Advancing Explainability Through AI Literacy And Design Resources
Speaker: Allison Woodruff – Mountain View, CA, United StatesTopic(s): Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing
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 share 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.About this Lecture
Number of Slides: 30 - 40Duration: 45 minutes
Languages Available: English
Last Updated:
Request this Lecture
To request this particular lecture, please complete this online form.
Request a Tour
To request a tour with this speaker, please complete this online form.
All requests will be sent to ACM headquarters for review.