Transparency as Answerability: Role-Dependent Information Flow Modeling

Key points

• Transparency in AI-supported decision systems is widely required but poorly defined.1
• We formalize this using information flow networks, in which transparency questions are expressed in terms of network structure and answerability is the condition that the system settles them.1
• The framework supports three dimensions of analysis: structural answerability from the network alone, compositional answerability across organizational boundaries for deployed systems, and role-dependent answerability given a stakeholder's accessible sub-network.1
• We show how structural and role-dependent transparency questions can be formally stated and analyzed across the Provider and Deployer boundary where the AI system is composed together with the deployer's decision process.1

Sources (1)

• [1]Transparency as Answerability: Role-Dependent Information Flow Modeling
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 12, 02:46 PM

  We propose treating transparency as a relation: a system is transparent to a stakeholder to the degree that their legitimate questions are answerable from its structure.

  Transparency in AI-supported decision systems is widely required but poorly defined.

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