Cover Image

Quota-based debiasing can decrease representation of already underrepresented groups

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Smirnov, Ivan, Lemmerich, Florian, Strohmaier, Markus
Format:	Preprint
Published:	2020
Subjects:	Computers and Society Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Comparative Evaluation of Quantification Methods
by: Schumacher, Tobias, et al.
Published: (2021)

A debiasing technique for place-based algorithmic patrol management
by: Einarsson, Alexander, et al.
Published: (2023)

Toxic comments reduce the activity of volunteer editors on Wikipedia
by: Smirnov, Ivan, et al.
Published: (2023)

German General Social Survey Personas: A Survey-Derived Persona Prompt Collection for Population-Aligned LLM Studies
by: Rupprecht, Jens, et al.
Published: (2025)

Prompt Perturbations Reveal Human-Like Biases in Large Language Model Survey Responses
by: Rupprecht, Jens, et al.
Published: (2025)

Sleeper Social Bots: a new generation of AI disinformation bots are already a political threat
by: Doshi, Jaiv, et al.
Published: (2024)

Fact-checking information from large language models can decrease headline discernment
by: DeVerna, Matthew R., et al.
Published: (2023)

Linearity-based neural network compression
by: Dobler, Silas, et al.
Published: (2025)

Why can't Epidemiology be automated (yet)?
by: Bann, David, et al.
Published: (2025)

What AI evaluations for preventing catastrophic risks can and cannot do
by: Barnett, Peter, et al.
Published: (2024)

AI threats to national security can be countered through an incident regime
by: Ortega, Alejandro
Published: (2025)

Where can AI be used? Insights from a deep ontology of work activities
by: Cai, Alice, et al.
Published: (2026)

What can large language models do for sustainable food?
by: Thomas, Anna T., et al.
Published: (2025)

Deceptive AI systems that give explanations are more convincing than honest AI systems and can amplify belief in misinformation
by: Danry, Valdemar, et al.
Published: (2024)

The US Algorithmic Accountability Act of 2022 vs. The EU Artificial Intelligence Act: What can they learn from each other?
by: Mokander, Jakob, et al.
Published: (2024)

From Turing to Tomorrow: The UK's Approach to AI Regulation
by: Ritchie, Oliver, et al.
Published: (2025)

Large language models can consistently generate high-quality content for election disinformation operations
by: Williams, Angus R., et al.
Published: (2024)

Embedding Cultural Diversity in Prototype-based Recommender Systems
by: Moradi, Armin, et al.
Published: (2024)

AI tutoring can safely and effectively support students: An exploratory RCT in UK classrooms
by: LearnLM Team, et al.
Published: (2025)

Artificial intelligence can persuade people to take political actions
by: Hackenburg, Kobi, et al.
Published: (2026)

The Coming Crisis of Multi-Agent Misalignment: AI Alignment Must Be a Dynamic and Social Process
by: Carichon, Florian, et al.
Published: (2025)

The Potential of Answer Classes in Large-scale Written Computer-Science Exams -- Vol. 2
by: Lohr, Dominic, et al.
Published: (2024)

Persona-driven Simulation of Voting Behavior in the European Parliament with Large Language Models
by: Kreutner, Maximilian, et al.
Published: (2025)

Truth or Tribe: How In-group Favoritism Prioritize Facts in Persona Agents
by: Lei, Shijun, et al.
Published: (2026)

Choosing a Model, Shaping a Future: Comparing LLM Perspectives on Sustainability and its Relationship with AI
by: Bush, Annika, et al.
Published: (2025)

A Detailed Study on LLM Biases Concerning Corporate Social Responsibility and Green Supply Chains
by: Ontrup, Greta, et al.
Published: (2025)

A Technological Perspective on Misuse of Available AI
by: Pöhler, Lukas, et al.
Published: (2024)

Form Without Function: Agent Social Behavior in the Moltbook Network
by: Zerhoudi, Saber, et al.
Published: (2026)

Measuring AI R&D Automation
by: Chan, Alan, et al.
Published: (2026)

Early Warning Signals Appear Long Before Dropping Out: An Idiographic Approach Grounded in Complex Dynamic Systems Theory
by: Saqr, Mohammed, et al.
Published: (2026)

Responsible AI in Business
by: Sandfuchs, Stephan, et al.
Published: (2026)

General-purpose AI models can generate actionable knowledge on agroecological crop protection
by: Wyckhuys, Kris A. G.
Published: (2025)

AI Sandbagging: Language Models can Strategically Underperform on Evaluations
by: van der Weij, Teun, et al.
Published: (2024)

Societal AI Research Has Become Less Interdisciplinary
by: Markus, Dror Kris, et al.
Published: (2025)

Measuring What Matters -- or What's Convenient?: Robustness of LLM-Based Scoring Systems to Construct-Irrelevant Factors
by: Walsh, Cole, et al.
Published: (2026)

Visibility Allocation Systems: How Algorithmic Design Shapes Online Visibility and Societal Outcomes
by: Ionescu, Stefania, et al.
Published: (2025)

ShaRP: Explaining Rankings and Preferences with Shapley Values
by: Pliatsika, Venetia, et al.
Published: (2024)

The ATOM Report: Measuring the Open Language Model Ecosystem
by: Lambert, Nathan, et al.
Published: (2026)

"It's not a representation of me": Examining Accent Bias and Digital Exclusion in Synthetic AI Voice Services
by: Michel, Shira, et al.
Published: (2025)

Neural network embeddings recover value dimensions from psychometric survey items on par with human data
by: Pellert, Max, et al.
Published: (2025)