Journey of ChatGPT from Prompts to Stories in Games: the Positive, the Negative, and the Neutral

This paper presents a study on biases present in the story endings for story-driven games generated by ChatGPT. The study uses various prompts to assess the biases in ChatGPT's output. The results emphasize a consistent inclination towards positive endings in the stories generated by ChatGPT. Even when explicitly instructed to generate neutral endings, ChatGPT exhibited a bias towards positive outcomes. These biases raise concerns regarding the training data and alignment processes used by OpenAI to train ChatGPT, as they may reflect societal biases or the preferences of the majority of the data. Addressing these biases is crucial to ensure that these models align with societal norms and avoid reinforcing existing biases. Future studies should concentrate on developing methods to reduce biases in AI language models and enhance the ethical perspective of these technologies. Our source code and data are made publicly available at https://bit.ly/chatgpt-game-story-gen.