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The role of AI in narrative studies is not a question of if but of when and of how we humans prepare for such a future. The if claim is addressed with a detailed rebuttal to Angus Fletcher's 'Why Computers Will Never Read (or Write) Literature." A counter-argument based upon key AI concepts, the historical progress of AI, and landmark failures and breakthroughs brings readers up to date on the current state of AI as it relates to narrative studies. Numerous examples explain why the cycle of AI winters and springs is now broken, and there is a new global AI arms race. Scholars now have a windfall of increasingly sophisticated, multi-million dollar models that can analyze and generate narrative. Still, in light of the inherent complexity of natural language and the current limitations of even these state-of-the-art AI models, a human-in-the-loop is essential for the foreseeable future. We attempt to allay common yet misplaced concerns by reasserting the centrality of the human scholar to guide and interpret while using these tools. Leveraging these new AI models will yield new insights for narrative studies, and this important work will include shaping the language of fairness, equality, and ethics of models that increasingly impact the lives of billions. We invite narrative scholars to participate in this growing interdisciplinary movement that chooses active engagement over passive critique.
Chun et al. (Sat,) studied this question.