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cloud.google.com·6h ago
AI Research
arXiv CS.AI·Sep 7·5 min read
When Does an Interpretation Count as Established? The Formation, Evaluation, and Responsibility of Interpretation in Generative AI
TL;DR
This paper explores how interpretations in generative AI are recognized and established, introducing concepts like interpretive appearance and standing substitution. It emphasizes the need for ongoing evaluation and responsibility in the interpretation process.
✦ Why It Matters
Implement delayed closure practices to ensure ongoing evaluation and accountability in your AI interpretations.
Key Takeaways
- Recognize the limitations of local evaluations in establishing interpretations.
- Implement clear criteria for valid judgments in AI outputs.
- Maintain a public structure for revising interpretations.
- Adopt delayed closure to keep interpretations open to new evidence.
Full Summary
Generative AI has focused on evaluating aspects like factuality and citation, but these checks alone do not confirm that an interpretation is established. The paper introduces three key concepts: interpretive appearance, which highlights the gap between an output's final form and the process behind it; the evaluation contract, which defines the criteria and boundaries for valid judgments; and standing substitution, which refers to the unwarranted escalation of local evaluations into broader claims without new evidence.
The authors argue that responsibility for interpretations is often unclear, as public structures for revising or questioning conclusions may be absent. They propose 'delayed closure' as a practice to keep interpretations open to revision and outline five public requirements to enhance accountability in generative AI outputs.
This conceptual framework aims to clarify why local evaluations and public recognition should not be seen as definitive proof of established interpretations.