Revolutionary Artificial Intelligence or Rogue Technology? The Promises and Pitfalls of ChatGPT

• Autorzy: Marek Sieja , Krzysztof Wach
• Języki publikacji: EN

Abstrakty

EN

Objective: The objective of the article is to offer a thorough exploration and comprehension of the obstacles and potential advantages linked to the application of generative artificial intelligence (GAI) in the business realm, particularly emphasizing ChatGPT. Research Design & Methods: The research utilized a narrative and critical examination of existing literature and constructed a conceptual framework grounded in prior studies. Our theoretical framework was developed through a deductive reasoning approach to ensure the logical and effective organization of the study. Consequently, this work should be considered a conceptual article that sheds light on one hand on the promises and opportunities, and on the other hand on the controversies and risks associated with generative artificial intelligence in the fields of management and economics, using ChatGPT as a specific case study. Findings: In recent years, artificial intelligence has experienced rapid progress, leading to its widespread applications. The chatbot industry, exemplified by ChatGPT, has garnered considerable attention, with experts and researchers asserting that generative artificial intelligence and ChatGPT could transform our work routines and daily existence. Although these technologies have the potential to revolutionize data analysis and report generation, concerns have been raised about their societal impacts, particularly in areas such as ethics, privacy, and security. Implications & Recommendations: The regulation of the GAI market is imperative to ensure fairness, competitive balance, and safeguard intellectual property and privacy while addressing potential geopolitical risks. With the evolving job landscape, individuals must continuously acquire new digital skills through education, particularly in response to the growing prominence of AI system training. Ethical considerations, such as prioritizing user privacy and security, are crucial for GAI developers to mitigate risks related to personal data violation and social surveillance, emphasizing responsible AI practices and adherence to ethical guidelines to prevent social manipulation and maintain goodwill. Contribution & Value Added: The article structures scientific knowledge on the advantages and drawbacks of the generative artificial intelligence in business. The articles attempted to put together the main aspects of this new phenomenon. (original abstract)

Słowa kluczowe

EN

Artificial intelligence; Technology; Digital technologies

PL

Sztuczna inteligencja; Technologia; Technologie cyfrowe

• Czasopismo: International Entrepreneurship Review
• Rocznik: 2023
• Tom: 9
• Numer: nr 4
• Strony: 101--115

Twórcy

autor

Marek Sieja

• Cracow University of Technology

autor

Krzysztof Wach

• Krakow University of Economics

Bibliografia

• 1. Aly, H. (2022). Digital transformation, development and productivity in developing countries: is artificial intelligence a curse or a blessing?. Review of Economics and Political Science, 7(4), 238-256. https://doi.org/10.1108/REPS-11-2019-0145
• 2. Bengio, Y., Courville, A., & Vincent, P. (2013). Representation learning: A review and new perspectives. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(8), 1798-1828.
• 3. Bonet-Jover, A., Sepúlveda-Torres, R., Saquete, E., & Martínez-Barco, P. (2023). A semi-automatic annotation methodology that combines Summarization and Human-In-The-Loop to create disinformation detection resources. Knowledge-Based Systems, 275, 110723. https://doi.org/10.1016/j.knosys.2023.110723
• 4. Cappa, F., Oriani, R., Peruffo, E., & McCarthy, I. (2021). Big data for creating and capturing value in the digitalized environment: unpacking the effects of volume, variety, and veracity on firm performance. Journal of Production and Innovation Management, 38 49-67. https://doi.org/10.1111/jpim.12545
• 5. Chatterjee, S., Sreenivasulu, N.S., & Hussain, Z. (2022). Evolution of artificial intelligence and its impact on human rights: from sociolegal perspective. International Journal of Law and Management, 64(2), 184-205. https://doi.org/10.1108/IJLMA-06-2021-0156
• 6. Costello, E. (2023). ChatGPT and the Educational AI Chatter: Full of Bullshit or Trying to Tell Us Something?. Postdigital Science and Education. https://doi.org/10.1007/s42438-023-00398-5
• 7. Derish, P.A, & Annesley, T.M. (2011). How to write a rave review. Clinical Chemistry, 57(3), 388-391. https://doi.org/10.1373/clinchem.2010.160622
• 8. 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
• 9. Dumrak, J. & Zarghami, S.A. (2023). The role of artificial intelligence in lean construction management. Engineering, Construction and Architectural Management, Ahead-of-Print. https://doi.org/10.1108/ECAM-02-2022-0153
• 10. 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, (13), 247-264. https://doi.org/10.55609/yenimedya.1146586
• 11. Ferrari, R. (2015). Writing narrative style literature reviews. Medical Writing, 24(4), 230-235.
• 12. Fisher, C. et al. (2010). Researching and Writing a Dissertation. 3rd edition. Harlow: Prentice Hall.
• 13. 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
• 14. Głodowska, A., Maciejewski, M., & Wach, K. (2023). Navigating the digital landscape: A conceptual framework for understanding digital entrepreneurship and business transformation. International Entrepreneurship Review, 9(4), 7-20. https://doi.org/10.15678/IER.2023.0904.01
• 15. He, A.-Z., & Zhang, Y. (2023). AI-powered touch points in the customer journey: a systematic literature review and research agenda. Journal of Research in Interactive Marketing, 17(4), 620-639. https://doi.org/10.1108/JRIM-03-2022-0082
• 16. Hoque, M.A., Rasiah, R., Furuoka, F., & Kumar, S. (2022). Linkages among automation, job displacement and reshoring: evidence from the Bangladeshi apparel industry. Research Journal of Textile and Apparel, 26(4), 515-531. https://doi.org/10.1108/RJTA-04-2021-0044
• 17. Jaiwant, S.V. (2023). The Changing Role of Marketing: Industry 5.0 - the Game Changer (pp. 187-202). In Saini, A. and Garg, V. (Ed.), Transformation for Sustainable Business and Management Practices: Exploring the Spectrum of Industry 5.0. Leeds: Emerald Publishing. https://doi.org/10.1108/978-1-80262-277-520231014
• 18. Janssen, M., & Kuk, G. (2016). The challenges and limits of big data algorithms in technocratic governance, Government Information Quarterly, 33(3) 371-377. https://doi.org/10.1016/j.giq.2016.08.011
• 19. 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
• 20. 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
• 21. Kitsara, I. (2022). Artificial Intelligence and the Digital Divide: From an Innovation Perspective. In A. Bounfour (Ed.) Platforms and Artificial Intelligence. Progress in IS (pp. 245-265). Springer, Cham. https://doi.org/10.1007/978-3-030-90192-9_12
• 22. Korzynski, P., Kozminski, A.K., & Baczynska, A. (2023a). Navigating leadership challenges with technology: Uncovering the potential of ChatGPT, virtual reality, human capital management systems, robotic process automation, and social media. International Entrepreneurship Review, 9(2), 7-18. https://doi.org/10.15678/IER.2023.0902.01
• 23. Korzynski, P., Mazurek, G., Altmann, A., Ejdys, J., Kazlauskaite, R., Paliszkiewicz, J., Wach, K., & Ziemba, E. (2023b). Generative artificial intelligence as a new context for management theories: analysis of ChatGPT. Central European Management Journal, 31(1), 3-13. https://doi.org/10.1108/CEMJ-02-2023-0091
• 24. Korzynski, P., Mazurek, G., Krzypkowska, P., & Kurasinski, A. (2023c). Artificial intelligence prompt engineering as a new digital competence: Analysis of generative AI technologies such as ChatGPT. Entrepreneurial Business and Economics Review, 11(3), 25-37. https://doi.org/10.15678/EBER.2023.110302
• 25. Korzynski, P., Rook, C., Florent Treacy, E., & Kets de Vries, M. (2021). The impact of self-esteem, conscientiousness and pseudo-personality on technostress. Internet Research, 31(1), 59-79. https://doi.org/10.1108/INTR-03-2020-0141
• 26. Kumar, A., Gupta, N., & Bapat, G. (2023a). Who is making the decisions? How retail managers can use the power of ChatGPT. Journal of Business Strategy. Ahead-of-Print. https://doi.org/10.1108/jbs-04-2023-0067
• 27. Kumar, A., Krishnamoorthy, B., & Bhattacharyya, S.S. (2023b). 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
• 28. Kwong, C.K., Jiang, H., & Luo, X.G. (2016). AI-based methodology of integrating affective design, engineering, and marketing for defining design specifications of new products. Engineering Applications of Artificial Intelligence, 47(10, 49-60. https://doi.org/10.1016/j.engappai.2015.04.001
• 29. Lee, L.W., Dabirian, A., McCarthy, I.P, &. Kietzmann, J. (2020). Making sense of text: artificial intelligence-enabled content analysis. European Journal of Marketing, 54(3), 615-644. https://doi.org/10.1108/EJM-02-2019-0219
• 30. Lutz, C. (2019). Digital inequalities in the age of artificial intelligence and big data. Human Behaviour and Emerging Techgnologies, 1(2), 141-148. https://doi.org/10.1002/hbe2.140
• 31. Mariani, M.M., Machado, I., Magrelli, V., & Dwivedi, Y.K. (2023). Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions. Technovation, 122, 102623. https://doi.org/10.1016/j.technovation.2022.102623
• 32. Mazurek, G. (2023). Artificial Intelligence, Law, and Ethics. Krytyka Prawa, 15(1), 11-14. https://doi.org/10.7206/kp.2080-1084.568
• 33. Mazurek, G., & Małagocka, K. (2019). Perception of privacy and data protection in the context of the development of artificial intelligence. Journal of Management Analytics, 6(4), 344-364. https://doi.org/10.1080/23270012.2019.1671243
• 34. Nair, K. (2019). Overcoming today's digital talent gap in organizations worldwide. Development and Learning in Organizations, 33(6), 16-18. https://doi.org/10.1108/DLO-02-2019-0044
• 35. 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
• 36. Pahl, S. (2023). An emerging divide: Who is benefiting from AI?. IAP-UNIDO. Retrieved from https://iap.unido.org/articles/emerging-divide-who-benefiting-ai

Identyfikatory

DOI

https://doi.org/10.15678/IER.2023.0904.07