Science and Technology Studies, 6(1), 225-232.
Marinucci, L., Mazzuca, C., & Gangemi, A. (2023). Exposing implicit biases and stereotypes in human and artificial intelligence: State of the art and challenges with a focus on gender. AI and Society, 38, 747–761.
McIntosh, T. R., Liu, T., Susnjak, T., Watters, P., Ng, A., & Halgamuge, M. N. (2023). A culturally sensitive test to evaluate nuanced GPT hallucination. IEEE Transactions on Artificial Intelligence, 1, 1–13.
Metze, K., Morandin-Reis, R. C., Lorand-Metze, I., & Florindo, J. B. (2023). Bibliographic research with ChatGPT may be misleading: The problem of hallucination. Journal of Pediatric Surgery, 59(1), 158.
Michaels, Guy, Ashwini Natraj, and John Van Reenen, “Has ICT Polarized Skill Demand? Evidence from Eleven Countries Over Twenty-Five Years,” The Review of Economics and Statistics, 2014, 96 (1), 60.
Naveed, H., Khan, A. U., Qiu, S., Saqib, M., Anwar, S., Usman, M., ... & Mian, A. (2023). A comprehensive overview of large language models. arXiv preprint arXiv:2307.06435.
Noy, S., and W. Zhang. 2023. “Experimental evidence on the productivity effects of generative artificial intelligence.” SSRN.
Peng, Baolin, Michel Galley, Pengcheng He, Hao Cheng, Yujia Xie, Yu Hu, Qiuyuan Huang, Lars Liden, Zhou Yu, Weizhu Chen, and Jianfeng Gao, “Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback,” 2023.
Robertson, J., Ferreira, C., Botha, E., & Oosthuizen, K. (2024). Game changers: A generative AI prompt protocol to enhance human-AI knowledge co-construction. Business Horizons.
Savage, N. 2023. “Synthetic data could be better than real data.” Nature, April 27, 2023.
Scepanovic, S., M. Constantinides, D. Quercia, and S. Kim. 2023. “Quantifying the impact of positive stress on companies from online employee reviews.” Scientific Reports, 13: 1603.
Senior, M. 2023. “Precision financing.” Nature Biotechnology, April 12, 2023.
Short, C. E., & Short, J. C. (2023). The artificially intelligent entrepreneur: ChatGPT, prompt engineering, and entrepreneurial rhetoric creation. Journal of Business Venturing Insights, 19, e00388.
Stojanov, A. (2023). Learning with ChatGPT 3.5 as a more knowledgeable other: An autoethnographic study. International Journal of Educational Technology in Higher Education, 20, 35.
The White House, “The Impact of Artificial Intelligence on the Future of Workforces in the European Union and the United States of America,” Technical Report, The White House December 2022.
Yang, H. 2023. “How I use ChatGPT responsibly in my teaching.” Nature, April 12, 2023.
Yang, K.C., and F. Menczer. 2023. “Large language models can rate news outlet credibility.” Unpublished manuscript.
