Investigating the intelligibility of a computer vision system for blind users - Ahmed, Subeida; Sellen, Abigail; Stumpf, Simone; Balasubramanian, Harshadha; Grayson, Martin; Morrison, Cecily (IUI '20: Proceedings of the 25th International Conference on Intelligent User Interfaces, 2020)
Computer vision systems to help blind users are becoming increasingly common, yet often these systems are not intelligible. Our work investigates the intelligibility of a wearable computer vision system to help blind users locate and identify people in their vicinity. Providing a continuous stream of information, this system allows us to explore intelligibility through interaction and instructions, going beyond studies of intelligibility that focus on explaining a decision a computer vision system might make. In a study with 13 blind users, we explored whether varying instructions (either basic or enhanced) about how the system worked would change blind users' experience of the system. We found offering a more detailed set of instructions did not affect how successful users were using the system nor their perceived workload. We did, however, find evidence of significant differences in what they knew about the system and they employed different, and potentially more effective, use strategies. Our findings have important implications for researchers and designers of computer vision systems for blind users, as well as more general implications for understanding what it means to make interactive computer vision systems intelligible.