:: Library Catalog

Saved in:

Bibliographic Details
Main Author:	Brusseau, James
Format:	Preprint
Published:	2025
Subjects:	Computers and Society
Online Access:	https://arxiv.org/abs/2504.13790
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Case Study in Acceleration AI Ethics: The TELUS GenAI Conversational Agent
by: Brusseau, James
Published: (2025)

AI Human Impact: Toward a Model for Ethical Investing in AI-Intensive Companies
by: Brusseau, James
Published: (2025)

Deleuze's "Postscript on the Societies of Control" Updated for Big Data and Predictive Analytics
by: Brusseau, James
Published: (2025)

The Dilemma Between Euphoria and Freedom in Recommendation Algorithms
by: Brusseau, James
Published: (2025)

Mapping AI Avant-Gardes in Time: Posthumanism, Transhumanism, Genhumanism
by: Brusseau, James
Published: (2025)

What to Do When Privacy Is Gone
by: Brusseau, James
Published: (2025)

How AI Generates Creativity from Inauthenticity
by: Brusseau, James, et al.
Published: (2025)

Collapsed Language Models Promote Fairness
by: Xu, Jingxuan, et al.
Published: (2024)

Addressing Both Statistical and Causal Gender Fairness in NLP Models
by: Chen, Hannah, et al.
Published: (2024)

The Bottomless Pit Revisited.
by: Hardesty, Larry
Published: (1991)

A Primer on Causal and Statistical Dataset Biases for Fair and Robust Image Analysis
by: Jones, Charles, et al.
Published: (2025)

The Statistical Signature of LLMs
by: Hadad, Ortal, et al.
Published: (2026)

FairSCOSCA: Fairness At Arterial Signals -- Just Around The Corner
by: Riehl, Kevin, et al.
Published: (2026)

Quantifying Fairness in LLMs Beyond Tokens: A Semantic and Statistical Perspective
by: Xu, Weijie, et al.
Published: (2025)

The Collapse of Heterogeneity in Silicon Philosophers
by: Shi, Yuanming, et al.
Published: (2026)

FairHome: A Fair Housing and Fair Lending Dataset
by: Bagalkotkar, Anusha, et al.
Published: (2024)

Fair Representation in Parliamentary Summaries: Measuring and Mitigating Inclusion Bias
by: Cunningham, Eoghan, et al.
Published: (2025)

From the Fair Distribution of Predictions to the Fair Distribution of Social Goods: Evaluating the Impact of Fair Machine Learning on Long-Term Unemployment
by: Zezulka, Sebastian, et al.
Published: (2024)

FairWire: Fair Graph Generation
by: Kose, O. Deniz, et al.
Published: (2024)

Four Things People Should Know About Migraines
by: Parsa, Mohammad S., et al.
Published: (2025)

Position: the Stochastic Parrot in the Coal Mine. Model Collapse is a Threat to Low-Resource Communities
by: Jarvis, Devon, et al.
Published: (2026)

Surviving the Narrative Collapse: Sustainability and Justice in Computing Within Limits
by: Guruge, Dave, et al.
Published: (2025)

Context Collapse: Barriers to Adoption for Generative AI in Workplace Settings
by: Moss, Emanuel, et al.
Published: (2026)

Configuration Work: Four Consequences of LLMs-in-use
by: Alcaras, Gabriel, et al.
Published: (2025)

Fairness in Limited Resources Settings
by: Bachmat, Eitan, et al.
Published: (2026)

On Algorithmic Fairness and the EU Regulations
by: Ruohonen, Jukka
Published: (2024)

Alternative Fairness and Accuracy Optimization in Criminal Justice
by: Wu, Shaolong, et al.
Published: (2025)

FairGT: A Fairness-aware Graph Transformer
by: Luo, Renqiang, et al.
Published: (2024)

What is Fair? Defining Fairness in Machine Learning for Health
by: Gao, Jianhui, et al.
Published: (2024)

Lost in Translation? Translation Errors and Challenges for Fair Assessment of Text-to-Image Models on Multilingual Concepts
by: Saxon, Michael, et al.
Published: (2024)

FairViT: Fair Vision Transformer via Adaptive Masking
by: Tian, Bowei, et al.
Published: (2024)

FairAdapter: Detecting AI-generated Images with Improved Fairness
by: Ding, Feng, et al.
Published: (2024)

FairRAG: Fair Human Generation via Fair Retrieval Augmentation
by: Shrestha, Robik, et al.
Published: (2024)

Fair for a few: Improving Fairness in Doubly Imbalanced Datasets
by: Yalcin, Ata, et al.
Published: (2025)

Procedural Fairness and Its Relationship with Distributive Fairness in Machine Learning
by: Wang, Ziming, et al.
Published: (2025)

Be Intentional About Fairness!: Fairness, Size, and Multiplicity in the Rashomon Set
by: Dai, Gordon, et al.
Published: (2025)

FairPFN: A Tabular Foundation Model for Causal Fairness
by: Robertson, Jake, et al.
Published: (2025)

AdapFair: Ensuring Adaptive Fairness for Machine Learning Operations
by: Huang, Yinghui, et al.
Published: (2024)

The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning
by: Fawkes, Jake, et al.
Published: (2024)

Assessing the Impact of Case Correction Methods on the Fairness of COVID-19 Predictive Models
by: Smolyak, Daniel, et al.
Published: (2024)