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Social response of European art communities to the Artificially Generated Art

Работа №143832

Тип работы

Бакалаврская работа

Предмет

искусство, культура, литература

Объем работы68
Год сдачи2023
Стоимость4640 руб.
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Chapter 1. Theoretical basis for social analysis 3
Introduction 3
1.1 History of AI Art 5
1.2 Theoretical review 10
1.3 General literature review 16
1.4 Chosen tools and methodology for analysis 19
1.4.1 The semi-structured “insider” interview 20
1.4.2 Forum Analysis 21
Chapter 2: Gathering the Data for analysis 23
2.1 Developing the questions for semi-structured interview 23
2.2 Semi-Structured interview 1 26
2.3 Semi-Structured interview 2 28
2.4 Semi-Structured interview 3 30
2.5 Overarching themes 32
2.6 Forum analysis 34
Chapter 3 Summary and Conclusions 41
3.1 Summing up the gathered data 41
3.2 Conclusion 46
Bibliography 47
Questions for Semi-Structured interview 54
Semi-Structured Interview 1 55
Semi-Structured Interview 2 59
Semi-Structured Interview 3 62
List of analysed discussions: 66

In recent years, advancements in artificial intelligence (AI) have permeated numerous industries, revolutionizing the way we approach various aspects of our lives. One such area deeply impacted by AI's growing influence is the artistic realm. With the advent of Generative Adversarial Networks (GANs) and other advanced algorithms, machines are now capable of creating aesthetically pleasing and thought-provoking pieces of art without human intervention. The subject of my research is the social response of the European art community.
Throughout history, the contemplation of artistic creation has been intricately linked to human ingenuity and creativity. Artists have always sought to express their perspectives on the world through their unique interpretation of emotions, experiences, and ideologies. As artificial intelligence becomes increasingly capable of imitating this delicate process, it raises concerns and challenges long-held beliefs regarding artistic expression and authenticity.
The response of the art community to artificially generated art has been multi-faceted and reflective of the wide range of opinions present within this diverse and dynamic field. Some artists and critics perceive AI-generated art as a threat, fearing it could render human involvement and creativity obsolete. They argue that true artistic endeavors stem from human emotions, experiences, and the complexities of the human condition, which machines lack the ability to genuinely replicate.
On the other hand, a significant portion of the art community views the rise of AI-generated art as an exciting avenue for exploration and creative collaboration. They contend that machines can serve as co-creators, augmenting human artistic expression and pushing the boundaries of traditional creativity. These proponents suggest that AI-generated art can act as a tool for artists, providing them with new perspectives, novel techniques, and a fresh source of inspiration.
Additionally, the art community's response to AI-generated art is not limited to the debate over human versus machine creation. There is also a growing interest in examining the societal implications and ethical considerations associated with this amalgamation of art and technology. Questions regarding authorship, originality, and the potential for mass production and replication have sparked conversations on the value and marketability of AI-generated artwork.
As we delve deeper into the response of the art community to artificially generated art, it becomes evident that this emerging field is at a crossroads. Whether it inspires awe or raises doubts, AI's impact on artistic creation is undeniable. By exploring the diverse perspectives within the art community and the questions arising from this collision of art and technology, we can gain a nuanced understanding of the implications and possibilities that AI will continue to bring to the artistic landscape.
In my master thesis I'm aiming to explore social response to AI generated art. Find any correlations between knowledge, usage of the technology and critical opinions. Analyze large amounts of data from the public forums and interviews to draw any conclusions about reactionary nature to the emerging technology.
Objectives of my research:
1. To characterize the technology and its disruptive nature
2. Pinpoint the most crucial topics within the debate and gather data on each of them within the public debate
3. Provide an extended overview of the current sentiment of the art community on the topic of AI Art.

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The novelty of the discussion and ongoing developments in the technology of the AI were major hurdles in this research. The importance of the topic for the industry and lack of scientific publications in this field presented the necessity for development of the research tools and research guidelines.
The research reached all of the set goals:
1) The technology and main points of the discussion were described as well as both of the opposing views of the argument.
2) Interviews with the insiders from the field helped to gather additional information and insights as well as help to develop some of the research tools needed for data analysis. Separating overall discussion into main points of interest
3) Data analysis was performed - on which the conclusions and opinions are based on. Adequate amount of data was gathered to draw such conclusions.
The opinions of the European Art Community had clear tendencies and the statistics highlight the complex interplay between rational discourse and emotional sentiment in the debate on AI art, emphasizing the need for a nuanced understanding of both perspectives. Whilst highlighting the emotional argumentation against the AI Art even with the dominating sentiment of opposition to integration of the technology into community in general.


1. The First A.I.-Generated Art Dates Back to the 1970s. Katya Cengel URL: https://www.smithsonianmag.com/innovation/first-ai-generated-art-dates-back-t o-1970s-180983700/
2. Female Iconoclasts: Vera Molnar, Pioneer of Early Computer and Generative Art. Adam Hencz URL: https://magazine.artland.com/vera-molnar/
3. Machine Learning Steps: A Complete Guide. Mayank Banoula URL: https://www.simplilearn.com/tutorials/machine-learning-tutorial/machine-learni ng-steps
4. HAROLD COHEN: AARON FEB 3-MAY 19, 2024. URL: https://whitney. org/exhibitions/harold-cohen-aaron
5. Inceptionism: Going Deeper into Neural Networks. Alexander Mordvintsev URL: https://research.google/blog/inceptionism-going-deeper-into-neural-networks/
6. THE NEXT REMBRANDT. J. Walter Thompson Amsterdam URL: https://dublin.sciencegallery.com/humans-need-not-apply-exhibits/the-next-rembrandt
7. Un portrait« peint » par une IA en vente aux encheres. Brice Louvet URL: https://sciencepost.fr/un-portrait-peint-par-une-ia-en-vente-aux-encheres/
8. The History and Evolution of PyTorch. URL: https://tensorgym.com/blog/pytorch-history
9. Montevirgen, K. (2024, June 4). OpenAI. Encyclopedia Britannica. https://www.britannica. com/money/OpenAI
10. Katherine Crowson URL: https://kath.io/
11. A Comprehensive History And Explanation of OpenAI’s DALL-E. Filip Julian MiszukURL: https://techbehemoths.com/blog/dall-e-history
12. Global Deepfake Epidemic Worsening Amid Elections - UK Seventh Most Targeted Nation. URL: https://www.prnewswire.com/news-releases/global-deepfake-epidemic-worsenin g-amid-elections—uk-seventh-most-targeted-nation-302159002.html
13. Responses to new technology: A model for future research. Edward J. O'Connor. URL: https://www.sciencedirect.com/science/article/abs/pii/104783109290007
14. Carley, Kathleen M. 1989. “The Value of Cognitive Foundations for Dynamic Social Theory.” The Journal of Mathematical Sociology 14: 171-208.
15. Carley, Kathleen M. 1989. “The Value of Cognitive Foundations for Dynamic Social Theory.” The Journal of Mathematical Sociology 14: 171-208...(61)


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