Honorable Mention
Content creators are instructed to write textual descriptions of visual content to make it accessible; yet existing guidelines lack specifics on how to write about people's appearance, particularly while remaining mindful of consequences of (mis)representation. In this paper, we report on interviews with screen reader users who were also Black, Indigenous, People of Color, Non-binary, and/or Transgender on their current image description practices and preferences, and experiences negotiating theirs and others' appearances non-visually. We discuss these perspectives, and the ethics of humans and AI describing appearance characteristics that may convey the race, gender, and disabilities of those photographed. In turn, we share considerations for more carefully describing appearance, and contexts in which such information is perceived salient. Finally, we offer tensions and questions for accessibility research to equitably consider politics and ecosystems in which technologies will embed, such as potential risks of human and AI biases amplifying through image descriptions.
https://doi.org/10.1145/3411764.3445498
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2021.acm.org/)