arXiv (All)
open access
Tolerance-Based Fairness Auditing: Violation Certification and Sensitivity Screening
As artificial intelligence is increasingly deployed, algorithmic unfairness has raised growing concerns and intensified demands for transparent fairness auditing. In practice, the tolerable degree of algorithmic unfairness depends on the specific legal, ethical, or application context. Given a presp
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
- Democratizing Algorithmic Fairness#777813
- Algorithmic fairness: A runtime perspective#659396
- Disambiguating Algorithmic Bias: From Neutrality to Justice#715348
- Transparent, explainable, and accountable AI for robotics#776124
- Where are the Humans? A Scoping Review of Fairness in Multi-agent AI Systems#19060
Record · ID 1155940
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