For example, computer vision might give people who are blind a better sense of the visual world, speech recognition and translation technologies might offer real-time captioning for people who are hard of hearing, and new robotic systems might augment the capabilities of people with mobility restrictions. Considering the needs of users with disabilities can help technologists identify high-impact challenges whose solutions can advance the state of AI for all users. At the same time, ethical challenges such as inclusion, bias, privacy, error, expectation setting, simulated data, and social acceptability must be considered. In this lecture, I will define these seven challenges, provide examples of how they relate to AI for Accessibility technologies, and discuss future considerations in this space.