RESEARCHMonitorWATCHLIST
Whose Voice Survives the Summary? A Voice-Retention Audit of LLM Employee Listening
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
Research introduces a Voice Retention metric to measure representational bias and systemic silencing in LLM summaries of employee feedback.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 1 October 2026
- Collected by OneBench
- 2 Oct 2026, 03:01 UK
Stored source excerpt
arXiv:2609.38818v1 Announce Type: cross Abstract: Organizations increasingly route employee feedback to leaders through large language model (LLM) summaries, an unaudited layer that silences already-spoken voice.…
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