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AI Research
arXiv CS.AI·1d ago·5 min read
Transparency as Answerability: Role-Dependent Information Flow Modeling
TL;DR
A new framework for transparency in AI decision systems is proposed, treating transparency as a relation based on answerability to stakeholders' questions. This approach addresses common failures in existing transparency models by formalizing information flow networks to enhance understanding across organizational boundaries.
✦ Why It Matters
Implement this framework to improve transparency and accountability in your AI systems today.
Key Takeaways
- Adopt the proposed framework for assessing AI transparency.
- Utilize information flow networks to model decision systems.
- Engage stakeholders in participatory design for better insights.
- Formulate transparency questions based on stakeholder roles.
How It Works
The framework uses information flow networks to model how questions about transparency can be answered based on the system's structure. It categorizes answerability into three dimensions: structural, compositional, and role-dependent, allowing for a nuanced understanding of transparency across different organizational contexts.