research-article

The Impact of Artificial Intelligence on the Creativity of Videos

Authors:

Ana Daniela Peres Rebelo,

Guedes De Oliveira Inês,

D. E. Verboom DamionAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 18, Issue 1

Article No.: 9, Pages 1 - 27

https://doi.org/10.1145/3462634

Published: 27 January 2022 Publication History

Abstract

This study explored the impact Artificial Intelligence (AI) has on the evaluation of creative elements in artistic videos. The aim was to verify to what extent the use of an AI algorithm (Style Transfer) contributes to changes in the perceived creativity of the videos. Creativity was evaluated in six quantitative items (Likert-type scale) and one qualitative question (qualitative description of the creativity expressed in the video by two words or expressions). Six videos were shown to both control (N = 49) and experimental group (N = 52) aiming at determining possible differences in creativity assessment criteria. Furthermore, both groups contained experts (Experimental, N = 27; Control, N = 25) and non-experts (Experimental, N = 25; Control, N = 24). The first round of videos composed of six videos that were the same for both the experimental and control condition (used to check for bias). No significant differences were found. In a second round, six videos were shown with AI transformation (experimental condition) and without that transformation (control group). Results showed that in two cases the perceived creativity increased in experimental condition, in one case a decrease occurred. In most evaluations no differences were observed. Qualitative evaluations reinforce the absence of a general pattern of improvements in AI transformations. Altogether, the results emphasize the importance of human mediation in the application of AI in creative production: a hybrid approach, or rather, Hybrid Intelligence.

References

[1]

Teresa M. Amabile. 1982. Social psychology of creativity: A consensual assessment technique. 43:997–1013, 1982. DOI:

[2]

Blaise A. Arcas. 2017. Art in the age of machine intelligence. Arts 6, 4 (2017), 18. DOI:

[3]

Richard A. Armstrong. 2014. When to use Bonferroni correction. Ophthalmic and Physiological Optics 34, 5 (2014), 502–508. DOI:

[4]

Sofian Audry and Jon Ippolito. 2019. Can artificial intelligence make art without artists? ask the viewer. Arts 8, 1 (2019), 35. DOI:

[5]

Melissa Avdeeff. 2019. Artificial intelligence & popular music: Skygge, flow machines, and the audio uncanny valley. Arts 8, 4 (2019), 130. DOI:

[6]

Nuno Barbosa. 2011. Moby - “Be The One”. Video. (2011). April 10, 2020 from https://vimeo.com/23435653.

[7]

Nuno Barbosa. 2011. Junip - “Without You”. Video. (2011). April 10, 2020 from https://vimeo.com/27365453.

[8]

Nuno Barbosa. 2012. Rouge - "Li Azul". Video. (2012). April 10, 2020 from https://vimeo.com/31365267.

[9]

Nuno Barbosa. 2012. MAGNOLIUS - “Selaron”. Video. (2012). April 10, 2020 from https://vimeo.com/40001143.

[10]

Nuno Barbosa. 2013. Souq - “Desert Snake Catcher”. Video. (2013). April 10, 2020 from https://vimeo.com/63415960.

[11]

Nuno Barbosa. 2013. Algodão - “Eu não sei quando te perdi”. Video. (2013). April 10, 2020 from https://vimeo.com/53332710.

[12]

Nuno Barbosa. 2013. Amplifying Creativity. Video. (2013). April 10, 2020 from https://vimeo.com/195623736.

[13]

Nuno Barbosa. 2014. Emmy Curl - March for Peace. Video. (2014). April 10, 2020 from https://vimeo.com/213043420.

[14]

Nuno Barbosa. 2015. Emmy Curl - “Come Closer”. Video. (2015). April 10, 2020 from https://vimeo.com/113000956.

[15]

Nuno Barbosa. 2018. Quattuor Elementa. Video. (2018). April 10, 2020 from https://vimeo.com/248511661.

[16]

Nuno Barbosa. 2018. Júlio Resende - “Fado Cyborg”. Video. (2018). April 10, 2020 from https://vimeo.com/281950030.

[17]

Nuno Barbosa. 2019. Júlio Resende - “Let's go to the Moon again”. Video. (2019). April 10, 2020 from https://vimeo.com/344976038.

[18]

Marcus Basalla and Johannes Schneider. 2020. Creativity of deep learning: Conceptualization and assessment. 2020. arXiv: 2012.02282

[19]

Phillip A. Bishop and Robert L. Herron. 2015. Use and misuse of the Likert item responses and other ordinal measures. International Journal of Exercise Science 8, 3 (2015), 297–302. 27182418

[20]

Margaret Ann Boden. 2009. Computer models of creativity. AI Magazine 30, 3 (2009), 23–34. DOI:

Digital Library

[21]

Amaresh Chakrabarti and Prabir Sarkar. 2015. Creativity: Generic definition, tests, factors and methods. International Journal of Design Sciences and Technology 21, 1 (2015), 7–37.

[22]

Liuqing Chen, Pan Wand, Hao Dong, Feng Shi, Ji Han, Yike Guo, Peter R. N. Childs, Jun Xiao, and Chao Wu. 2019. An artificial intelligence based data-driven approach for design ideation. Journal of Visual Communication and Image Representation 61 (2019), 10–22. DOI:

Digital Library

[23]

Harold Cohen. Driving the creative machine, September 2010. Lecture. http://www.aaronshome.com/aaron/publications/orcastalk2s.pdf.

[24]

Arthur J. Cropley. 2016. Qualitative research methods: an introduction for students of psychology and education. 2016 Jun. https://www.academia.edu/20371271/Qualitative_Research_Methods_An_introduction_for_students_of_psychology_and_education.

[25]

Dominik Dellermann, Philipp Ebel, Matthias Söllner, and Jan M. Leimeister. 2019. Hybrid intelligence. Business & Information Systems Engineering 61, 5 (2019), 637–643. DOI:-

[26]

Melissa J. Dolese. 2015. Art as Communication: Employing Gricean Principles of Communication as a Model for Art Appreciation. PhD thesis, New York, NY, USA, 2015. https://academicworks.cuny.edu/gc_etds/907/.

[27]

Ahmed Elgammal, Bingchen Liu, Mohamed Elhoseiny, and Marian Mazzone. 2017. CAN: Creative adversarial networks, generating "art" by learning about styles and deviating from style norms. 2017. arXiv:1706.07068

[28]

Peter Ellis. 2014. The language of research (part 1): Research paradigms. Wounds UK 10, 2 (2014), 118–119. https://www.wounds-uk.com/journals/issue/38/article-details/the-language-of-research-part-1-research-paradigms.

[29]

Maria Laura Frigotto and Massimo Riccaboni. 2011. A few special cases: Scientific creativity and network dynamics in the field of rare diseases. Scientometric 89, 1 (2011), 397–420. DOI:https://doi.org/10.1007/s11192-011-0431-9

Digital Library

[30]

Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge. 2016. Image style transfer using convolutional neural networks. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 2414–2423, 2016. DOI:

[31]

Danah Henriksen and Punya Mishra. 2014. Twisting knobs and connecting things: Rethinking technology & creativity in the 21st century. Tech Trands 58, 1 (2014), 15–19. DOI:

[32]

Joo-Wha Hong and Nathaniel Ming Curran. 2019. Artificial intelligence, artists, and art: Attitudes toward artwork produced by humans vs. artificial intelligence. ACM Transactions on Multimedia Computing, Communications, and Applications 15, 2s (2019). DOI:https://doi.org/10.1145/3326337

Digital Library

[33]

IBM. 2020. Machine learning, 2020. https://www.ibm.com/analytics/machine-learning.

[34]

Cheng-Bin Jin. 2018. Real-Time Style Transfer. https://github.com/ChengBinJin/Real-time-style-transfer/.

[35]

Yongcheng Jing, Yezhou Yang, Zunlei Feng, Yizhou Ye, and Mingly Song. 2019. Neural style transfer: A review. IEEE Transactions on Visualization and Computer Graphics, pages 1–1, 2019. DOI:

[36]

Joost N. Kok, Egbert J. W. Boers, Walter A. Kosters, Peter Van der Putten, and Mannes Poel. 2009. Artificial Intelligence, chapter Artificial Intelligence: Definition, Trends, Techniques and Cases. Eolss Publishers, Oxford, UK, 2009.

[37]

Chethan Kumar. 2018. Artificial intelligence: Definition, types, examples, technologies, Aug 2018. https://medium.com/@chethankumargn/artificial-intelligence-definition-types-examples-technologies-962ea75c7b9b.

[38]

Nancy L. Leech and Anthony J. Onquegbuzie. 2002. On becoming a pragmatic researcher: The Importance of combining quantitative and qualitative research methodologies. International Journal of Social Research Methodology 8, 5 (2002), 375–387. DOI:

[39]

Nancy L. Leech and Anthony J. Onquegbuzie. 2009. A typology of mixed methods research designs. Quality and Quantity 43, 2 (2009), 265–275. DOI:

[40]

Andy Lomas. 2018. On hybrid creativity. Arts 7, 3 (2018), 25. DOI:

[41]

Mary A. Malina, Hanne S. O. Norreklit, and Frank H. Selto. 2011. Lessons learned: Advantages and disadvantages of mixed method research. Qualitative Research in Accounting & Management 8, 1 (2011), 59–71. DOI:

[42]

Marian Mazzone and Ahmed Elgammal. 2019. Art, creativity, and the potential of artificial intelligence. Arts 8, 1 (2019), 26. DOI:

[43]

Balas K. Natarajan. 1991. Machine Learning: A Theoretical Approach. Morgan Kaufmann, Massachusetts, USA, 1991.

Digital Library

[44]

Stephen Ornes. 2019. Science and culture: Computers take art in new directions, challenging the meaning of creativity. Proceedings of the National Academy of Sciences 116, 11 (2019), 4760–4763. DOI:

[45]

Harold Osborne. 1982. Expressiveness in the arts. The Journal of Aesthetics and Art Criticism 41, 1 (1982), 19–26. http://www.jstor.org/stable/430820.

[46]

Yeonsook Park. 2019. Can artworks by artificial intelligence be artworks? AM Journal of Art and Media Studies 20 (2019), 113–121. DOI:

[47]

Simon J. D. Prince. 2012. Computer Vision: Models, Learning, and Inference. Cambridge University Press, Cambridge, UK, 2012.

Digital Library

[48]

Mark A. Runco and Garrett J. Jaeger. 2012. The standard definition of creativity. Creativity Research Journal 24, 1 (2012), 92–96. DOI:

[49]

Shai Shalev-Shwartz and Shai Ben-David. 2014. Understanding Machine Learning: From Theory to Algorithms. Cambridge University Press, London, UK, 2014.

Digital Library

[50]

Richard Szeliski. 2011. Computer Vision: Algorithms and Applications. Springer, Cambridge, UK, 2011.

Digital Library

[51]

Simon P. Taylor. 2017. What is innovation? A study of the definitions, academic models and applicability of innovation to an example of social housing in England. Open Journal of Social Sciences 5, 11 (2017), 128–146. DOI:

[52]

Chetan Walia. 2019. A dynamic definition of creativity. Creativity Research Journal 31, 3 (2019), 237–247. DOI:

[53]

Yingxu Wang. 2009. On abstract intelligence: Toward a unifying theory of natural, artificial, machinable, and computational intelligence. International Journal of Software Science and Computational Intelligence 1, 1 (2009), 1–17. DOI:

[54]

Joost C. F. de Winter and Dimitra Dodou. 2010. Five-point Likert items: T test versus Mann-Whitney-Wilcoxon. Practical Assessment, Research, and Evaluation 15, 1 (2010), 11. DOI:

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Index Terms

The Impact of Artificial Intelligence on the Creativity of Videos
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Computer graphics

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Published In

cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 18, Issue 1

January 2022

517 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/3505205

Editor:
Alberto Del Bimbo
University of Firenze, Italy

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Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 January 2022

Accepted: 01 April 2021

Revised: 01 March 2021

Received: 01 August 2020

Published in TOMM Volume 18, Issue 1

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Gu CJia SLai JChen RChang X(2024)Exploring Consumer Acceptance of AI-Generated Advertisements: From the Perspectives of Perceived Eeriness and Perceived IntelligenceJournal of Theoretical and Applied Electronic Commerce Research10.3390/jtaer1903010819:3(2218-2238)Online publication date: 3-Sep-2024
https://doi.org/10.3390/jtaer19030108
Chen LSong YSun LChilds PYin Y(2024)Development of an exploratory creativity assessment scaleInternational Journal of Design Creativity and Innovation10.1080/21650349.2024.231977212:2(101-117)Online publication date: 3-Mar-2024
https://doi.org/10.1080/21650349.2024.2319772
Al-Zahrani A(2024)Unveiling the shadows: Beyond the hype of AI in educationHeliyon10.1016/j.heliyon.2024.e3069610:9(e30696)Online publication date: May-2024
https://doi.org/10.1016/j.heliyon.2024.e30696
Hou GWang X(2024)Emotional valence and arousal: the impact of AI-generated image stimuli on design creativityInternational Journal of Technology and Design Education10.1007/s10798-024-09941-2Online publication date: 21-Oct-2024
https://doi.org/10.1007/s10798-024-09941-2
Le TChen YLee T(2023)Structure-aware Video Style Transfer with Map ArtACM Transactions on Multimedia Computing, Communications, and Applications10.1145/357203019:3s(1-25)Online publication date: 24-Feb-2023
https://dl.acm.org/doi/10.1145/3572030

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