Abstract
Imagine having a concept for a literary work but being unable to see it take shape because of a plethora of reasons: paucity of time, writer's block, linguistic barriers, among others. Gen AI promises to be a supportive partner in these creative endeavours. With the synergy of mind and machine, literary texts are born. This chapter attempts to provide insights into the comparison between the nuances of human-AI co-creative partnerships through the crafting of short stories. Using the lens of Collaborative Autoethnography, two seasoned educators collaboratively reflect on cognitive, behavioural, and affective dimensions of co-creating with ChatGPT, a chatbot developed by Open AI. The chapter analyses the co-creation process followed by each of the authors and brings out the commonalities and specificities of the individual lived experience to achieve a narrative piece of work. The insights of the co-creation process would be beneficial to educators, curriculum designers, technology specialists, students and those who intend to use AI-powered chatbots as co-creators.
TopHuman And Ai-Assisted Creativity: Fundamental Differences And Similarities
Human-led creative processes harness the depth of human intuition, emotions, and subjective experiences, constituting the cornerstone of artistic expression. Creativity often germinates from personal inspiration, perspectives and cultural influences (Kwan et al., 2018). Such human-centric creation embodies varied and nuanced interpretations, reflecting the intricate tapestry of diverse human thought processes. It involves complex cognitive manoeuvres, emotional connections, and a contextual understanding deeply rooted in human experiences, fostering adaptability in evolving ideas based on intuition and personal evolution.
Contrastingly, AI collaboration in creative endeavours relies on algorithms and machine learning to generate content or aid the creative process. This approach leverages computational prowess to process vast data and patterns, birthing novel outputs grounded in learned information. AI exhibits efficiency and speed in ideation, overcoming time constraints, and facilitating iterative creative processes. However, it remains constrained by the data it has been trained on, lacking human-like intuition, emotions or contextual understanding (Merriam, 2021), marking a pivotal distinction from human-led creation. While studies in the last five years attest that human-AI collaborations enhance story creation (Fang et al., 2023), the researchers did not find any study on the comparison of brainstorming and co-creation of fiction between human co-creators and with ChatGPT using the collaborative autoethnographic approach.
Key Terms in this Chapter
Collaborative Autoethnography: involves a collective approach to the autoethnographic process, where a group of individuals (here, two) collaboratively examines and reflects upon their shared experiences and cultural dynamics. This method combines personal narratives and cultural analysis, emphasizing collaboration among researchers to explore and understand shared experiences or cultural phenomena from multiple perspectives. The process often involves shared storytelling, dialogue, and collective interpretations to uncover broader sociocultural insights.
ChatGPT: is an advanced AI language model created by OpenAI, capable of engaging in natural conversation and generating contextually relevant text based on given input.
Human-Centered AI: prioritizes creating AI systems that cater to human needs and values. It focuses on human well-being, usability, and ethics, aiming for transparent, intuitive systems that align with human intentions. This approach emphasizes collaboration and trust between humans and AI, placing human concerns at the forefront of AI development for more empathetic and beneficial solutions.
Natural Language Processing (NLP): involves the interaction between computers and human language. It encompasses AI techniques and algorithms enabling machines to understand, interpret, and generate human language. NLP facilitates tasks like language translation, sentiment analysis, speech recognition, and text generation, enabling machines to process and respond to human language in a way that's comprehensible and contextually relevant.
Ethical AI: involves principles and guidelines ensuring that Artificial Intelligence (AI) technologies operate in ways that align with human values, fairness, transparency, and societal welfare. It addresses concerns about bias, privacy, safety, and the overall ethical impact of AI on individuals and communities, aiming to develop and deploy AI systems responsibly and in accordance with moral considerations.
AI Co-Creativity: embodies a collaborative alliance between human creators and Artificial Intelligence (AI), notably Generative AI models like ChatGPT. It represents the shared creation, moulding, or enhancement of creative outputs where AI collaborates as a partner, offering insights, suggestions, or content alongside human creators. This concept merges human ingenuity with AI prowess in the creative realm, fostering joint authorship and reciprocal influence, leading to innovative results.
ChatBot: is an AI-powered computer program that engages in text or voice-based conversations, mimicking human interaction, to assist users with tasks, answer inquiries, or provide information.
Educational Technology (Edtech): involves using technology to enhance learning and teaching, incorporating digital tools and resources to improve educational experiences and outcomes.
Human-AI Collaboration: denotes the cooperative interaction between humans and Artificial Intelligence (AI) systems to achieve shared goals or tasks. It involves the combined efforts where humans and AI work together, leveraging respective strengths to complement each other's abilities. This collaboration can encompass various domains such as creative endeavours, problem-solving, decision-making, or task automation, aiming to harness the unique capabilities of both humans and AI for more effective outcomes.
Artificial Intelligence (AI): replicates human-like intelligence in machines, enabling them to learn, reason, and solve problems. It involves creating algorithms and models that help machines perform tasks typically done by humans. AI has diverse applications across various industries.
GenAI, or Generative Artificial Intelligence,: encompasses AI models, like ChatGPT, programmed to autonomously create content. By learning from extensive datasets, these models leverage machine learning algorithms to produce human-like text, images, and diverse content forms. Known for their ability to comprehend context and generate coherent outputs, GenAI models, exemplified by ChatGPT, find applications in creativity, education, and problem-solving arenas.