As AI is increasingly integrated into various industries, concerns about its potential to reproduce or exacerbate bias have become widespread. While the use of AI holds the promise of reducing bias, it can also have unintended consequences, particularly in high-stakes computer vision applications such as facial recognition. However, even seemingly low-stakes computer vision applications such as identifying potholes and damaged roads can also present ethical challenges related to bias. This talk will explore how bias in computer vision often poses an ethical challenge, regardless of the stakes involved. We will discuss the limitations of technical solutions aimed at mitigating bias, and why “bias-free” AI may not be achievable. Instead, we will focus on the importance of adopting a “bias-aware” approach to responsible AI design and explore strategies that can be employed to achieve this.