Quantitative Auditing of AI Fairness with Differentially Private Synthetic Data
Fuente:
arXiv
Saved in:
| Main Authors: | Yuan, Chih-Cheng Rex, Wang, Bow-Yaw |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Ensuring Fairness with Transparent Auditing of Quantitative Bias in AI Systems
by: Yuan, Chih-Cheng Rex, et al.
Published: (2024)
by: Yuan, Chih-Cheng Rex, et al.
Published: (2024)
On the Need and Applicability of Causality for Fairness: A Unified Framework for AI Auditing and Legal Analysis
by: Binkyte, Ruta, et al.
Published: (2022)
by: Binkyte, Ruta, et al.
Published: (2022)
Auditing Fairness by Betting
by: Chugg, Ben, et al.
Published: (2023)
by: Chugg, Ben, et al.
Published: (2023)
Cost Efficient Fairness Audit Under Partial Feedback
by: Das, Nirjhar, et al.
Published: (2025)
by: Das, Nirjhar, et al.
Published: (2025)
Auditing Fairness under Model Updates: Fundamental Complexity and Property-Preserving Updates
by: Ajarra, Ayoub, et al.
Published: (2026)
by: Ajarra, Ayoub, et al.
Published: (2026)
Synthetic Data in AI: Challenges, Applications, and Ethical Implications
by: Hao, Shuang, et al.
Published: (2024)
by: Hao, Shuang, et al.
Published: (2024)
Data Augmentation via Diffusion Model to Enhance AI Fairness
by: Blow, Christina Hastings, et al.
Published: (2024)
by: Blow, Christina Hastings, et al.
Published: (2024)
Urania: Differentially Private Insights into AI Use
by: Liu, Daogao, et al.
Published: (2025)
by: Liu, Daogao, et al.
Published: (2025)
Differentially Private Data Release on Graphs: Inefficiencies and Unfairness
by: Fioretto, Ferdinando, et al.
Published: (2024)
by: Fioretto, Ferdinando, et al.
Published: (2024)
Decision Making with Differential Privacy under a Fairness Lens
by: Fioretto, Ferdinando, et al.
Published: (2021)
by: Fioretto, Ferdinando, et al.
Published: (2021)
What Drives Length of Stay After Elective Spine Surgery? Insights from a Decade of Predictive Modeling
by: Cho, Ha Na, et al.
Published: (2026)
by: Cho, Ha Na, et al.
Published: (2026)
Mapping the Potential of Explainable AI for Fairness Along the AI Lifecycle
by: Deck, Luca, et al.
Published: (2024)
by: Deck, Luca, et al.
Published: (2024)
FairSHAP: Preprocessing for Fairness Through Attribution-Based Data Augmentation
by: Zhu, Lin, et al.
Published: (2025)
by: Zhu, Lin, et al.
Published: (2025)
AI Fairness Beyond Complete Demographics: Current Achievements and Future Directions
by: Wang, Zichong, et al.
Published: (2025)
by: Wang, Zichong, et al.
Published: (2025)
Learning Fair Ranking Policies via Differentiable Optimization of Ordered Weighted Averages
by: Dinh, My H., et al.
Published: (2024)
by: Dinh, My H., et al.
Published: (2024)
Procedural Fairness Through Decoupling Objectionable Data Generating Components
by: Tang, Zeyu, et al.
Published: (2023)
by: Tang, Zeyu, et al.
Published: (2023)
Latent Noise Injection for Private and Statistically Aligned Synthetic Data Generation
by: Shen, Rex, et al.
Published: (2025)
by: Shen, Rex, et al.
Published: (2025)
A Unifying Human-Centered AI Fairness Framework
by: Rahman, Munshi Mahbubur, et al.
Published: (2025)
by: Rahman, Munshi Mahbubur, et al.
Published: (2025)
Opportunities and Challenges of Frontier Data Governance With Synthetic Data
by: Thakur, Madhavendra, et al.
Published: (2025)
by: Thakur, Madhavendra, et al.
Published: (2025)
Synthetic Data and the Shifting Ground of Truth
by: Offenhuber, Dietmar
Published: (2025)
by: Offenhuber, Dietmar
Published: (2025)
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
by: Han, Xiaotian, et al.
Published: (2023)
by: Han, Xiaotian, et al.
Published: (2023)
Algorithmic Fairness in AI Surrogates for End-of-Life Decision-Making
by: Ahmad, Muhammad Aurangzeb
Published: (2025)
by: Ahmad, Muhammad Aurangzeb
Published: (2025)
Evaluating AI Group Fairness: a Fuzzy Logic Perspective
by: Krasanakis, Emmanouil, et al.
Published: (2024)
by: Krasanakis, Emmanouil, et al.
Published: (2024)
Fair CCA for Fair Representation Learning: An ADNI Study
by: Hou, Bojian, et al.
Published: (2025)
by: Hou, Bojian, et al.
Published: (2025)
Balancing Fairness and Accuracy in Data-Restricted Binary Classification
by: Lazri, Zachary McBride, et al.
Published: (2024)
by: Lazri, Zachary McBride, et al.
Published: (2024)
FAIRPLAI: A Human-in-the-Loop Approach to Fair and Private Machine Learning
by: Sanchez Jr., David, et al.
Published: (2025)
by: Sanchez Jr., David, et al.
Published: (2025)
Whose Preferences? Differences in Fairness Preferences and Their Impact on the Fairness of AI Utilizing Human Feedback
by: Lerner, Emilia Agis, et al.
Published: (2024)
by: Lerner, Emilia Agis, et al.
Published: (2024)
Fairness in Federated Learning: Fairness for Whom?
by: Taik, Afaf, et al.
Published: (2025)
by: Taik, Afaf, et al.
Published: (2025)
SimFair: Physics-Guided Fairness-Aware Learning with Simulation Models
by: Wang, Zhihao, et al.
Published: (2024)
by: Wang, Zhihao, et al.
Published: (2024)
Toward Fair Federated Learning under Demographic Disparities and Data Imbalance
by: Wu, Qiming, et al.
Published: (2025)
by: Wu, Qiming, et al.
Published: (2025)
Fair Classification with Partial Feedback: An Exploration-Based Data Collection Approach
by: Keswani, Vijay, et al.
Published: (2024)
by: Keswani, Vijay, et al.
Published: (2024)
DualAlign: Generating Clinically Grounded Synthetic Data
by: Li, Rumeng, et al.
Published: (2025)
by: Li, Rumeng, et al.
Published: (2025)
Unlocking Fair Use in the Generative AI Supply Chain: A Systematized Literature Review
by: Mahuli, Amruta, et al.
Published: (2024)
by: Mahuli, Amruta, et al.
Published: (2024)
Trustless Audits without Revealing Data or Models
by: Waiwitlikhit, Suppakit, et al.
Published: (2024)
by: Waiwitlikhit, Suppakit, et al.
Published: (2024)
FairMT: Fairness for Heterogeneous Multi-Task Learning
by: Hu, Guanyu, et al.
Published: (2025)
by: Hu, Guanyu, et al.
Published: (2025)
OxonFair: A Flexible Toolkit for Algorithmic Fairness
by: Delaney, Eoin, et al.
Published: (2024)
by: Delaney, Eoin, et al.
Published: (2024)
FairPFN: Transformers Can do Counterfactual Fairness
by: Robertson, Jake, et al.
Published: (2024)
by: Robertson, Jake, et al.
Published: (2024)
FairHealth: An Open-Source Python Library for Trustworthy Healthcare AI in Low-Resource Settings
by: Yesmin, Farjana
Published: (2026)
by: Yesmin, Farjana
Published: (2026)
Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making
by: Alamdari, Parand A., et al.
Published: (2023)
by: Alamdari, Parand A., et al.
Published: (2023)
Runtime Monitoring and Enforcement of Conditional Fairness in Generative AIs
by: Cheng, Chih-Hong, et al.
Published: (2024)
by: Cheng, Chih-Hong, et al.
Published: (2024)
Similar Items
-
Ensuring Fairness with Transparent Auditing of Quantitative Bias in AI Systems
by: Yuan, Chih-Cheng Rex, et al.
Published: (2024) -
On the Need and Applicability of Causality for Fairness: A Unified Framework for AI Auditing and Legal Analysis
by: Binkyte, Ruta, et al.
Published: (2022) -
Auditing Fairness by Betting
by: Chugg, Ben, et al.
Published: (2023) -
Cost Efficient Fairness Audit Under Partial Feedback
by: Das, Nirjhar, et al.
Published: (2025) -
Auditing Fairness under Model Updates: Fundamental Complexity and Property-Preserving Updates
by: Ajarra, Ayoub, et al.
Published: (2026)