arXiv (All)
open access
Auditing Bias and Safety in Voice AI Customer Care
68t0168t50audio-and-speech-processingcomputation-and-languagecomputers-and-societyh-5-2human-computer-interactioni-2-11
Voice AI systems increasingly mediate customer care interactions where caller presentation cues such as accent, affect, fluency, and urgency are available alongside the service request. Existing fairness and safety evaluations cover speech recognition disparities, spoken dialogue bias, and voice age
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Machine Translation of Audiovisual Media and Epistemic Access: Ethical Questions in AI Video Localization#716591
- Prediction-Powered Smoothing and Validation for Disaggregated AI Evaluation#1034553
- Prediction-Powered Smoothing and Validation for Disaggregated AI Evaluation#978414
- Co-designing for Compliance: Multi-party Computation Protocols for Post-Market Fairness Monitoring in Algorithmic Hiring#1178630
- Co-designing for Compliance: Multi-party Computation Protocols for Post-Market Fairness Monitoring in Algorithmic Hiring#1178616
Record · ID 927509
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive