Study on the Beneficial Impacts and Ethical Dimensions of Generative AI in Software Product Management

Authors

  • Suneet Gupta Professor, CSE Dept, Alliance College of Engineering and Design, Alliance University Bangalore.
  • Pragalbh Sharma Assistant Professor, Institute of Business Management, GLA University, Mathura
  • Shweta Chaudhary Assistant Professor, Department of Management, Seth Padam Chand Jain Institute of Management, Khandari, Agra.
  • Vinod Kumar Associate Professor, M.M. Institute of Management, Maharishi Markandeshwar (Deemed to be University), Mullana-Ambala, Haryana, India 133207
  • Surinder Pal Singh Assistant Professor, Department of CSE, MMEC, Maharishi Markandeshwar (Deemed to be University), Mullana-Ambala, Haryana, India 133207.
  • Melanie Lourens Deputy Dean Faculty of Management Sciences, Durban University of Technology, South Africa.
  • Nimisha Beri Professor, School of Education, Lovely Professional University.

Keywords:

Generative AI, Product Manager, Product Management, AI Applications in Product Management, Applications of Generative AI, Generative AI Tools, Generative AI Limitations, Ethical Considerations

Abstract

The field of generative artificial intelligence (GAI) has advanced significantly in recent years, and its effects may be seen across the software product management industry. This comprehensive literature review draws on relevant studies published between 2016 and 2023 and demonstrates the possible uses, advantages, and restrictions of generative AI in this domain. The research demonstrates that technology aids in ideation, market research, consumer insights, spec writing, and product development. By automating tasks like code production and analysing user input, it may cut down on expensive and time-consuming software development. However, there are still concerns about the precision and safety of the technology, as well as ethical implications. Practical applications of generative AI have the potential to greatly enhance software product management processes, leading to more effective use of resources, higher quality product results, and enhanced user experiences.

Downloads

Download data is not yet available.

References

Appel, G., Neelbauer, J., & Schweidel, D. A. (2023). Generative AI has an intellectual property problem. hbr.org: https://hbr.org/2023/04/generative-ai-has-an-intellectual-property-problem

Brand, J., Israeli, A., & Ngwe, D. (2023). Using gpt for market research. SSRN 4395751.

Brynjolfsson, E., Li, D., & Raymond, L. R. (2023). Generative AI at Work (No. w31161). National Bureau of Economic Research.

Cao, Y., Li, S., Liu, Y., Yan, Z., Dai, Y., Yu, P. S., & Sun, L. (2023). A comprehensive survey of AI-generated content (AIGC): A history of generative AI from GAN to chatGPT. arXiv preprint arXiv:2303.04226.

Dam, H. K., Tran, T., Grundy, J., Ghose, A., & Kamei, Y. (2019, May). Towards effective AI- powered agile project management. In 2019 IEEE/ACM, 41st international conference on software engineering: New ideas and emerging results (ICSE-NIER) (pp. 41-44). IEEE.

Davenport, T. H., & Mittal, N. (2022, November 14). How generative AI is changing creative work. hbr.org: https://hbr.org/2022/11/how-generative-ai-is-changing-creative-work

Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., ... & Wright, R. (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, 71, 102642.

Fu, M., & Tantithamthavorn, C. (2022). Gpt2sp: A transformer-based agile story point estimation approach. IEEE Transactions on software engineering.

GDPR. (2023). Principles relating to processing of personal data. gdpr-info.eu: https://gdpr- info.eu/art-5-gdpr/

Grandviewresearch. (2023, May). Generative AI market size to reach $109.37 billion by 2030. https://www.grandviewresearch.com/press-release/global-generative-ai-market

Hacker, P., Engel, A., & Mauer, M. (2023). Regulating ChatGPT and other large generative AI models. arXiv preprint arXiv:2302.02337.

Houde, S., Ross, S. I., Muller, M., Agarwal, M., Martinez, F., Richards, J., ... & Weisz, J. D. (2022, March). Opportunities for generative AI in UX modernization. In Joint International Conference on Intelligent User Interfaces Workshops: APEx-UI, HAI-GEN, HEALTHI, HUMANIZE, TExSS, SOCIALIZE.

ISPMA. (2023). A comprehensive guide for effective software product management. https://ispma.org/bok/

Karim, M. R., Antar, S. S., & Khan, M. A. (2022, December). Idea generation using transformer decoder models. In Proceedings of the 2022 5th international conference on algorithms, computing and artificial Intelligence (pp. 1-5).

Khan, J. Y., & Uddin, G. (2022, October). Automatic code documentation generation using GPT-

3. In 37th IEEE/ACM international conference on automated software engineering (pp. 1-6).

Kim, H., Choi, B., & Cho, H. (2021). AI-driven user story points estimation based on natural language processing. Journal of Systems and Software, 171, 110818.

Korzynski, P., Mazurek, G., Altmann, A., Ejdys, J., Kazlauskaite, R., Paliszkiewicz, J., ... & Ziemba, E. (2023). Generative artificial intelligence as a new context for management theories: Analysis of ChatGPT. Central European Management Journal.

Lewin, K. (1947). Frontiers in group dynamics: Concept, method and reality in social science; social equilibria and social change. Human Relations, 1(1), 5-41.

Malik, G., Cevik, M., Parikh, D., & Basar, A. (2022). Identifying the requirement conflicts in SRS documents using transformer-based sentence embeddings. arXiv preprint arXiv:2206.13690.

McKinsey & Company. (2022, August). McKinsey technology trends outlook 2022. https://www.mckinsey.com/~/media/mckinsey/business%20functions/mckinsey%20digital/our%2 0insights/the%20top%20trends%20in%20tech%202022/McKinsey-Tech-Trends-Outlook-2022- Applied-AI.pdf

Nguyen, M. T., Nguyen, P. T., Nguyen, V. V., & Nguyen, Q. M. (2021, November). Generating product description with generative pre-trained transformer 2. In 2021 6th international conference on innovative technology in intelligent system and industrial applications (CITISIA) (pp. 1-7). IEEE.

Owen, R., Stilgoe, J., Macnaghten, P., Gorman, M., Fisher, E., & Guston, D. (2013). A framework for responsible innovation. Responsible innovation: Managing the responsible emergence of science and innovation in society, 27-50.

Paajoki, A. (2020). Best practices for and benefits from implementing ISPMA’s SPM framework.

Park, Y., Park, A., & Kim, C. (2023). ALSI-Transformer: Transformer-based code comment generation with aligned lexical and syntactic information. IEEE Access.

Peng, S., Kalliamvakou, E., Cihon, P., & Demirer, M. (2023). The impact of AI on developer productivity: Evidence from github copilot. arXiv preprint arXiv:2302.06590.

Peters, T. J., & Waterman, R. H. (1984). In search of excellence. Nursing Administration Quarterly, 8(3), 85-86.

Radford, A., Narasimhan, K., Salimans, T., & Sutskever, I. (2021). Scaling laws for autoregressive generative modeling. arXiv preprint arXiv:2102.08602.

Siggelkow, N., & Terwiesch, C. (2023, April 4). Create winning customer experiences with generative AI. Harvard Business Review. https://www.hbr.org/2023/04/create-winning-customer- experiences-with-generative-ai

Simon, H. A. (1987). Making management decisions: The role of intuition and emotion. Academy of Management Perspectives, 1(1), 57-64.

Statista. (2023, May 24). Size of the chatbot market worldwide from 2021 to 2030. statista: https://www.statista.com/statistics/656596/worldwide-chatbot-market/

The Artificial Intelligence Act. (2023). The Artificial Intelligence Act. artificialintelligenceact.eu: https://artificialintelligenceact.eu/

Xu, W. (2023). AI in HCI design and user experience. arXiv preprint arXiv:2301.00987

Zhang, M., Gang, Z., Yu, W., Huang, N., & Liu, W. (2022). MAA-PTG: Multimodal aspect-aware product title generation. Journal of Intelligent Information Systems, 59(1), 213-235.

Downloads

Published

13.12.2023

How to Cite

Gupta, S. ., Sharma, P. ., Chaudhary, S. ., Kumar, V. ., Singh, S. P. ., Lourens, M. ., & Beri, N. . (2023). Study on the Beneficial Impacts and Ethical Dimensions of Generative AI in Software Product Management. International Journal of Intelligent Systems and Applications in Engineering, 12(8s), 251–264. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4116

Issue

Section

Research Article