Why AI Is WEIRD and Should Not Be This Way: Towards AI For Everyone, With Everyone, By Everyone

Understand

This paper presents a vision for creating AI systems that are inclusive at every stage of development, from data collection to model design and evaluation.

• We address key limitations in the current AI pipeline and its WEIRD representation, such as lack of data diversity, biases in model performance, and narrow evaluation metrics.
• We also focus on the need for diverse representation among the developers of these systems, as well as incentives that are not skewed toward certain groups.
• We highlight opportunities to develop AI systems that are for everyone (with diverse stakeholders in mind), with everyone (inclusive of diverse data and annotators), and by everyone (designed and developed by a globally diverse workforce).