Generative AI in Management – Today and Tomorrow

Jerzy Korczak, Ilona Pawełoszek

Abstract


Theoretical background: The rapid and exponential technological advancements have far-reaching impacts on management information systems, management practices, and human life. The promising outcomes in Artificial Intelligence and cutting-edge research on semantic networks and natural language processing have motivated the authors to envision the future of management technology.

Purpose of the article: Our paper focuses on the new communication facilities and artificial intelligence models used to process management-type queries in natural language.

Research methods: The article discusses recently developed technologies, proposed by Google and Microsoft, notably Google Bard and Bing integrated with ChatGPT-4. Both chatbots use Generative AI methods and large language models to understand domain-based queries and generate answers.

Main findings: The practical and social implications of new models in management practice are discussed. To illustrate the qualities and weaknesses of the features of new technologies, four examples of management decision-making are discussed. The case studies also show differences between these two technologies. Finally, the paper concludes by summarizing the expectations and limitations of Generative AI applications in management. The paper is one of the first publications describing and demonstrating the idea of interfaces in natural language in business-oriented applications.


Keywords


Artificial Intelligence in business; human-computer interface; natural language processing; decision-making

Full Text:

PDF

References


Adiwardana, D. et al. (2020). Towards a human-like open-domain chatbot. arXiv:2001.09977. doi:10.48550/arXiv.2001.09977

Alexopoulos, P. (2020). Semantic Modeling for Data. Avoiding Pitfalls and Breaking Dilemmas. O’Reilly Media.

Babcock, J., & Bali, R. (2021). Generative AI with Python and TensorFlow 2. Packt Publishing.

Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web. Scientific American, 284(5), 34–43.

Bianchi, C. (2023). Global Search Engine Desktop Market Share. Retrieved from https://www.statista.com/statistics/216573/worldwide-market-share-of-search-engines/

Bollacker, K., Evans, C., Paritosh, P., Sturge, T., & Taylor, J. (2008). Freebase: A collaboratively created graph database for structuring human knowledge. SIGMOD 08 Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, 1247–1250.

Bostrom, N. (2016). Superintelligence: Paths, Dangers, Strategies. Oxford: Oxford University Press.

Brown, T. et al. (2020). Language models are few-shot learners. Advances in Neural Information Processing Systems, 33, 1877–1901.

Canbek, N.G., & Mutlu, M.E. (2016). On the track of artificial intelligence: Learning with intelligent personal assistants. Journal of Human Sciences, 13(1), 592–601. doi:10.14687/ijhs.v13i1.3549

Chien, C.F., Dauzère-Pérès, S., Huh, W.T., Jang, Y.J., & Morrison, J.R. (2020). Artificial intelligence in manufacturing and logistics systems: Algorithms, applications, and case studies. International Journal of Production Research, 58(9), 2730–2731. doi:10.1080/00207543.2020.1752488

Conroy, S. (2023). Google Bard and AI integration with Google Maps. Retrieved from https://www.wepc.com/tips/google-bard-with-google-maps/

Cook, M. (2022). Benchmarking: Diffbot Knowledge Graph Versus Google Knowledge Graph. Retrieved from https://blog.diffbot.com/author/merrill/

Foster, D. (2019). Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play. O’Reilly Media.

Fraley, A. (2023). The Artificial Intelligence and Generative AI Bible. Int. Kindle Ed.

Gopalakrishnan, K. et al. (2019). Topical-Chat: Towards Knowledge-Grounded Open-Domain Conversations. Proc. Interspeech, 1891–1895.

Gulliksen, J., Cajander, Å., Sad, B., Eriksson, E., & Kavathatzopoulos, I. (2009). User-centered systems design as organizational change: A longitudinal action research project to improve usability and the computerized work environment in a public authority. International Journal of Technology and Human Interaction, 5(3), 13–53.

Hoffman, R. (2023). Impromptu: Amplifying Our Humanity Through AI. Dallepedia

Hussien, A., Rahma, A., & Wahab, A. (2021). Recommendation systems for e-commerce systems: An overview. Journal of Physics. Conference Series, 1897. doi:10.1088/1742-6596/1897/1/012024

James, L. (2023). 8 Steps for an Effective Decision Making Process. Retrieved from https://www.londonbusinessmag.co.uk/effective-decision-making

Kurzweil, R. (2006). Singularity Is Near. When Humans Transcend Biology. Springer.

Lopatovska, I. (2019). Overview of the Intelligent Personal Assistants. Ukrainian Journal on Library and Information Science. doi:10.31866/2616-7654.3.2019.169669

Min, B. et al. (2021). Recent advances in natural language processing via large pre-trained language models: A survey. doi:10.48550/arXiv.2111.01243

Pawełoszek, I., & Korczak, J. (2023). Future Manager – Perspective of Human and Artificial Intelligence, Futures, (to be published).

Piotrowski, D. (2022). Demographic and Socio-Economic Factors as Barriers to Robo-Advisory Acceptance in Poland. Annales Universitatis Mariae Curie-Skłodowska, sectio H – Oeconomia, 56(3), 109–126. doi:10.17951/h.2022.56.3.109-126

Popovic, M. (2023). Automate Your Decision-Making with ChatGPT. Retrieved from https://docs.kanaries.net/articles/chatgpt-auto-decision-making

Power, D.J. (2008). Decision support systems: A historical overview. In P. Bernus, J. Blazewicz, G. Schmidt & M.J. Shaw (Eds.), Handbook on Decision Support Systems 1 (pp. 121–140). Berlin – Heidelberg: Springer. doi:10.1007/978-3-540-48713-5_7

Roehl, U.B.U. (2022). Understanding automated decision-making in the public sector: A classification of automated, administrative decision-making. In G. Juell-Skielse, I. Lindgren & M. Åkesson (Eds.), Service Automation in the Public Sector. Progress in IS. Springer. doi:10.1007/978-3-030-92644-1_3

Singhal, A. (2012). Introducing the Knowledge Graph: things, not strings. The Keyword (blog), Google. May 26. Retrieved from https://blog.google/products/search/introducing-knowledge-graph-things-not/

Sordoni, A. et al. (2015). A Neural Network Approach to Context-Sensitive Generation of Conversational Responses. Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2015 (pp. 196–205). 31 May – 5 June 2015. Denver: Association for Computational Linguistics (ACL).

Stohr, E.A., & White, N. (1983). User Interfaces for Decision Support Systems: An Overview. NYU Working Paper No. IS-82-63. Retrieved from https://ssrn.com/abstract=1290182

Tarus, J.K., Niu, Z., & Mustafa, G. (2018). Knowledge-based recommendation: A review of ontology-based recommender systems for e-learning. Artificial Intelligence Review, 50, 21–48. doi:10.1007/s10462-017-9539-5

Thoppilan, R. et al. (2022). LaMDA: Language Models for Dialog Applications. Computation and Language. doi:10.48550/arXiv.2201.08239

Torrey, L., & Shavlik, J. (2010). Transfer Learning. In Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques (pp. 242–264). Hershey IGI Global. doi:10.4018/978-1-60566-766-9.ch011

Vinyals, O., & Le, Q.V. (2015). A neural conversational model. arXiv:1506.05869. doi:10.48550/arXiv.1506.05869

Wang, H. et al. (2022). Enabling Harmonious Human-Machine Interaction with Visual-Context Augmented Dialogue System: A Review. arXiv, abs/2207.00782. doi:10.48550/arXiv.2207.00782

Wolfram, S. (2023). What Is ChatGPT Doing ... and Why Does It Work? Wolfram Media.

Zhao, W.X. et al. (2023). A Survey of Large Language Models. arXiv, abs/2303.18223.

Zinczuk B. (2018). Artificial intelligence and its socially responsible use in the modern economy. Annales Universitatis Mariae Curie-Skłodowska, sectio H – Oeconomia, 52(5), 125–133. doi:10.17951/h.2018.52.5.125-133




DOI: http://dx.doi.org/10.17951/h.2023.57.4.123-143
Date of publication: 2023-12-23 17:34:12
Date of submission: 2023-08-21 14:44:52


Statistics


Total abstract view - 1405
Downloads (from 2020-06-17) - PDF - 0

Indicators



Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 Jerzy Korczak, Ilona Pawełoszek

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.