On the elements and implications of accountability for AI providers

Abstract

Increasing awareness and efforts to develop responsible AI are drawing attention to the area of accountability for decisions or predictions made with or around AI. Considerations can build off existing accountability concepts, however, need to recognize specific limitations and shortcomings that arise in the context of AI. Linking definitions from theory to practical discussion can reveal components and fundamental questions that need to be resolved to establish accountability in real-world use cases. The current status of settling these essentials is reviewed and open questions on how accountability can move from theory to practice are discussed with a specific focus on the elements and implications of accountability for AI providers.

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