Generative AI and Its Impact on Creative Industries

By: Ameya Sree Kasa, Department of Computer Science & Engineering (Artificial Intelligence), Madanapalle Institute of Technology & Science, Angallu (517325), Andhra Pradesh. ameyasreekasa@gmail.com

Abstract:

Explorative AI, one of the subcategories under artificial intelligence that involves procedures such as algorithms and machine learning to bring out new concepts, is transforming creative markets by giving fresh ways in the development of content. Moving into the technical part of this article, it examines generative AI in depth and how it applies to art, music, literature, and design. This discusses how deep learning produced artifacts are revolutionizing the traditional creative procedures, changing the industry, and influencing the creativity of artistic practice. The discussion is used to introduce the positive implications of the emergence of generative AI for creativity and practical work, and critical points, which are the ethical issues for AI-based creative work and the shift in roles in the creative industries. At the same time, the article offers the prognosis of the further development of generative AI and its potential impact on the creative industry in the long term, thus, it provides valuable information about the further advancements in the sphere of highly innovative AI area.

Keywords: Generative AI, Creative Industries, AI-Generated Content

1. Introduction:

Generative AI can be understood as a remarkable advancement in growing the application of Artificial Intelligence since it provides devices the capability of creating original content based on the parsed and learned data. In the creative industries, it is a revolutionizing technology that drastically changes the processes of producing art, music, literature, and designing. With the help of such a smart processing as generative AI which creates new and unique works, new types of tools allowing for encouraging and developing creativity are introduced. This article focuses on the shift through generative AI that a variety of creative fields undertake in this article the author discusses changes in methods and practices. In addition, it discusses the prospects for further developments of creativity and IP in the future, again drawing both the positive potential of new modes of creative action and the potential difficulties in defining originality and ownership.

2. Generative AI:

Generative AI can be defined as a novel evolution in the application of AI and entails a capability that allows a system to come up with its content through learning from large amounts of data. Unlike other AI machines, generative AI is based on computations with the assistance of several algorithms to produce new outputs, apart from arts, music, literature, and designs. [1] Whereas traditional AI simply executes tasks predefined by an end-user, generative AI can run in an unsupervised manner and come up with totally new ideas for artwork, composition, designs, and many other things, opening up completely new ways for creativity and innovation. Composing music or generating photorealistic images, writing text, and designing products, the uses are endless. In this way, generative AI brings innovations to creative processes and, with increased efficiency, also opens up some serious challenges in terms of authorship, originality, and other ethical questions about machine creativity. [2]

3. Why Generative AI?

Generative AI must, therefore, be important because it ensures that the boundaries of creativity and automation are usually pushed to the limit by enabling machines to actually create new content based on learned patterns of data. [3]

4. Role of Generative AI on creative Industries:

They are relatively new, and are rapidly defining the nature of creative industries by changing content generation, customization and novelty. Generative AI is changing the way content is ideated, created, and consumed, especially in creative industries. [4] This helps creatives to bring forth original art, music, and literature through the use of the underlying algorithms in the resultant styles, melodies, and narratives. It provides personalization in a marketing campaign by generating unique relevant content to provide innovative combinations and ideas. [5] Generative AI can automate tasks, hence easing the actual load of work to a point that creative professionals can move up to work on higher-level issues. In this way, it democratizes creativity and participation in the field of art by lowering the barrier to entry. However, it also raises important ethical and legal issues with respect to issues of authorship and intellectual property. Generative AI, as it keeps evolving, has started showing much greater features to generate and apply advancement further, requiring the creative field to be redefined. [6]

5. Challenges & Concerns:

Generative AI has brought exciting new opportunities to the creative industries, providing artists, writers, musicians, and other creators with innovative tools. However, this technology also presents several challenges and concerns like mentioned in the figure 2 below. [7]

6. Future Directions:

The future for generative artificial intelligence in creative industries is untenable, with transformational improvements in the offing that will redefine how art, writing, music, and all other forms of creativity are done. With still more powerful tools at our disposal to unleash creativity, highly customized and subtle outputs become conceivable. It is expected that AI will foster collaborative settings, matching human creators with a combination of intuition and computational muscle. [8] Content creation will be much more sophisticated, allowing interactivity and immersion. More focus will be put into actually handling the bias and making AI-created content more inclusive. [9] More ethical and more transparent AI systems at the core of accountability and responsible usage. AI’s important role in education will be to provide really bespoke feedback that helps aspiring creators. [10]Integrated possibilities with AR and VR will open new creative avenues, and evolving copyright models will work to sort out the complications of AI-generated works. As it begins to find its bearings, the AI technology will democratize creative tools, placing new capability into the hands of more people, better positioned for exploration and innovation. The way in which such an approach is taken toward these developments will be important in pushing the potential of AI while negotiating its difficulties. [11]

7. Conclusion:

Generative AI will transform creative industries by improving the tools required for artistic expression, enabling real-time collaboration between humans and AI, and further personalization and immersion of content. With advances in AI technology, it will enhance efforts to reduce bias and promote inclusivity while emphasizing ethical and transparent practices. Integrate AI with AR and VR to unleash new creative vistas, and evolving copyright frameworks will treat the emerging complexities. With broader access to AI tools, creativity becomes democratized. Thoughtful adoption of these innovations will be in a position to fully capture the potential of AI and meet challenges against its application effectively.

8. References:

1. P. Pappachan, Sreerakuvandana, and M. Rahaman, “Conceptualising the Role of Intellectual Property and Ethical Behaviour in Artificial Intelligence,” in Handbook of Research on AI and ML for Intelligent Machines and Systems, IGI Global, 2024, pp. 1–26. doi: 10.4018/978-1-6684-9999-3.ch001.
2. S. Feuerriegel, J. Hartmann, C. Janiesch, and P. Zschech, “Generative AI,” Bus. Inf. Syst. Eng., vol. 66, no. 1, pp. 111–126, Feb. 2024, doi: 10.1007/s12599-023-00834-7.
3. A. Bhutoria, “Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model,” Comput. Educ. Artif. Intell., vol. 3, p. 100068, Jan. 2022, doi: 10.1016/j.caeai.2022.100068.
4. M. Moslehpour, K. Y. Chau, Y.-T. Tu, K.-L. Nguyen, M. Barry, and K. D. Reddy, “Impact of corporate sustainable practices, government initiative, technology usage, and organizational culture on automobile industry sustainable performance,” Environ. Sci. Pollut. Res. Int., vol. 29, no. 55, pp. 83907–83920, Nov. 2022, doi: 10.1007/s11356-022-21591-2.
5. A. Nyalapelli, S. Sharma, P. Phadnis, M. Patil, and A. Tandle, “Recent Advancements in Applications of Artificial Intelligence and Machine Learning for 5G Technology: A Review,” in 2023 2nd International Conference on Paradigm Shifts in Communications Embedded Systems, Machine Learning and Signal Processing (PCEMS), Apr. 2023, pp. 1–8. doi: 10.1109/PCEMS58491.2023.10136039.
6. J. Amankwah-Amoah, S. Abdalla, E. Mogaji, A. Elbanna, and Y. K. Dwivedi, “The impending disruption of creative industries by generative AI: Opportunities, challenges, and research agenda,” Int. J. Inf. Manag., vol. 79, p. 102759, Dec. 2024, doi: 10.1016/j.ijinfomgt.2024.102759.
7. A. Golda et al., “Privacy and Security Concerns in Generative AI: A Comprehensive Survey,” IEEE Access, vol. 12, pp. 48126–48144, 2024, doi: 10.1109/ACCESS.2024.3381611.
8. M. Markevych and M. Dawson, “A Review of Enhancing Intrusion Detection Systems for Cybersecurity Using Artificial Intelligence (AI),” Int. Conf. Knowl.-BASED Organ., vol. 29, no. 3, pp. 30–37, Jun. 2023, doi: 10.2478/kbo-2023-0072.
9. A.-V. Andriu, “Adaptive Phishing Detection: Harnessing the Power of Artificial Intelligence for Enhanced Email Security,” Romanian Cyber Secur. J., vol. 5, no. 1, pp. 3–9, May 2023, doi: 10.54851/v5i1y202301.
10. M. Rahaman, B. Chappu, N. Anwar, and P. K. Hadi, “Analysis of Attacks on Private Cloud Computing Services that Implicate Denial of Services (DoS),” vol. 4, 2022.
11. B. Ramdurai, The Impact, Advancements and Applications of Generative AI. 2023.
12. Gupta, B. B., & Panigrahi, P. K. (2022). Analysis of the Role of Global Information Management in Advanced Decision Support Systems (DSS) for Sustainable Development. Journal of Global Information Management (JGIM), 31(2), 1-13.
13. Gupta, B. B., & Narayan, S. (2021). A key-based mutual authentication framework for mobile contactless payment system using authentication server. Journal of Organizational and End User Computing (JOEUC), 33(2), 1-16.
14. Gupta, B. B., & Narayan, S. (2021). A key-based mutual authentication framework for mobile contactless payment system using authentication server. Journal of Organizational and End User Computing (JOEUC), 33(2), 1-16.

Cite As

Kasa A.S. (2024) Generative AI and Its Impact on Creative Industries, Insights2Techinfo, pp.1

753600cookie-checkGenerative AI and Its Impact on Creative Industriesyes