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WILL AI END CREATIVITY?

UNPACKING THE HUMANITY BEHIND GENERATIVE AI CO-CREATIONS

[Student IDEAS] by Nelberto Nicholas Quinto - PhD student in the Management department at ESSEC Business School

Abstract

As AI ventures into the world of creativity, fears are mounting about its potential to undermine human ingenuity and curb innovative pursuits, leading some to proclaim the 'end of creativity.' To navigate this complex issue, this article demystifies the concept of 'creativity,' explores its societal and organizational importance, and breaks down its key elements—novelty and usefulness. Amidst this analysis, a key concern emerges: does the 'human touch' – e.g. emotions, feelings, human experience and intention, etc. – matter in our evaluations of creativity, and if it does - are AI co-creation necessarily devoid of it? We analyze this in a case study and conclude on how this affects our understanding of AI’s effect on overall creativity. 

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Recent advancements in artificial intelligence (AI) have prompted us to ponder the fate of human creativity and its relationship with technology. Present-day AI platforms have demonstrated their prowess in generating a diverse array of creative outputs. From fabricating tailor-made digital imagery, crafting compelling advertising phrases, drafting cogent essays, or even composing infectious tunes, the allure of generative AI technologies is unmistakable. In 2022 alone, they have drawn a staggering $2.654 billion in investments, marking a tenfold increase since 2020. As AI encroaches upon what was once considered a uniquely human domain, the ontological, economic, and legal systems that underlie creative production are consequently being redefined in profound, uncharted ways. Amidst this upheaval, a question emerges: Is creativity dying, and is AI the culprit?

What Exactly Is Creativity and Why is it Important?

To untangle this provocative question, it is essential to probe into the essence of creativity—its core attributes and its significance to society and organizations. Creativity is defined as the generation of ideas, solutions, or products that are both novel and useful1,2. It is a multifaceted phenomenon, encapsulating not just the outcome or process of idea development, artistic creation, or problem-solving3, but also the inherent ability of individuals to produce the new and valuable. As the cornerstone of innovation, creativity transforms unique ideas into tangible actions or products, which in turn fuel technological advancements. Within organizations, creative employees are a catalyst for competitive advantage4. They contribute unique solutions to pressing challenges, resulting in strategies, business processes, and design concepts that drive success. Creativity also bolsters adaptability in the face of external changes and disruptive technologies, enhancing the likelihood of success for individuals and organizations5.

To grasp the essence of creativity’s central components – novelty (newness, originality) and usefulness (value, quality) – think of the last time you or someone around you has deemed something to be ‘creative.’ Was the value found in the end result or in the process that led to it? As will be revealed, this distinction is central to the debate of whether the growing impact of AI will usher in a creative renaissance or its antithesis.

How AI Affects Creativity: Perspectives, Benefits, and Limitations

The Product Perspective

The traditional perspective of creativity places emphasis on the final product. Think about an evocative novel or an influential film. Their creativity is gauged by the audience's experience with the completed work. The unpredictability of the plot, the introduction of nonconforming characters, and the use of groundbreaking narrative styles all serve as sources of novelty. Meanwhile, the exhilaration experienced from narratives that defy convention, the emotions they stir within us, the curiosity they spark, and the respite they offer from everyday life—all are markers of usefulness attributed to the end product. AI-generated designs, leading to a revolutionary product, align with this perspective. From a managerial standpoint, the value is not in the AI's process of creation but in the resultant artifact—its appeal in the market, and its innovative design that caters to and anticipates consumer needs.

From this product-centered perspective, AI emerges as a potent tool for enhancing our creativity. It produces innovative ideas and forms that inspire human artists and democratize access to creative production by making aesthetic prowess and innovative combinations more accessible. Generative AI can be conceptualized as a new 'paintbrush' for artists and creatives. Anyone can pick up this 'brush' and create—be it poems, design prototypes, or unique product concepts—without necessarily needing the traditional, extensive training or experience. For many, this accessibility may very well foster inclusivity, thereby encouraging a larger population to engage in creative pursuits. It brings people who might never consider performing artistic or innovative work into the sphere of creative endeavors, exploring their human ingenuity as they co-create with AI. 

AI Limitations in Creative Production

However, such democratization comes with its own challenges and limitations. The novelty of the output generated heavily relies on the creativity infused in prompts. The usefulness of the final output also remains somewhat limited, especially when considering the current state of AI wherein the quality of the generated paragraphs, images, or media may still fall short of those produced by traditional professionals.

There's often a substantial amount of trial and error involved in crafting the right prompts, as well as significant post-processing once a satisfactory output is achieved. While these are technical limitations that may be resolved as AI advances, there's another side to consider. As AI improves, so will the benchmarks for what is considered quality, useful, and new. Therefore, it's rare for a few string of prompts to suffice in creating something truly considered creative—that is, novel and valuable—for its time. Even with significant advancements in AI capabilities over time, leading to minimal post-processing or prompt engineering needs, there's always an inherent risk tied to tools that simplify processes.  

The Process Perspective

Another facet of creativity lies not in the final product, but in the process itself. Envision a Master Chef contestant, orchestrating a culinary symphony with a keen eye for novelty and a daring spirit to match the time and ingredient constraints set by Gordon Ramsay and his colleagues. Their masterpiece unfolds as an intricate dance of unexpected ingredient pairings, artistic presentations, and innovative use of techniques, equipment, and resources. Here, creativity is not solely defined by the outcome but by the culinary journey that unfurls, tantalizing taste buds and challenging preconceived notions of what can be done with limited resources. Similarly, improvisational theater values the performers' on-the-spot thinking, synchronized action, and narrative creation, as much as the final performance. The process is integral to determining creativity. Even in organizational settings, the sequential motions inherent in problem-solving —brainstorming, experimentation, and collaboration—are regarded as creative, alongside the effectiveness of their end solution.

Human Experience is Where the Real Issue Lies

Despite known limitations, numerous instances exist where works co-created with AI have been recognized for their creativity. Last year, a digital image generated by AI won a statewide art competition in Colorado. The judges affirmed that their decision to honor the contestant would have remained the same, regardless of prior knowledge of AI involvement in the artwork. In April of this year, a song that employed AI to generate melodies in the voices and styles of popular artists Drake and The Weeknd, went viral on social media. Titled 'Heart On My Sleeve', this track mimicked the stars' distinctive styles in verses ostensibly about pop sensation Selena Gomez, who has romantic ties with The Weeknd. The song was widely lauded for its innovative stylistic fusion and its infectious rhythm. Similarly, in corporate environments, generative AI has been employed to aid the development of innovative marketing campaigns as well as fundamentally novel and useful business strategies that managers can build upon and implement. As such, AI capabilities continue to improve over time, it's becoming increasingly apparent that there's little pushback against the technology’s ability to generate works that are novel and valuable, provided that creativity is interpreted from a product oriented perspective. Hence, the primary criticisms against AI's capability to produce or enhance creativity stem from adopting the process-centric one. 

Valuing process over product often comes with an emphasis on the emotional and sensory journey inherent in human imagination and innovation. This viewpoint suggests that the true value of creative work is deeply entwined with the feelings and shared experiences manifested in its creation. As AI produces creative works based on learned patterns– without true comprehension of our intentions, history, or emotions– creations that leverage it are seen to lack the depth and meaning that gives value to the creative process. Thus, for the many patrons of the human touch, any process void of these elements loses their usefulness automatically. Singer and songwriter Nick Cave eloquently expressed this very sentiment when reacting to a song written by AI chatbot GPT in 'his style':

"Songs arise out of suffering, by which I mean they are predicated upon the complex, internal human struggle of creation and, well, as far as I know, algorithms don’t feel. Data doesn’t suffer. ChatGPT has no inner being, it has been nowhere, it has endured nothing, it has not had the audacity to reach beyond its limitations, and hence it doesn’t have the capacity for a shared transcendent experience, as it has no limitations from which to transcend. ChatGPT’s melancholy role is that it is destined to imitate and can never have an authentic human experience, no matter how devalued and inconsequential the human experience may in time become.”

Are AI Co-Creations Really Devoid of Human Experience: A Case Study

In December of 2022, an intriguing event unfolded in the creative world. One, that invites reflection into the humanity behind AI-co creations. Aamar Reshi, then a tech worker in Silicon Valley, who had no prior experience in graphic illustration or creative writing, produced a children’s book in the span of 72 hours and sold 841 copies in Amazon over a week. His secret sauce? OpenAI's Chat GPT for the story narrative, and the AI art generator, Midjourney, for the illustrations. This well-documented accomplishment represents an interesting shift in the creative landscape, as tasks that traditionally demanded years of learning and skill honing were executed by Aamar in a mere three days—and at virtually no financial cost.

A crucial aspect of this narrative is that Aamar circumvented the laborious grind of mastering digital design and storytelling intricacies. His main inputs, as documented on his Twitter feed6 were two-fold: textual prompts that generated the narratives and illustrations found in his book, and his clever use of these digital tools to construct a coherent piece in a limited amount of time. Trial and error was central to his creative process, as he experimented with different prompts to craft his desired manuscript and illustrations. What used up most of his time was learning to maintain a consistent depiction of his protagonists, Alice and Sparkle on Midjourney. Yet, the conversion of his imagined images and plot ideas into tangible illustrations, descriptions, and written stories required merely a few seconds of waiting time for each iteration. While Aamar's journey showcases the power of AI to democratize the creative process, it also highlights the pitfalls of such an approach. His illustrations lacked consistency and detail, likely a result of his over-reliance on AI tools and his lack of domain expertise in the digital arts. In the end, Sparkle, Alice's robot companion, was rendered differently across each page due to Midjourney's inability to produce consistent illustrations from the same descriptions. Alice, too, was not spared from inconsistencies, depicted with missing fingers on occasion. 

The Creativity and Humanity behind Aamar’s Co-Creation with AI

Aamar was innovative in his clever use of limited resources to solve a pressing challenge: creating a children's book. Although he did not utilize traditional artistic techniques or software, his co-creation with AI served as a conduit for transmuting his imagination into tangible prototypes that allowed him to develop a novel plotline through experimentation with various prompts. Confronted with the issue of inconsistent images, Aamar applied his human ingenuity to devise a clever solution: describing Sparkle to be a robot that metamorphosed into various forms-  a creative fix that cohesively blended with his narrative. 

As noted, his case also illustrates the democratization and streamlining of creative work. Even if he lacked formal training in graphic design and had no prior experience as an illustrator or storyteller, he was still able to conceive an original, interesting story that had (somewhat) coherent and meaningful illustrations. In essence, he came up with creative solutions to turning his fresh ideas into a tangible product which found significant demand, and hence– value, upon its release. And although the usefulness of his work is limited by the inconsistent and, at times un-detailed, illustrations –a limitation which might diminish as AI technology continues to evolve and improve– the evidence suggests that Aamar’s final product is in fact, creative - i.e. novel and useful. Despite the innovative manner in which he developed his storybook however, the value in his process remains questionable to those who value the human elements which underlie creativity production. Therefore, the query looms: was his work void of the humanity that– arguably– gives meaning, depth, and usefulness to the creative process?

Not only did he “borrow” the feelings and emotions nested in the collective intelligence within Chat GPT's memory to produce his plot, dialogue, and illustrations, but upon further contemplation, much of his process actually involves a variety of inherently human attributes. The excitement he felt with his work, the love he felt for his niece that sparked this project, the oscillations between euphoria and melancholy during each imaginative iteration, and the victorious sensation he savored as he reveled in his accomplished masterpiece were all profoundly human experiences and emotions.

In the parlance of Nick Cave’s critique: his blood, sweat, and guts coalesced into a tangible expression of creativity– there at his desk– a realization of a nebulous idea that made its way to him. That is- within the vast expanse of algorithmic and artistic unpredictability, his creative idea found him. In all his humanity. And he made it come to fruition in three relentless days. Thus, Aamar’s case illustrates that the process of co-creation with generative AI can, and often does, involve quintessential human aspects where innovation emerges from processes and ideas that are new and valuable.

Reflections on the Generalizability of these Case Take-Aways

For those of you who have used AI to generate works that were considered novel and highly valuable by your peers, organization, or audience-evaluators, perhaps it is time to reflect and appreciate the inherent humanity in your creative work. For those of you who haven’t, you are invited to envision what such a process should involve as you go through the next sentences. 

Think of instances where you brainstormed ideas or developed potential solutions through a conversation with Chat GPT. Maybe there were times when you involved generative AI in creating a business proposal, an artistic illustration, a musical piece; or perhaps a scientific publication, an innovative product, or even a clever recommendation that was, in fact, considered original and beneficial. Did your creative journey involve the emotional roller coaster of highs and lows? The frustration felt when ideas fail? The iterative cycles where you leveraged multiple tools and information sources in inventive ways to achieve a part of your desired outcome? 

Did you harness feelings and intuitions from your gut? Did you rely on tacit heuristics and knowledge formed from years of accumulated experience and social interactions deeply embedded in your human psyche? If the answer to some of these questions are a yes, then it only shows that Aamar’s experience was not an isolated case- but is, in truth, a generalizable one. 

These aspects are integral to our humanity–our shared experience– and they would very likely have been present in the generative AI co-creation instances that you experienced or envisioned. Even the journey to developing your accumulated expertise in whatever it is you do involves painstakingly human ways in which you labored to sharpen them.  More people need to be reminded that the knowledge and skill that you and I have developed is critical to both evaluating and building upon the intermediate outputs produced by AI to produce works that are actually novel and useful. 

Indeed, the route to producing work that is genuinely innovative, with or without AI's assistance, invariably involves a unique recombination of our lived human experiences and abilities. As can be drawn from your personal cases, and that of Aamar Reshi’s, creators often employ a range of tools, techniques, and information sources to generate value and endure iterative procedures that are seldom smooth and free of emotional dynamics. As such, so long as humans remain in the production loop, any creative process that leverages generative AI still retains significant traces of our shared experience and human nature.

When Does Co-Creating with AI Harm Creativity then?

As with all tools that streamline processes, there is always a danger that individuals might over-rely on them, progressively depending less on their abilities and unique value contributions. In this case, such a trend could lead to a reduced cultivation of both individual creativity and the essential skills relevant to creative production—be it mastering the use of a paintbrush, crafting a riveting narrative for a target audience, evaluating the aesthetics of a presentation deck, or steering a company brainstorming session. As AI takes up an increasing part of the creative process, our aptitude for ideation, improvisation, and critical thinking may begin to fade. 

Similarly, when individuals overestimate AI’s ability to generate value, there is also a tendency to bypass activities that cultivate our ability to generate the novel and useful. Examples include discussing our ideas with our colleagues (as opposed to just chatting with an LLM about them), engaging in exploratory learning, or improving the depth of our specific professional expertise. The ease of producing AI-generated outputs that, at first glance, might seem highly innovative and valuable, might also cause a drop in motivation to engage in creative work - i.e. the question: 'If AI can generate creative works with relative ease, why should I expend the effort?' People need to understand that the path is often an arduous, emotionally tumultuous one, and cases where new and useful products are developed with relative ease are very much the exception rather than the norm. Moreover, projecting into the future, if AI does advance to the extent that it eliminates the need for substantial post-processing work, several prompt iterations, inventive ways to combine different tools and knowledge inputs to produce a novel and useful work– and well, all the emotions that come with these– would that signal the demise of creativity? It definitely is a possibility. If co-creating with generative AI results in fewer problems that demand new and impactful solutions, then creativity may diminish simply because we would need less of it. But that is, by all means, a good problem to have. 

Conclusion

It is imperative that individuals learn to co-create with generative AI tools both responsibly and proficiently. The outlined risks to our creativity demands an understanding that these technologies are not replacements for our own cognitive ability and domain expertise. Neither are they supposed to be used as quick-fix mechanisms for producing content (e.g. essays, images, or sounds) with scant surprise or quality appeal. Instead, individuals should engage with these tools in ways that stimulate their critical thinking, challenge them to push the boundaries of convention, and inspire them to conceive ideas, products, artworks, or business processes that are not only distinct from predecessors but also more efficient, value-enhancing, and superior in quality. And all of this begins with understanding that the path to truly creative co-creation with generative AI is a painstaking, iterative, and exploratory process that requires novel ways to combine our cumulative human experiences, imaginative capacity, and knowledge with the current capabilities of these technologies. 

Such a paradigm shift necessitates substantial investment from organizations, educational institutions, and even governments in programs designed to enable and encourage these exploratory practices. Experimentation, after all, benefits from guidance and often comes at the cost of not getting traditional work or schooling done. But this should not be a cause of worry. We have already witnessed select groups of individuals and organizations leveraging generative AI in new and useful ways that showcase their unlocked creative potential. Business news feeds and popular technology sites such as TechCrunch, Product Hunt, and VentureBeat are filled with a rich variety of new use cases each week. Hence, it is conceivable that support for such endeavors are likely to come. And, as history has demonstrated, when the innovative use of AI enables select groups of people or organizations to excel in their niche, gain a competitive advantage, or simply overcome their peers, then others will emulate their strategies– fueling creativity and perpetuating the cycle of innovation.

Will AI spell creativity’s demise, or could it instead ignite a renaissance of sorts? If the concern lies in losing the humanity behind the creative process, then, so long as humans are involved in the creation process, and that problems and needs that require novel and useful solutions, approaches, or products continue to exist, then the more optimistic of the two scenarios is likely to materialize. In other words, AI may well just revolutionize creativity for the better. 

There are, however, a few other concerns that need to be accounted for, such as the lack of acceptance or understanding behind the value that these generative technologies bring. Particularly relevant as well is how increasing AI adoption inevitably creates higher standards for what is valuable, truly unique, and feasible to accomplish within a given period of time. The sequel to this article attempts to summarize all of these other concerns, building on the evidence and logical arguments presented in this first part to more robustly answer the tantalizing question behind AI’s impact on creativity. Importantly, this second installment will underscore the necessity to shift our focus. The imminent issue may not be a potential dwindling of our ingenuity, but rather a constellation of critical factors surrounding the perception and common understanding regarding what it takes to co-create ideas, processes, or products with AI that are truly novel and useful. There's also a pressing need to consider the protective measures extended to workers who are at the interface of AI's influence. For instance, while AI may not necessarily stifle overall creativity, it holds the potential to extinguish the arts if considerations around the valuation of artistic capabilities and the protection of artists' intellectual property are not meticulously examined. These will all be touched upon in the sequel of this two-part article series (see "The AI Creative Renaissance: the Impact of Co-Creating with AI on Creativity and the Future of Work").

References

[1] Teresa M. Amabile et al., Affect and Creativity at Work, Administrative Science Quarterly 50, no. 3 (September 1, 2005): 367–403, https://doi.org/10.2189/asqu.2005.50.3.367.

[2]  Teresa M. Amabile, The Social Psychology of Creativity: A Componential Conceptualization., Journal of Personality and Social Psychology 45, no. 2 (August 1983): 357–76, https://doi.org/10.1037/0022-3514.45.2.357.

[3]  Spencer Harrison et al., The Turn toward Creative Work, Academy of Management Collections 1, no. 1 (August 4, 2022), https://doi.org/10.5465/amc.2021.0003.

[4]  Richard Florida and Jim Goodnight, Managing for Creativity, Harvard Business Review, July 1, 2005, https://hbr.org/2005/07/managing-for-creativity.

[5]  Martin Reeves and Mike Deimler, Adaptability: The New Competitive Advantage, Harvard Business Review, July 1, 2011, https://hbr.org/2011/07/adaptability-the-new-competitive-advantage.

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