International Journal of Advanced Culture Technology

The International Promotion Agency of Culture Technology (국제문화기술진흥원)
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User Perception of Ai Self-Organizing Natural Image Generation Analyzed by Cognitive Paradigm

  • Received : 2024.07.25
  • Accepted : 2024.09.01
  • Published : 2024.09.30
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Abstract

The algorithm is applied on the premise that the image generated by AI can be recognized and used smoothly by the user. Other assets are not exposed to the user or discarded because they are unnecessary or unfamiliar. This study aims to expand the scope of the utility of the image generated by AI, which is used as a high-level tool in the design field. To this end, we first examined human information processing and reflection in AI by the cognitive paradigm by examining previous studies and cases, and discussed the value of expansion by focusing on creativity and bottom-up processing of AI's self-organization. Considering the human recogmition process that instinctively grasps an object, the following AI usability was proposed. It is to utilize AI as a high-level tool applied appropriately to human perception, or to utilize the derivative itself by bottom-up self-organization. In addition, it is to set the algorithm to the minimum intervention so that basic elements such as shape, color, size, texture, and movement are composed of figure-ground according to the human perception process that instinctively grasps an object, and to utilize the results. Limiting the use of AI to a tool suitable for human perception and information processing or production by designers or general users is to operate only a part of the convenience and usability of AI. The image creation through AI's self-organization, as seen from the cognitive paradigm, is a step toward opening a new era of design where technical aesthetics meets devices, just as design has been constantly developing in pursuit of novelty and differentiation due to its nature.

Keywords

Acknowledgement

Funding for this paper was provided by Namseoul University year 2023

References

  1. H. Gardner, The mind's new science: A history of the cognitive revolution, NY, US: Basic Books, pp. 28-45, 1985
  2. Bechtel & Graham, A Companion to Cognitive Science, Blackwell Publishing Ltd., pp. 1-98, 1998
  3. J. M. Lee, Cognitive Psychology, Hakjisa, pp. 171-172, 2002
  4. N. Wiener, Cybernetics, Second Edition: or the Control and Communication in the Animal and the Machine, MIT, p. 181, 1948
  5. H. A. Simon, Studying human intelligence by creating artificial intelligence, American Scientist, Vol. 69, No. 3, 300-309, 1981
  6. J. M. Lee, Cognitive Psychology, Hakjisa, pp. 193-195, 2002
  7. S. Johnson, Emergence: The Connected Lives of Ants, Brains, Cities, and Software, Gimm-young Publishers, p. 71, 2004
  8. Y. Liang, M. Zhang, W. N. Browne, Image feature selection using genetic programming for figure-ground segmentation, Engineering Applications of Artificial Intelligence, Vol. 62, pp. 96-108, 2017
  9. Tao Xu, De Cheng, Yuanjun Zhao, Jinglong Zhang, Gang Chen, Yang Wang, Xiufeng Yan, Gavin P. Robertson, Shobhan Gaddameedhi, Philip Lazarus, Shuwen Wang, and Jiyue Zhu. Polymorphic tandem DNA repeats activate the human telomerase reverse transcriptase gene, Proceedings of the National Academy of Sciences. Vol. 118, No. 26, pp. 1-11, 2021.
  10. R. Sebastian, https://sebastianrisi.com/self_assembling_ai/, 2024
  11. J. Wagemans, J. Feldman, S. Gepshtein, R.Kimchi, J. R. Pomerantz, P. A. van der Helm, & C. van Leeuwen, A century of Gestalt psychology in visual perception: II. Conceptual and theoretical foundations, Psychological Bulletin, Vol. 138, No. 6, pp. 1218-1252, 2012.
  12. P. Schmalbrock & C. Frings, A mighty tool not only in perception: Figure-ground mechanisms control binding and retrieval alike, Attention, Perception, & Psychophysics, Vol. 84, No.7, pp. 2255-2270, 2022.
  13. Reinke, C., Etcheverry, M., & Oudeyer, P. Y. Intrinsically motivated discovery of diverse patterns in self-organizing systems, International Conference on Learning Representations, 2019
  14. S. J. Lee, The relation between Movement working as a Grouping clue in Moving Picture and Semantic structure forming, Archives of Design Research, Vol. 19, No. 5, pp. 119-128, 2006
  15. M. Rubenstein, A. Cornejo, & R. Nagpal, Programmable self-assembly in a thousand-robot swarm, Science, Vol. 345, No. 6198, pp. 795-799, 2014
  16. S. J. Lee, Study on the reception process and sharing of design creativity : focusing on the survey of poster design between the professional and non-professional, Doctoral Dissertation. University of Hongik, Seoul, South Korea, 2019.