When Megan Gray, CEO of Moment AI, first tested one of her company's services -- a tool using AI to determine facial signs indicating a driver may have fallen asleep or suffered a medical issue -- it didn't work. "The technology worked on our CTO, who is a white male. But then I tried it, and it couldn't detect that my eyes were closed," Gray said. This is just one example of how a lack of diversity in the field of AI affects the technologies that are created. At GTC DC, this week's Washington edition of the GPU Technology Conference, a range of events focused on sharing ideas on how workplaces can become more inclusive, and how researchers can improve their AI technology to avoid bias.

Teaching an upper-level undergraduate robotics course at Historically Black Colleges and Universities (HBCUs) is challenging. The lack of suitable teaching materials is one of the biggest challenges, although there are many great masterpieces in developing robotics course materials, which are, however, generally developed for teaching students at elite Research I universities. This paper presents ideas and details in adopting and revising these course materials and creating upper-level undergraduate robotics course materials that are suitable for underrepresented students.