Artificial intelligence (AI) has become an increasingly critical component of not only the computing workforce but also society. It is essential for a diverse group of young people to contribute to this field. However, even within computing, AI is not taught to all post-secondary students. Students often must self-select into AI courses, meaning their reasons for choosing AI may be based on preconceptions of the discipline that may or may not be accurate. We extend the work of a small-n interview study of primarily Asian/Asian American undergraduate students, many of whom expressed perceptions of AI that paralleled identified computing stereotypes. Many of these stereotypes have the potential to discourage undergraduate computing students to take classes or specialize in AI, particularly those from underrepresented groups. Here we present a larger scale validation of those findings in the form of survey data conducted at a large public research institution in the USA. The survey largely confirmed the findings of the interview study at a larger scale, and we also found that gender did not significantly influence the results. Finally, we discuss strategies for AI integration into non-AI computing courses based on those previously used in responsible computing contexts, the goal being to counter harmful preconceptions before students specialize into computing subareas.