While artificial intelligence (AI) technology is becoming increasingly popular, its underlying mechanisms tend to remain opaque to most people. To address this gap, the field of AI literacy aims to develop various resources to teach people how AI systems function. Here we contribute to this line of work by proposing two games that demonstrate principles behind how large language models (LLMs) work and use data. The first game, Learn Like an LLM, aims to convey that LLMs are trained to predict sequences of text based on a particular dataset. The second game, Tag-Team Text Generation, focuses on teaching that LLMs generate text one word at a time, using both predicted probabilities of the data and randomness. While the games proposed are still in early stages and would benefit greatly from further discussion, we hope they can contribute to using game-based learning to teach about complex AI systems like LLMs.

翻译：尽管人工智能技术日益普及，但其底层机制对大多数人而言仍不透明。为填补这一认知鸿沟，人工智能素养领域致力于开发多种教育资源，帮助人们理解AI系统的运作方式。本文为此提出两款游戏，用以阐释大语言模型的工作原理及数据使用机制。第一款游戏《像LLM一样学习》旨在传达大语言模型基于特定数据集训练来预测文本序列的核心概念；第二款游戏《接力文本生成》则聚焦教学大语言模型如何逐词生成文本，这一过程既依赖数据的预测概率又引入随机性。虽然这两款游戏仍处于初级阶段，有待进一步完善和深入探讨，但我们希望它们能为游戏化学习在复杂AI系统（如大语言模型）教育中的应用提供新思路。