Artificial Intelligence (AI) has become an integral part of modem technology, yet it continues to reflect and amplify human biases, particularly racial bias. Artificial Intelligence (AI) has become an integral part of modern technology, yet it continues to reflect and amplify human biases, particularly racial bias. This paper explores the issue of racial bias in generative AI. By examining case studies such as Google Gemini’s image generation controversies and Microsoft’s Tay chatbot, and centering computer science student voices on bias in AI systems and its potential to impact their future work in their discipline, this paper discusses potential underlying causes of this bias as historical and systemic prejudices inform them. The paper also presents potential strategies for mitigating bias, emphasizing the need for rigorous testing, diverse datasets, and ethical AI development practices. Understanding and addressing these biases is essential for computer science students, as it shapes their training, influences their ability to develop fair and responsible Al systems, and prepares them to navigate ethical challenges in their professional careers.