As the latest stage of the digitization of the productive sector, the Fourth Industrial Revolution is changing the way people go about their daily lives, perform tasks, and interact with one another. Among the many technologies leading the way in this new era, artificial intelligence (AI) stands out. Meant to replicate the intelligence of human beings and the duties associated with it, AI has found its way into various industries, including the phones used in everyday life. However, though AI applications are incredibly convenient, controversy still surrounds them, with the latest issue being the use of AI within the creative industry. Based on the premise that creativity is a uniquely human trait, accusations that AI is killing innovation are on the rise. However, before accepting these claims at face value, one must look at the far more complex relationship between creativity and AI, as well as the opportunities they present.
AI has undergone remarkable advancements, deeply embedding itself in a diverse range of domains. Powered by machine learning (ML), particularly deep learning, AI has revolutionized fields such as healthcare, finance, and transportation. Notably, the creative industry has experienced an intriguing transformation due to AI integration, with AI-generated art, music, and literature challenging conventional notions of creativity. Tools like deep neural networks (DNNs) enable the creation of novel artworks, compositions, and stories. Yet, what is particularly impressive is the rapid standardization of these AI platforms. Anyone can make use of AI software such as DALL-E 2, Magenta, and ChatGPT, to explore and create works of art; even professionals use them to streamline design processes and generate new ideas.
Nevertheless, the democratization of AI has been met with considerable criticism and debate over the authenticity of its creativity. Most concerns revolve around the claim that AI-generated work is merely a mimicry of pre-existing work presented in a slightly different manner from the original pieces. Further fueled by concerns of potential job displacement, artists feel as though their work is undermined, threatening not only their livelihood but also the future of true innovation.
Creativity — A Multifaceted Concept
A highly complex concept , creativity is difficult to define, though a number of people have tried. The field of psychology is overrun with studies and attempts to understand the creative process, with the general consensus being that, in its most basic form, creativity involves the development of new and original ideas. While this definition would seem rather intuitive and selfexplanatory, some take issue with the use of the word “original” and its interpretation. American psychologist Keith Sawyer is one such person. In his book Explaining Creativity: The Science of Human Innovation, Sawyer criticizes what he perceives to be a mistaken, Western-influenced perception of creativity that forbids any form of imitation because he believes creativity relies on preceding efforts to build the foundation for new ideas. In an interview with Professor Sung Changwon (Department of Philosophy), he expressed a similar opinion that, even though creativity does not involve the creation of something that did not exist before, this definition can be – and often is – aligned with a process of learning and imitation of existing knowledge, making creativity a result of emulation.
Following a similar line of thought, Margaret Boden, a Research Professor of cognitive sciences at the University of Sussex, proposes that there are three types of creativity: combinational, exploratory, and transformational. Of these, only transformational creativity involves the development of completely original work, whereas the first two require some influence and imitation of previous ideas. In addition to looking at the end product, analyzing the underlying factors influencing creativity is equally important in identifying whether creative thought has occurred. To that end, Harvard Professor Teresa M. Amabile’s componential theory of creativity identifies the main factors affecting one’s ability to be creative. Initially, rational elements such as field expertise and cognitive processes involving pattern recognition, divergent thinking, and conceptual blending play a critical role in the formation of a new idea. Furthermore, she points out that the emotional factor of intrinsic motivation is a key to jumpstarting the creative process. This raises the question of whether AI can meet these requirements and display creativity.
Understanding the Capabilities of AI
Before addressing the creative capability of AI, it is necessary to understand the underlying basic technologies that allow AI to mimic human cognition and thus potentially engage in creative thinking. AI has come a long way since its inception, evolving from rule-based systems to more advanced techniques such as ML and DNN. Each phase of its development has brought it closer to achieving tasks that were once considered exclusive to human capabilities. In the early stages, AI heavily relied on rule-based systems, which operated based on explicit sets of rules and predefined instructions, where programmers meticulously encoded a series of “if-then” statements to guide the computer’s decision-making processes. While these systems demonstrated logical reasoning, they were limited by their inability to adapt to new situations that deviated from the programmed rules. They lacked the flexibility required to handle complex realworld scenarios, and their success was often dependent on the programmer’s expertise to ensure a comprehensive rule system.
The transition from rule-based systems to ML marked a significant turning point in AI’s evolution; it introduced the concept of computers learning from data rather than being confined to predetermined rulesets. This paradigm shift allowed AI systems to recognize patterns, make predictions, and improve their performance over time. As a subset of ML, deep learning brought AI even closer to simulating human-like cognitive processes. Inspired by the structure of the human brain, deep learning systems use artificial neural networks (ANNs) consisting of interconnected nodes that process and transmit information. Through layers of nodes and weighted connections, these networks can recognize intricate patterns within data. This breakthrough initially revolutionized tasks such as image recognition, language processing, and decision-making. Now, it is being employed by AI content generators to produce pieces of art, writing, and even music.
The Creative Conundrum: Can Machines Truly Create?
Harnessing the power of ANNs, AI produces a wide array of creative outputs, ranging from award-winning art pieces to literature almost indistinguishable from that of a human being. Though each piece of software is unique in terms of the type of content it creates, most AI tools follow a similar process. For example, DALL-E, an AI art generator, first learns from a vast database of existing artworks and identifies common patterns belonging to specific techniques of painting. Following the learning stage, DALL-E can take users’ prompts and apply whichever style it is asked to by making use of the similar features identified within that category. It can also combine multiple techniques and create something entirely new. In this manner, while current AI tools would not meet Boden’s definition of transformational creativity, some do appear to exhibit abilities closely linked to exploratory and combinational creativity. However, as Professor Chung explains, though AI content generators excel in fulfilling certain cognitive aspects of creativity, their lack of consciousness still renders them reliant on human intervention to ensure they remain aligned with the user’s values and judgments.
Thus, AI falls short of capturing the emotional dimension of Amabile’s theory of creativity. More specifically, intrinsic motivation — an internal drive to express thoughts, emotions, and ideas — is not a characteristic found in any AI generator to date. Software such as DALL-E 2 and ChatGPT operate and produce content only when given a prompt and directions by a user who possesses the intrinsic motivation to create something. Furthermore, under these conditions, the user is generally already inspired and with an idea in mind when they use the software, and this idea can rarely be brought to life using only a simple prompt. On the contrary, the creative process is iterative and collaborative. Humans continue to refine, alter, and enhance the generated output, shaping it as many times as it takes to meet their creative vision. This phenomenon illustrates that AI’s role is not that of an autonomous creative entity but rather a conduit through which people can exercise and amplify their own creativity. AI-generated content may be a starting point, but without human intervention, input, and emotional understanding, it may not always produce a truly satisfactory end result.
Elevating Human Creativity
Nowadays, AI is rapidly gaining prominence as a potent force capable of elevating human creativity through an evolving synergy between technology and human ingenuity, and it plays an important role in idea generation. Through the ML process, AI adeptly processes vast quantities of data, unraveling intricate patterns quickly and becoming a powerful catalyst for sparking unique concepts. By rapidly proposing unconventional ideas and uncovering connections between seemingly disparate elements, AI has become a launchpad for creative thinking.
This dynamic interplay between AI-generated suggestions and human insight fosters innovation, often leading to groundbreaking discoveries that might have otherwise remain hidden. This can be observed through BandLab, a music creating platform with over 60 million users, which uses AI to craft distinctive melodies, harmonies, and rhythms. These AI-generated components stimulate musicians while also igniting their creative fervor and urging them to explore innovative musical arrangements. In essence, AI operates as an amplifier that expansively broadens the horizons of human imagination.
Furthermore, AI serves as a valuable tool in challenging the bias of expertise, offering solutions that may not have been contemplated using traditional methods. According to Harvard Business Review , individuals’ prior experiences can restrict their ability to explore fresh problem-solving avenues, leading to a phenomenon known as the Einstellung effect. These limitations can be overcome by incorporating AI because it prompts individuals with alternative ideas that might have been disregarded. Hence, AI encourages the diversification of creative concepts, leading to unique and innovative approaches to creation.
Ethical Considerations
However, this convergence of human and AI creativity brings forth a profound set of ethical and philosophical issues. As AI takes on a more active role in shaping creative output, questions about authorship and originality are gradually emerging. The distinction between human-generated and AI-assisted work has become blurred, raising concerns about proper attribution and intellectual property rights. Additionally, the essence of creativity and its emotional depth can be debated. Professor Sung stated, “Questions arise about AI’s capability to understand and address unique human concerns and ethical dilemmas, such as the trolley problem.” He further added, “AI inherently lacks consciousness and relies on human intervention to align with human values and ethical judgments.”
Several recent incidents have underscored the importance of delineating the nuanced boundaries between influence, inspiration, and plagiarism in terms of AI-augmented creativity. A case in point is the Colorado State Fair’s fine art competition held on September 5, 2022, where an AI-generated artwork titled “Théâtre D’opéra Spatial,” submitted by Jason Allen, surpassed human-crafted artworks and secured first place. A comment on X (formerly Twitter) by user OmniMorpho, which received over 2,000 likes, stated, “If creative jobs aren’t safe from machines, then even high-skilled jobs are in danger of becoming obsolete.” Despite the controversial outcome, the current legal framework fails to address complex issues such as these. Allen defended his victory by stating “I’m not going to apologize for it. I won, and I didn’t break any rules.”
In the context of “Théâtre D’opéra Spatial,” Professor Kwon Hunyeong (Department of Cyber Security) raised pertinent questions regarding the regulation of AI-generated creations. “In the context of cyber law, most countries define copyright holders as ‘humans’ and artworks as ‘expressions of human thought or emotion.’ Therefore, AI-created works are generally not recognized as eligible for copyright protection,” explained Professor Kwon. He emphasized this point as a key factor explaining how AI-generated creations, such as “Théâtre D’opéra Spatial,” have managed to avoid legal issues. However, he foresees improvements in the law because there are ongoing discussions about whether AI-generated works should be attributed to the developers or trainers of the AI program that created it. He also highlighted the intricacies associated with enforcing stringent regulations against AI usage. While some individuals may misuse AI technology, he acknowledged the necessity for AI to streamline repetitive tasks for individuals and companies, subsequently enhancing their efficiency and time management. “From an instructor’s perspective, AI can automate routine tasks like grading exams, offering feedback, and creating teaching materials, allowing educators to focus on teaching. AI can enhance efficiency and productivity in educational settings.”
There are further examples that highlight the dark side of AI, with one being the increasing abuse of deep fake technology to spread false content. Deep fake technology employs advanced AI algorithms to create highly realistic yet entirely fabricated media, such as videos, audio clips, and images. These manipulated pieces of content can be incredibly convincing, making it difficult to distinguish what is genuine from what is not. For instance, a deep fake video can potentially depict a public figure saying or doing something they never actually did, leading to misinformation and potentially damaging their reputation. For example, Chinese TikToker Yilong Ma impersonated Elon Musk with the help of deep fake technology, convincing viewers that they were doppelgangers. Such misuse of AI-driven deep fake technology underscores the pressing need for robust ethical considerations in the development and deployment of AI systems. As these technologies continue to evolve, ensuring responsible and accountable use is crucial to prevent harm to individuals, society, and the trust placed in digital media.
Balancing Creativity and AI
AI’s trajectory points toward further development in the future. As AI technology continues to rapidly evolve and gain wider traction in society, the importance of establishing a concrete definition of creativity becomes more evident. Over the next decade, AI’s role in creative endeavors is poised to undergo transformative changes, revolutionizing how we conceptualize and generate artistic and innovative content. As AI technologies like generative adversarial networks (GANs) and natural language processing (NLP) continue to advance, it is foreseeable that scenarios will emerge in which AI collaborates as a partner with human creators.
With AI automation gaining momentum, there is a concern that certain tasks traditionally carried out by humans could become automated, leading to reduced demand for human creative professionals. According to a report by the World Economic Forum, it is projected that AI will replace 85 million jobs by 2025. This prediction highlights the urgent issue of job displacement in various sectors, including creative fields, and it underscores the importance of finding a way for AI to collaborate with the unique creativity of humans. Striking the right balance is crucial; overly restricting AI could stifle the generation of fresh ideas, yet unregulated, it may outperform and potentially dominate human labor.
Addressing these concerns requires a proactive approach. Forming a balance between AI’s creative capabilities and safeguarding human ingenuity is crucial. This necessitates initiatives that prepare creative professionals for an AI-augmented future, emphasizing the uniquely human aspects of creativity that AI cannot replicate, such as emotional depth, intuition, and nuanced storytelling. Fostering interdisciplinary collaborations that combine AI expertise with creative vision could open up entirely new creative ideas, enabling the co-creation of art that is both technologically advanced and profoundly human. “AI-generated works may ignore or distort the essence of art, leading to ethical and copyright issues,” said Professor Kwon. “These challenges should be carefully addressed to ensure that AI contributes positively to human creativity.” Ultimately, shaping AI’s role in creativity will require not only technological innovation but also thoughtful consideration of the social and economic implications for creative professionals.
Therefore, to foster a harmonious coexistence between human and AI creativity, several strategies need to be explored. Embracing AI as a tool rather than a replacement is key. By treating AI as a partner, humans can provide the contextual understanding, emotional depth, and ethical considerations that are often missing in AI-generated content. Furthermore, transparency in AI-generated content is crucial. Implementing clear labeling to indicate whether a piece of art or content is AI-assisted can help maintain trust and authenticity. This transparency empowers audiences to engage with the content while being aware of the creative process involved. Lastly, continuous upskilling and reskilling initiatives are essential. Creative professionals should be equipped with the skills to work alongside AI, including understanding how to harness its potential, refine its output, and imbue it with human sensibilities. This could involve training programs that combine technical AI knowledge with creativity, fostering a new breed of professional adept at navigating this hybrid landscape.
The interaction between AI and creativity is intricate. AI’s expanding capacity to generate art, music, and literature challenges conventional notions of creativity, despite its absence of intrinsic motivation compared to human creativity. Ethical concerns concerning authorship and originality are gaining prominence, necessitating ongoing legal deliberation. Achieving equilibrium entails preparing creative professionals for an AI-augmented future, highlighting the distinct aspects of human creativity, and promoting collaboration between AI and human creativity. This dynamic evolution calls for the treatment of AI as a tool, ensuring transparency in AI-generated content, and facilitating continuous skill development. Ultimately, navigating this evolving relationship requires ethical, legal, and educational issues to be addressed in order to leverage AI’s potential for enhancing human creativity and benefiting society