Author: Viktoriya Pisotska, PhD


In recent times, the conversation surrounding the influence of digital technologies on creative industries has gained momentum, emphasizing the significance of digital platforms and the emergence of digital ownership via NFTs (Chalmers et al 2022), a trend amplified by the COVID-19 pandemic (Khlystova et al., 2022). The discussion has evolved to include the critical role of artificial intelligence (AI) in creative industries, a sector where the definition of creativity within the AI context remains a subject of debate.


This article examines the creative industries, defined as activities that originate from individual creativity, skill, and talent and have the potential for wealth and job creation through the generation and exploitation of intellectual property (DCMS, 2001). The distinctive nature and ways of working of this sector render it particularly susceptible to profound changes and innovations propelled by generative AI (Hong et al., 2014), with a vast impact on economies and societies (Campbell et al., 2022, Dwivedi et al., 2023b). A comprehensive understanding of the interplay between generative AI and creative industries is crucial for leveraging potential benefits, addressing emerging challenges of these industries and beyond (Amankwah-Amoah, 2024).


The objective of this concise article is to stimulate inquiry and critical analysis among scholars and practitioners regarding AI’s ramifications for creative industries, their artists, as well as to discuss AI’s broader societal implications. It endeavors to initiate a dialogue by posing fundamental questions aimed at unraveling the nuances of creativity in the AI milieu. These inquiries include: How should we redefine creativity in the age of AI? Who qualifies as creative in this new context? How can one differentiate between artworks solely created by humans and those partially or entirely produced by AI? In what ways can AI tools enhance the creativity and productivity of artists? What competencies will be essential for artists in an AI-evolving landscape? Moreover, what strategies can artists employ to safeguard their creations, assert ownership, and what ethical guidelines should govern AI’s application in the creative sectors?


Research on AI commenced in the mid-20th century. The term “artificial intelligence” was first introduced in 1956 during the Dartmouth Conference, where a consortium of researchers convened to explore the feasibility of creating machines capable of demonstrating human-like intelligence. Since that time, AI research has advanced substantially, with significant developments across various subfields, including machine learning, natural language processing, computer vision, and robotics. However, the adoption of AI applications has been gradual (Allam & Dhunny, 2019). An intriguing trend is highlighted by an analysis from Google Trends (Fig. 1), which illustrates a decrease in AI interest from early 2004 to 2008, followed by a notable resurgence in AI’s popularity from 2014 to 2024 (Google Trends, 2024).


Fig.1: Popularity of AI from 2004 to 2024 (Google Trends, 2024).


In the realm of creative industries, a growing number of scholars (e.g., Anantrasirichai & Bull, 2022) have recently begun to explore the application of AI in this sector. One of the limitations in the past was the readiness of the technology itself. Researchers (e.g., Davies et al., 2020) have suggested that the growth rate of research publications on AI, particularly those pertinent to creative industries, has increased by more than 500% in numerous countries. Predominantly, these studies have focused on AI’s application in creative industries (Anantrasirichai & Bull, 2022), the related challenges (De Cock Buning, 2018), and discussions about creativity (Lee, 2022). A recent survey conducted by Adobe (2018) revealed that three-quarters of artists in the US, UK, Germany, and Japan would consider using AI tools to assist in tasks like image search, editing, and other ‘non-creative’ activities. This demonstrates a widespread acceptance of AI as a supportive tool within the community and indicates a general awareness of the current state of technology, as most AI technologies are designed to operate in specific domains where they assist and support human efforts rather than replace them. Remarkably, the first painting created entirely by AI was auctioned for $432,500 in 2018 (The New York Times). Despite the growing interest in the intersection of AI and creative industries, this area of research remains nascent, with many questions yet to be addressed.


One pressing question is: how, and if, should we redefine creativity in the age of AI? Lee (2022) argues that AI holds the potential to re-humanize the notion of creativity, which has been increasingly perceived through a dehumanized lens due to the prevailing discourse within creative industries over the last two decades. Lee suggests that the industry’s characterization of creativity as a form of capital obstructs a labor-centric view of creativity. Explorations into AI and creativity probe the intrinsic nature of human creativity and the artistic process, while also recognizing the potential challenge AI poses to human creators by detaching creativity from human agency. Thus, the discussion surrounding AI and creativity in the context of creative industries invites critical examination of the political-economic aspects of creativity (labor vs. capital) and the source of creativity (humans/artists vs. mechanical processes/capital).


Regarding the question of whether we will be able to distinguish between artworks entirely created by humans and those that are partially or entirely generated by AI, current research does not provide a definitive answer. As AI technology advances, producing increasingly sophisticated and human-like creations, this task will undoubtedly become more challenging. Several methods could potentially differentiate between the two. Firstly, artists can disclose whether their works are AI-assisted or solely human-made, although this depends on the creator’s honesty and transparency. Appropriate software could identify AI-generated artworks. Techniques such as forensic analysis, artistic style analysis, and expert critique can be employed to detect subtle patterns or ‘fingerprints’ in AI-generated images, identify the human touch in art, and involve art critics and experts in differentiating between human and AI-generated creations. However, these analyses may become more difficult as AI evolves. Consequently, there is a need to establish legal standards mandating the disclosure of AI usage in creative works.


To reflect on how AI tools can enhance not only an artist’s creativity but also productivity, consider the example of 20th Century Fox. The company employed AI algorithms developed by IBM Watson to analyze movie trailers and predict which elements would most resonate with different target audiences (Forbes, 2024). Furthermore, independent filmmakers and smaller production companies have utilized AI for tasks like script analysis, video editing, and even composing music scores. Although AI has not reached the capability to independently produce entire films, it has been incorporated into the filmmaking process, streamlining certain tasks and boosting creativity and efficiency.


Regarding the necessary skills, insights can be gleaned from artists who are already integrating AI into their creative work. For instance, Hans Zimmer, a celebrated composer known for his scores in movies such as “The Lion King,” “Inception,” “Interstellar,” and “Dune”, has expressed his interest (e.g., in his interview for GQ) in using technology to enhance his creative process and expand the limits of music composition. He identifies essential skills including emotional intelligence—a quality AI lacks—along with creativity, originality, artistic identity and vision, authenticity, and the ability to engage in critical thinking and problem-solving. In Zimmer underscores the importance of striking a balance between technology and human expression, ensuring that technology augments the artistic vision rather than detracting from it.


The impacts of generative AI go beyond creative industries’ boundaries, affecting culture, policy and society (Amankwah-Amoah et al., 2024). Governments worldwide recognize AI as a key driver of economic growth and societal advancement (Hall & Pesenti 2018). A prime example of its application is in the development of smart cities, which leverage Big Data and the Internet of Things (IoT) to boost urban efficiency and the overall workings of city life (Allam & Dhunny, 2019). The advent of digitized cities, equipped with an array of sensors, computational cores, and diverse telecommunication networks, has unlocked the potential to collate extensive data from various neighborhoods about how people in cities live, and how cities evolve over a certain period of time. It is possible to obtain data about land spaces, open spaces, buildings and such. This data acquisition can enable a more comprehensive and nuanced understanding of urban life and the evolving dynamics of city spaces, including the efficient use of land and the interaction within open and built environments (Allam & Dhunny, 2019). When such data is processed through AI systems it illuminates aspects of urban logistics and informs the decision-making processes of urban planners, fostering more effective governance and policy-making that align with the needs and well-being of urban residents. Moreover, AI can be instrumental in shaping urban policies that address and mitigate the impacts of climate change—recognizing the critical importance of developing resilient and sustainable cities for future generations. Yet, despite these optimistic strides, concerns regarding privacy breaches and the overarching social implications of AI remain salient issues requiring further scholarly investigation and ethical deliberation (Jha et al., 2021; Yigitcanlar et al., 2020; Anantrasirichai, Bull, 2022). While generative AI is here to stay (Dwivedi, 2023a), it is imperative to critically reflect on its congruence with societal and cultural norms and to contemplate the ethical implications for those involved. As we journey forward, ensuring that innovation and technology enhance, rather than overshadow, the human touch in our creative tapestry is imperative. In essence, actively managing the creative process and directing AI’s evolution, rather than merely consuming it, will become increasingly important. At the time of writing this article, several questions remain open to interpretation, not least of which is the query of whether AI has crafted this text.






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