Eternagram：通过基于大语言模型的对话探索毁灭后的气候未来来激励气候行动
Eternagram: Inspiring Climate Action Through LLM-based Conversational Exploration of a Post-Devastation Climate Future
AI总结：
Eternagram通过基于大语言模型的对话探索毁灭后的气候未来，激发公众对气候问题的关注和环保意识。
摘要：
气候行动难以说服人们，因为我们倾向于将气候变化视为遥远且与日常生活无关。与其传统的信息性参与，基于游戏的干预可以创造沉浸式的叙事，使访客置身于其行动有实际后果的情境中。为了使这些叙事更具吸引力，我们使用了一个假设场景，即外星人偶然发现社交媒体，通过基于文本的冒险游戏装置间接探讨气候变化。模仿访客在社交媒体应用中的自然对话，我们设计了一个基于大语言模型的聊天机器人，该机器人了解一个气候毁灭后的世界，这与我们自己的地球相似。通过互动聊天和发布的图片发现世界毁灭，玩家开始意识到自己的行动对这个遥远世界气候变化的影响，从而培养环保态度。此前发表于CHI，这款游戏装置展示了基于大语言模型的创造性叙事在探索虚构世界并推动社会变革方面的潜力。
英文摘要：
Climate action is difficult to persuade because we tend to perceive climate change as remote and disconnected from daily life. Instead of traditional informational engagements, game-based interventions can create narratives that immerse the visitor in situations where their actions have tangible consequences. To make these narratives engaging, we used a speculative scenario of an alien stumbling upon social media to obliquely address climate change through a text-based adventure game installation. Mimicking visitors' natural dialogue in social media apps, we designed an LLM-based chatbot with knowledge of post-climate devastated world that mirrors our own planet Earth. In discovering the world's downfall through interactive chatting and posted images, players begin to realize that their own actions can make a difference on impacts of climate change in this distant world, fostering pro-environmental attitudes. Previously published at CHI, this game installation demonstrates the potential of LLM based creative narratives in exploring speculative worlds driving social change.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
