Children of Color's Perceptions of Fairness in AI: An Exploration of Equitable and Inclusive Co-Design
Zoe Skinner, Stacey Brown, Greg Walsh
Abstract
When it comes to algorithmic rights and protections for children, designers will need to face new paradigms to solve problems they are targeting. The field of Design typically deals with form and function and is executed in molecules or pixels. But algorithms have neither. More importantly, algorithms may be biased in their execution against those without privileged status such as people of color, children, and the non-affluent. In this paper, we review our work on exploring perceptions of fairness in AI through co-design sessions with children of color in non-affluent neighborhoods of Baltimore City. The design sessions aimed at designing an artificially intelligent librarian for their local branch. Our preliminary findings showcase three key themes of this group's perceptions of fairness in the context of an artificially intelligent authority figure.