Artificial intelligence's (AI) progress holds great promise in tackling pressing societal concerns such as health and climate. Large Language Models (LLM) and the derived chatbots, like ChatGPT, have highly improved the natural language processing capabilities of AI systems allowing them to process an unprecedented amount of unstructured data. However, the ensuing excitement has led to negative sentiments, even as AI methods demonstrate remarkable contributions (e.g. in health and genetics). A key factor contributing to this sentiment is the misleading perception that LLMs can effortlessly provide solutions across domains, ignoring their limitations such as hallucinations and reasoning constraints. Acknowledging AI fallibility is crucial to address the impact of dogmatic overconfidence in possibly erroneous suggestions generated by LLMs. At the same time, it can reduce fear and other negative attitudes toward AI. This necessitates comprehensive AI literacy interventions that educate the public about LLM constraints and effective usage techniques, i.e prompting strategies. With this aim, a pilot educational intervention was performed in a high school with 21 students. It involved presenting high-level concepts about intelligence, AI, and LLMs, followed by practical exercises involving ChatGPT in creating natural educational conversations and applying established prompting strategies. Encouraging preliminary results emerged, including high appreciation of the activity, improved interaction quality with the LLM, reduced negative AI sentiments, and a better grasp of limitations, specifically unreliability, limited understanding of commands leading to unsatisfactory responses, and limited presentation flexibility. Our aim is to explore AI acceptance factors and refine this approach for more controlled future studies.

翻译：人工智能（AI）的进展在应对健康、气候等紧迫社会问题方面展现出巨大潜力。大型语言模型（LLM）及其衍生的聊天机器人（如ChatGPT）极大地提升了AI系统的自然语言处理能力，使其能够处理前所未有的非结构化数据。然而，随之而来的兴奋情绪也引发了负面感受，尽管AI方法已展现出显著贡献（例如在健康和遗传学领域）。造成这种情绪的关键因素之一是误导性认知，即认为LLM能毫不费力地跨领域提供解决方案，忽视了其幻觉现象和推理限制等局限性。承认AI的可错性对于应对对LLM可能产生的错误建议的教条式过度自信所带来的影响至关重要。同时，这也有助于减少对AI的恐惧及其他负面态度。这需要开展全面的AI素养教育，向公众普及LLM的限制及有效使用技巧（即提示策略）。基于此目的，我们在一所高中对21名学生进行了一项初步教育干预。干预内容包括介绍关于智能、AI和LLM的高层次概念，随后进行涉及ChatGPT的实践练习，包括创建自然的教育对话并应用既定的提示策略。初步结果令人鼓舞：学生对活动的评价很高，与LLM的交互质量得到改善，对AI的负面情绪有所减少，并且对LLM的局限性（特别是不可靠性、对指令理解有限导致回应不令人满意、以及呈现灵活性不足）有了更好的理解。我们的目标是探索AI接受度的相关因素，并完善这一方法，以便今后开展更受控的研究。