Advancing Explainability Through AI Literacy and Design Resources

Abstract

Explainability helps people understand and interact with the systems that make decisions and inferences about them. This should go beyond providing explanations at the moment of a decision; rather, explainability is best served when information about AI is incorporated into the entire user journey and AI literacy is built continuously throughout a person’s life. We have shared resources that can be used in both industrial and academic environments to encourage AI practitioners to think more broadly about what explanations can look like across products and ways to provide people with a solid foundation that helps them better understand AI systems and decisions.