The Role of Creativity in the Development of Future Intelligent Decision Technologies

  • Andrzej M.J. SkulimowskiEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 364)


This paper presents a methodological background and selected final results of a foresight project concerning the role of creativity in the development of intelligent decision technologies. Technological trends and scenarios have been generated via a simulation of a hybrid system consisting of discrete-time control and discrete-event components. Both form a complex information society model, which describes the evolution of social, economic and scientific factors relevant to the production and adoption of intelligent technologies. The trends and scenarios derived are then discussed and refined during cooperative expert activities. Specifically, we have investigated the development of intelligent decision technologies, with special attention paid to web-based decision support systems, neurocognitive and autonomous systems, as well as artificial creativity aspects. The overall project is outlined in Sect. 2. In Sect. 3, we will present selected trends related to the development of creative technologies in the context of overall progress in information and communication technologies (ICT) and computer science (CS). The discussion of the future role of creativity in the design and implementation of intelligent systems is based on the results of a Delphi study carried out within the recent foresight project SCETIST.


Artificial creativity foresight Multi-round delphi Trend analysis Creativity support systems Intelligent decision technologies 



The research presented in this paper has been conducted within the foresight project “Scenarios and Development Trends of Selected Information Society Technologies until 2025” (SCETIST) co-financed by the ERDF within the Innovative Economy Operational Programme 2006-2013, Contract No. WND-POIG.01.01.01-00-021/09.


  1. 1.
    Brookhart, S.: Assessing creativity. Educ. Leadersh. 70(5), 28–34 (2013)Google Scholar
  2. 2.
    Daim, T.U., Rueda, G., Martin, H., Gerdsri, P.: Forecasting emerging technologies: use of bibliometrics and patent analysis. Technol. Forecast. Soc. Chang. 73, 981–1012 (2006)CrossRefGoogle Scholar
  3. 3.
    Gero, J.S.: Future directions for design creativity research. In: Taura, T., Nagai, Y. (eds.) Design Creativity 2010, pp. 15–22. Springer-Verlag, London (2011)CrossRefGoogle Scholar
  4. 4.
    Iba, T.: An autopoietic systems theory for creativity. In: Riopelle, K., Gloor, P., Miller, C., Gluesing, J. (eds.): 1st Collaborative Innovation Networks Conference–COINS’2009. Procedia Social and Behavioral Sciences, vol. 2(4), pp. 6610–6625. Elsevier Science BV, Amsterdam (2010)Google Scholar
  5. 5.
    Lane, D., Pumain, D., van der Leeuw, S.E., West, G. (eds.). Complexity Perspectives in Innovation and Social Change, Springer Science + Business Media B.V. (2009)Google Scholar
  6. 6.
    Linstone, H.A., Turoff, M. (eds.): The Delphi Method. Techniques and Applications. p. 616 (1975). [Electronic version © Harold A. Linstone, Murray Turoff, 2002]Google Scholar
  7. 7.
    Pereira, C.F.: Creativity and Artificial Intelligence. A Conceptual Blending Approach. Mouton de Gruyter, Berlin, New York, p. 253 (2007)Google Scholar
  8. 8.
    Petrick, I.J., Echols, A.E.: Technology roadmapping in review: A tool for making sustainnable new product development decisions. Technol. Forecast. Soc. Chang. 71, 81–100 (2004)CrossRefGoogle Scholar
  9. 9.
    Plucker, J.A., Makel, M.C.: Assessment of creativity. In: Kaufman, J.C., Sternberg, R.J. (eds.) The Cambridge Handbook of Creativity, pp. 48–73. Cambridge University Press, New York (2010)CrossRefGoogle Scholar
  10. 10.
    Schmidhuber, J.: Developmental robotics, optimal artificial curiosity, creativity, music, and the fine arts. Connect. Sci. 18(2), 173–187 (2006)CrossRefGoogle Scholar
  11. 11.
    Simonton, D.K.: Taking the U.S. patent office criteria seriously: a quantitative three-criterion creativity definition and its implications. Creat. Res. J. 24(2–3), 97–106 (2012)Google Scholar
  12. 12.
    Skulimowski, A.M.J.: Decision Support Systems Based on Reference Sets. AGH University Scientific Publishers, Monographs No. 40, p.167 (1996)Google Scholar
  13. 13.
    Skulimowski, A.M.J.: Framing new member states and candidate countries information society insights. In: Compaño, R., Pascu, C. (eds.) Prospects for a Knowledge-Based Society in the New Members States and Candidate Countries, pp. 9–51. Publishing House of the Romanian Academy, Bucharest (2006)Google Scholar
  14. 14.
    Skulimowski, A.M.J.: Methods of technological roadmapping and foresight (in Polish). Chemik: Nauka-Technika-Rynek 42(5), 197–204 (2009)Google Scholar
  15. 15.
    Skulimowski, A.M.J.: Freedom of choice and creativity in multicriteria decision making. In: Theeramunkong, T., Kunifuji, S, Nattee, C., Sornlertlamvanich, V. (eds.) Knowledge, Information, and Creativity Support Systems: KICSS 2010 Revised Selected Papers, Lecture Notes in Artificial Intelligence, vol. 6746, pp. 190–203. Springer (2011)Google Scholar
  16. 16.
    Skulimowski, A.M.J.: A foresight support system to manage knowledge on information society evolution. In: Aberer K., et al. (eds.) Social Informatics. 4th International Conference, SocInfo 2012, Lausanne, Switzerland, 5–7 Dec 2012, Proceedings. Lecture Notes in Computer Science, vol. 7710, pp. 246–259. Springer, Berlin (2012)Google Scholar
  17. 17.
    Skulimowski, A.M.J.: Discovering complex system dynamics with intelligent data retrieval tools. In: Zhang, Y., et al. (eds.) Sino-foreign-interchange Workshop on Intelligent Science and Intelligent Data Engineering IScIDE 2011, Xi’an, China, 23–26 October 2011. Lecture Notes in Computer Science, vol. 7202, pp. 614–626. Springer, Berlin (2012)Google Scholar
  18. 18.
    Skulimowski, A.M.J.: Universal intelligence, creativity, and trust in emerging global expert systems. In: Rutkowski L., et al. (eds.) Artificial Intelligence and Soft Computing. 12th International Conference, ICAISC 2013, Zakopane, Poland, 9–13 June 2013, Proceedings, Part II. Lecture Notes in Artificial Intelligence, vol. 7895, pp. 582–592. Springer, Berlin (2013)Google Scholar
  19. 19.
    Skulimowski, A.M.J.: Web-based learning in remote areas: evaluation of learning goals, scenarios and bidirectional satellite internet implementation. In: Wang, J.-F., Lau, R. (eds.) Advances in Web-Based Learning—ICWL 2013, 12th International Conference, Kenting, Taiwan, 6–9 October 2013. Proceedings, Lecture Notes in Computer Science, vol. 8167, pp. 50–60. Springer, Berlin (2013)Google Scholar
  20. 20.
    Skulimowski, A.M.J.: Towards a new insight into technological evolution: the foresight of information society and emerging intelligent technologies. In: Skulimowski, A.M.J. (eds.) Looking into the Future of Creativity and Decision Support Systems: Proceedings of the 8th International Conference on Knowledge, Information and Creativity Support Systems, Kraków, Poland, 7–9 November 2013, Advances in Decision Sciences and Future Studies, vol. 2, pp. 599–610. Progress & Business Publishers, Kraków (2013)Google Scholar
  21. 21.
    Skulimowski, A.M.J.: Anticipatory network models of multicriteria decision-making processes. Int. J. Sys. Sci. 45(1), 39–59 (2014). doi: 10.1080/00207721.2012.670308 CrossRefMathSciNetzbMATHGoogle Scholar
  22. 22.
    Skulimowski, A.M.J. (ed.): Scenarios and Development Trends of Selected Information Society Technologies until 2025 (SCETIST). Final Report, Progress & Business Publishers, Kraków (2013).
  23. 23.
    Skulimowski, A.M.J., Pukocz, P.: Enhancing creativity of strategic decision processes by technological roadmapping and foresight. In: Lee, V.C.S., Ong, K.-L. (eds.) KICSS 2012: Seventh International Conference on Knowledge, Information and Creativity Support Systems: Melbourne, Victoria, Australia, 8–10 November 2012. IEEE Computer Society. CPS Conference Publishing Services, pp. 223–230 (2012)Google Scholar
  24. 24.
    Tadeusiewicz, R.: A need of scientific reflection on the information society development. In: Bliźniuk, G., Nowak, J.S. (eds.) Information Society 2005 (in Polish), pp. 11–38. PTI, Katowice (2005)Google Scholar
  25. 25.
    Villani, D., Antonietti, A.: Measurement of creativity. In: Carayannis, E.G. (ed.) Encyclopedia of Creativity, Invention, Innovation and Entrepreneurship, pp. 1234–1238. Springer, New York (2013)CrossRefGoogle Scholar
  26. 26.
    Voigt, M., Bergener, K.: Enhancing creativity in groups–proposition of an integrated framework for designing group creativity support systems. In: Proceedings of the 46th Hawaii International Conference on System Sciences, pp. 225–234. IEEE (2013)Google Scholar
  27. 27.
    von der Gracht, H.A.: Consensus measurement in Delphi studies: Review and implications for future quality assurance. Technol. Forecast. Soc. Chang. 79(8), 1525–1536 (2012)CrossRefGoogle Scholar
  28. 28.
    Wong, Ch-Y, Goh, K.-L.: Modeling the behaviour of science and technology: self-propagating growth in the diffusion process. Scientometrics 84(3), 669–686 (2010)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Chair of Automatic Control, Decision Science LaboratoryAGH University of Science and TechnologyKrakówPoland
  2. 2.International Centre for Decision Sciences and Forecasting, Progress & Business FoundationKrakówPoland

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