Imagine a world where playing video games helps build the very foundation of artificial intelligence. That's the intriguing premise behind new research exploring how the power of human gameplay can enhance knowledge graphs, the backbone of accurate and explainable AI. Large language models (LLMs) like ChatGPT are impressive, but they sometimes struggle with accuracy and can even hallucinate, making up facts. This is a major problem for critical applications like analyzing human trafficking data, where accuracy is paramount. Knowledge graphs offer a solution by providing LLMs with a structured, verifiable database of facts. However, building these graphs is complex. They often miss implicit connections – things obvious to humans but not explicitly stated in text. This is where video games come in. Researchers have developed a framework called GAME-KG (Gaming for Augmenting Metadata and Enhancing Knowledge Graphs). It uses crowdsourced feedback gathered through specially designed games to fill in these missing links. In a demonstration using a noir-style mystery game called Dark Shadows, players interacted with a knowledge graph built from US Department of Justice press releases on human trafficking. By playing the game, they helped identify implicit connections and strengthen the graph's accuracy. Early results are promising. When GPT-4 was tested with questions based on the game-enhanced knowledge graph, its answers were more accurate and explainable. This research opens exciting possibilities. Imagine gamers unknowingly contributing to a global knowledge base that powers more reliable and transparent AI. While challenges remain, including the potential for human bias, this innovative approach could revolutionize how we build and validate AI knowledge, making it more robust and trustworthy for critical applications.