Fairness, accountability, transparency in AI at scale
Muhammad Aurangzeb Ahmad, Ankur Teredesai, Carly Eckert
Abstract
The panel aims to elucidate how different national govenmental programs are implementing accountability of machine learning systems in healthcare and how accountability is operationlized in different cultural settings in legislation, policy and deployment. We have representatives from three different govenments, UAE, Singapore and Maldives who will discuss what accountability of AI and machine learning means in their contexts and use cases. We hope to have a fruitful conversation around FAT ML as it is operationalized ccross cultures, national boundries and legislative constraints.
Topics & Concepts
AccountabilityOperationalizationConversationTransparency (behavior)LegislationSoftware deploymentLegislatureScale (ratio)Computer sciencePolitical sciencePublic relationsBusinessPublic administrationSociologyComputer securitySoftware engineeringGeographyLawCommunicationCartographyEpistemologyPhilosophyArtificial Intelligence in Healthcare and EducationHealthcare Systems and Reforms