Expanding Explainability: Towards Social Transparency in AI Systems

Catalog evidence and recorded chart appearances. Inclusion is not an endorsement.

Source snapshot imported 2026-10-20. This is not a live feed. Source and contributions.

Evidence and limits

Finding: Explanations can include who used the system, what they decided, and why, not only model internals, making organizational context visible.

Impact: Watch social transparency as a trace-design candidate. Reject social precedent as authority or truth.

Boundary: Interview and speculative evidence does not validate the proposed design. Next: which social context aids accountability without exposing private content or normalizing past errors?

Flags: small qualitative sample; proposed design not deployed

Record State: Catalog review recorded; not a performance endorsement

What was reviewed: Structure and relevance screened; not a full evaluation

Inspect original source

Recorded chart appearances

  • 2026-10-13: position 15. Relevant to the recorded review topic (see source); Structure and relevance screened; not a full evaluation evidence
  • 2026-10-12: position 14. Relevant to the recorded review topic (see source); Structure and relevance screened; not a full evaluation evidence