This article by Reham Hosny is one of a series commissioned as part of MyWorld, a UKRI-funded project that explores the future of creative technology innovation by pioneering new ideas, products and processes in the West of England. We have commissioned writers, academics, creators and makers to contribute a written snapshot into how artificial intelligence is changing, enhancing and challenging creative writing and publishing practices.  

In the early stages of algorithmic creative writing, Christopher Strachey‘s love letter generator, developed in the 1950s using the first general-purpose electronic computer Ferranti Mark 1, stands as a pioneering effort. This early endeavour marked the genesis of a transformative journey that has unfolded through subsequent decades, shaping the landscape of creative expression in the era of artificial intelligence (AI). 

 Strachey’s experiment utilised constrained structures derived from poetic forms as templates for the algorithms. The concept of predefined structural constraints gained further traction in the 1960s with the French experimental school Oulipo, which sought to explore novel forms of algorithmic writing. A significant paradigm shift occurred with recent Large Language Models (LLMs), which, through extensive training on diverse datasets, can generate creative content in response to human language prompts. This transformation marks a departure from predefined constrained structures governed by specific algorithms for producing certain literary genres and patterns. Instead, contemporary AI generators can produce a myriad of patterns and genres, drawing from huge training on millions of datasets.  

The extensive integration of AI in creative expression, alongside the public and widespread use of generative AI tools such as ChatGPT, DALL-E, and Bard, has sparked a significant discourse on the ethical considerations, challenges, and potentials inherent in AI-driven creative expression. This debate encompasses concerns about originality, authenticity, copyright, and authorship. This discussion also prompts reflection on the ethical implications of potential biases embedded in AI algorithms, raising questions about fairness and representation in the narratives generated. Additionally, the commodification of AI-generated content and its impact on the economic value of creative works introduces further ethical considerations, questioning the equitable distribution of profits and recognition within the creative industry. 

Moreover, as AI continues to evolve, a burgeoning exploration into the nature of creativity and the roles of active agents within AI-based creative processes has emerged. Conceptually, creativity as the capacity to generate innovative ideas and connect seemingly disparate thoughts evolves into a novel paradigm of “symbiotic creativity” when considered in the AI environment. Global projects are being currently developed to empower machines to understand and learn human aesthetics rather than imitating artwork crafted by humans. This kind of symbiotic creativity originates from the reciprocal and iterative augmentation between human and algorithmic potential, representing a dynamic evolution in creative collaboration.  

 The operational principle of AI generative models relies on learning from accumulated human interactions to emulate human-like responses in analogous scenarios. This reciprocal exchange enhances the sophistication of responses, qualifying AI as a proficient collaborator. In examining the mutual relationship between artificial intelligence and its context, N. Katherine Hayles introduces the metaphor of “Technosymbiosis” to argue that the act of meaning-making is not exclusive to humans; machines autonomously engage in this process within computational frameworks. “The feedback and feedforward loops” that enhance the symbiotic evolution of AI and humans, as perceived by Hayles, provide innovative opportunities for creativity in its new AI-assisted manifestation.   

Harnessing artificial creative capabilities, such as algorithmic generation and pattern recognition, in conjunction with human intuition, emotional depth, and subjective judgment, extends the scope and profundity of creative writing. Literary chatbots exemplify this synergy, pushing the boundaries of creative expression. Within the realm of AI applications, literary chatbots can seamlessly integrate into interactive storytelling experiences, allowing human participants to shape the narrative through consequential choices. Some literary chatbots are specifically designed for collaborative story or poem creation, where users contribute prompts or ideas, prompting the chatbot to generate narrative elements and creative content in response. Furthermore, writers can utilise these chatbots to delve into character exploration, plot development, and the cultivation of new creative concepts. The interactive fiction piece Galatea (2000) by Emily Short and the interactive drama Façade (2005) by Michael Mateas and Andrew Stern are two significant examples of early born-digital “bot” literature curated by the Electronic Literature Organization. 

Engaging in the discourse on the intersection of AI and creativity presents both challenges and opportunities. At this pivotal juncture, as AI becomes increasingly viable, accessible, and entrenched in platforms, it is crucial to investigate the potential for symbiotic creativity between AI and humans, fostering collaborative pathways rather than posing threats to our intertwined futures.