Inclusive Design: Methods to Ensure a High Degree of Participation in Artificial Intelligence (AI) Systems

With the rising use of Artificial Intelligence (AI) systems within different function in society, the issues of bias within these systems are becoming more widespread and notably impacting a larger number of people with a greater degree of seriousness. To mitigate and address these issues, this paper analyzes current practices in dataset compilation, use and AI system design before highlighting some state-of-the-art work being done in this domain. This is followed by recommendations to improve and build upon that work and propose an inclusivity matrix along with evaluation metrics, vernacular sharing and a call for small-data based AI approaches as concrete steps in addressing the issues of bias in these systems.