yusuke1997/dblp-id-title huggingface dataset:
Minimizing Risk Through Minimizing Model-Data Interaction: A Protocol For Relying on Proxy Tasks When Designing Child Sexual Abuse Imagery Detection Models
Promoting Ethical Awareness in Communication Analysis: Investigating Potentials and Limits of Visual Analytics for Intelligence Applications
Representation Online Matters: Practical End-to-End Diversification in Search and Recommender Systems
Liberatory Collections and Ethical AI: Reimagining AI Development from Black Community Archives and Datasets
Social Perception of Faces in a Vision-Language Model
Understanding the Effects of Explaining Predictive but Unintuitive Features in Human-XAI Interaction
From the total survey error framework to an error framework for digital traces of humans: translation tutorial
Algorithmic targeting of social policies: fairness, accuracy, and distributed governance
Detecting disparities in police deployments using dashcam data
Algorithmic Decisions, Desire for Control, and the Preference for Human Review over Algorithmic Review
The role of explainable AI in the context of the AI Act
Policy-as-Prompt: Rethinking Content Moderation in the Age of Large Language Models
Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases
"The human body is a black box": supporting clinical decision-making with deep learning
Fair Classification with Group-Dependent Label Noise
Centering disability perspectives in algorithmic fairness, accountability, & transparency
What We Can't Measure, We Can't Understand: Challenges to Demographic Data Procurement in the Pursuit of Fairness
Adaptive Sampling Strategies to Construct Equitable Training Datasets
PreFAIR: Combining Partial Preferences for Fair Consensus Decision-making
Actionable Recourse for Automated Decisions: Examining the Effects of Counterfactual Explanation Type and Presentation on Lay User Understanding
The Reality of AI and Biorisk
NeuroView-RNN: It's About Time
Null Compliance: NYC Local Law 144 and the challenges of algorithm accountability
Model Cards for Model Reporting
Are "Intersectionally Fair" AI Algorithms Really Fair to Women of Color? A Philosophical Analysis
Exploring the Role of Grammar and Word Choice in Bias Toward African American English (AAE) in Hate Speech Classification
Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, FAccT 2025, Athens, Greece, June 23-26, 2025
Reliable and Safe Use of Machine Translation in Medical Settings
Mind the Gap: Autonomous Systems, the Responsibility Gap, and Moral Entanglement
On The Impact of Machine Learning Randomness on Group Fairness
Learning Resource Allocation Policies from Observational Data with an Application to Homeless Services Delivery
Evaluation Gaps in Machine Learning Practice
Constructing Capabilities: The Politics of Testing Infrastructures for Generative AI
What to account for when accounting for algorithms: a systematic literature review on algorithmic accountability
What Remains Opaque in Transparency Initiatives: Visualizing Phantom Reductions through Devious Data Analysis
Fairness is not static: deeper understanding of long term fairness via simulation studies
The Model Card Authoring Toolkit: Toward Community-centered, Deliberation-driven AI Design
Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees
Recourse, Repair, Reparation, & Prevention: A Stakeholder Analysis of AI Supply Chains
Trust Development and Repair in AI-Assisted Decision-Making during Complementary Expertise
Measuring Machine Learning Harms from Stereotypes Requires Understanding Who Is Harmed by Which Errors in What Ways
Decoupled Classifiers for Group-Fair and Efficient Machine Learning
Racial/Ethnic Categories in AI and Algorithmic Fairness: Why They Matter and What They Represent
One Bad NOFO? AI Governance in Federal Grantmaking
The Death of the Legal Subject: How Predictive Algorithms Are (Re)constructing Legal Subjectivity
Reward Model Interpretability via Optimal and Pessimal Tokens
Representation, Self-Determination, and Refusal: Queer People's Experiences with Targeted Advertising
Best vs. All: Equity and Accuracy of Standardized Test Score Reporting
The cost of fairness in binary classification
Estimating the Electoral Consequences of Legislative Redistricting in France
How to Explain and Justify Almost Any Decision: Potential Pitfalls for Accountability in AI Decision-Making
High Dimensional Model Explanations: An Axiomatic Approach
Dissecting Racial Bias in an Algorithm that Guides Health Decisions for 70 Million People
Rights Out of Sight: Data Practices and Transparency Gaps in Smart Consumer IoT Ecosystems
Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation
When Human-AI Interactions Become Parasocial: Agency and Anthropomorphism in Affective Design
The Misuse of AUC: What High Impact Risk Assessment Gets Wrong
Opening the Scope of Openness in AI
Lost in translation: an interactive workshop mapping interdisciplinary translations for epistemic justice
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, FAccT 2023, Chicago, IL, USA, June 12-15, 2023
Examining risks of racial biases in NLP tools for child protective services
Making Intelligence: Ethical Values in IQ and ML Benchmarks
Multiaccurate Proxies for Downstream Fairness
When learning becomes impossible
Blind Faith? User Preference and Expert Assessment of AI-Generated Religious Content
Nteasee: Understanding Needs in AI for Health in Africa - A Mixed-Methods Study of Expert and General Population Perspectives
Price Discrimination with Fairness Constraints
Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning
Intervening to Increase Community Trust for Fair Network Outcomes
NLP for Maternal Healthcare: Perspectives and Guiding Principles in the Age of LLMs
Algorithmic Recourse: from Counterfactual Explanations to Interventions
Recommend Me? Designing Fairness Metrics with Providers
Reasons, Values, Stakeholders: A Philosophical Framework for Explainable Artificial Intelligence
Multi-category fairness in sponsored search auctions
Discrimination in Online Personalization: A Multidisciplinary Inquiry
Algorithmic Tools in Public Employment Services: Towards a Jobseeker-Centric Perspective
Why is "Problems" Predictive of Positive Sentiment? A Case Study of Explaining Unintuitive Features in Sentiment Classification
Measuring Representational Harms in Image Captioning
The Devil is in the Details: Interrogating Values Embedded in the Allegheny Family Screening Tool
Fast online ranking with fairness of exposure
Normative Evaluation of Large Language Models with Everyday Moral Dilemmas
Building and Auditing Fair Algorithms: A Case Study in Candidate Screening
"Cold, Calculated, and Condescending": How AI Identifies and Explains Ableism Compared to Disabled People
Questioning the ability of feature-based explanations to empower non-experts in robo-advised financial decision-making
Understanding and Mitigating Risks of Generative AI in Financial Services
Algorithms in the Stacks: Investigating automated, for-profit diversity audits in public libraries
Models for understanding and quantifying feedback in societal systems
Walking the Walk of AI Ethics: Organizational Challenges and the Individualization of Risk among Ethics Entrepreneurs
Simplicity Bias Leads to Amplified Performance Disparities
Justified Evidence Collection for Argument-based AI Fairness Assurance
Value-Driven Design for Public Administration: Insights from a Generative Chatbot in a Housing Application Case Study
"I wouldn't say offensive but...": Disability-Centered Perspectives on Large Language Models
The Harmful Fetishisation of Reductive Personal Tracking Metrics in Digital Systems
The Value of Disagreement in AI Design, Evaluation, and Alignment
Explainable AI in industry: practical challenges and lessons learned: implications tutorial
You Sound Depressed: A Case Study on Sonde Health's Diagnostic Use of Voice Analysis AI
Algorithmic Fairness in Performative Policy Learning: Escaping the Impossibility of Group Fairness
Fair Representation Clustering with Several Protected Classes
Regulating Explainability in Machine Learning Applications - Observations from a Policy Design Experiment
Auditing for Gerrymandering by Identifying Disenfranchised Individuals
Machine learning data practices through a data curation lens: An evaluation framework
Comparing Apples to Oranges: A Taxonomy for Navigating the Global Landscape of AI Regulation
Unlawful Proxy Discrimination: A Framework for Challenging Inherently Discriminatory Algorithms
Stakeholder Participation for Responsible AI Development: Disconnects Between Guidance and Current Practice
Whose side are ethics codes on?: power, responsibility and the social good
Harms from Increasingly Agentic Algorithmic Systems
On Microtargeting Socially Divisive Ads: A Case Study of Russia-Linked Ad Campaigns on Facebook
A Robot Walks into a Bar: Can Language Models Serve as Creativity SupportTools for Comedy? An Evaluation of LLMs' Humour Alignment with Comedians
The effects of competition and regulation on error inequality in data-driven markets
Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers
Assessing the intersection of organizational structure and FAT* efforts within industry: implications tutorial
Can Workers Meaningfully Consent to Workplace Wellbeing Technologies?
Designing for Responsible Trust in AI Systems: A Communication Perspective
Towards Effective Discrimination Testing for Generative AI
Identifying and Improving Disability Bias in GPT-Based Resume Screening
A Theory of Auditability for Allocation and Social Choice Mechanisms
Selection in the Presence of Implicit Bias: The Advantage of Intersectional Constraints
Can You Fake It Until You Make It?: Impacts of Differentially Private Synthetic Data on Downstream Classification Fairness
Auditing for Racial Discrimination in the Delivery of Education Ads
Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately
Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale
Examining the Expanding Role of Synthetic Data Throughout the AI Development Pipeline
Understanding Disparities in Post Hoc Machine Learning Explanation
FAccT-Check on AI regulation: Systematic Evaluation of AI Regulation on the Example of the Legislation on the Use of AI in the Public Sector in the German Federal State of Schleswig-Holstein
Fairness and Abstraction in Sociotechnical Systems
Understanding experiences with compulsory immigration surveillance in the U.S
Add-Remove-or-Relabel: Practitioner-Friendly Bias Mitigation via Influential Fairness
Experimentation with fairness-aware recommendation using librec-auto: hands-on tutorial
How can I choose an explainer?: An Application-grounded Evaluation of Post-hoc Explanations
Fairness-Aware Programming
The hidden assumptions behind counterfactual explanations and principal reasons
Behavioral Use Licensing for Responsible AI
Four Years of FAccT: A Reflexive, Mixed-Methods Analysis of Research Contributions, Shortcomings, and Future Prospects
'Affordances' for Machine Learning
An Action-Oriented AI Policy Toolkit for Technology Audits by Community Advocates and Activists
Robots Enact Malignant Stereotypes
A Data-Driven Simulation of the New York State Foster Care System
Algorithmic Fairness and Vertical Equity: Income Fairness with IRS Tax Audit Models
Operationalizing the Search for Less Discriminatory Alternatives in Fair Lending
Tackling Algorithmic Disability Discrimination in the Hiring Process: An Ethical, Legal and Technical Analysis
Fair Clustering via Equitable Group Representations
Ethnic Classifications in Algorithmic Fairness: Concepts, Measures and Implications in Practice
Gender Bias Detection in Court Decisions: A Brazilian Case Study
Deconstructing FAT: using memories to collectively explore implicit assumptions, values and context in practices of debiasing and discrimination-awareness
How are ML-Based Online Content Moderation Systems Actually Used? Studying Community Size, Local Activity, and Disparate Treatment
Subverting Fair Image Search with Generative Adversarial Perturbations
Fairness-Guided Pruning of Decision Trees
Data augmentation for fairness-aware machine learning: Preventing algorithmic bias in law enforcement systems
Multi-dimensional Discrimination in Law and Machine Learning - A Comparative Overview
Centralized Trust in Decentralized Systems: Unveiling Hidden Contradictions in Blockchain and Cryptocurrency
The Dimensions of Data Labor: A Road Map for Researchers, Activists, and Policymakers to Empower Data Producers
Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI
Real Risks of Fake Data: Synthetic Data, Diversity-Washing and Consent Circumvention
Assessing algorithmic fairness with unobserved protected class using data combination
On the apparent conflict between individual and group fairness
Detecting Prefix Bias in LLM-based Reward Models
Differential Tweetment: Mitigating Racial Dialect Bias in Harmful Tweet Detection
The Digital Faces of Oppression and Domination: A Relational and Egalitarian Perspective on the Data-driven Society and its Regulation
Problem Formulation and Fairness
CtrlZ.AI zine fair: critical perspectives
Two computer scientists and a cultural scientist get hit by a driver-less car: a method for situating knowledge in the cross-disciplinary study of F-A-T in machine learning: translation tutorial
Measuring and mitigating voting access disparities: a study of race and polling locations in Florida and North Carolina
Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content?
What do Large Language Models Say About Animals? Investigating Risks of Animal Harm in Generated Text
What does it mean to 'solve' the problem of discrimination in hiring?: social, technical and legal perspectives from the UK on automated hiring systems
All The Cool Kids, How Do They Fit In?: Popularity and Demographic Biases in Recommender Evaluation and Effectiveness
Datafication Genealogies beyond Algorithmic Fairness: Making Up Racialised Subjects
The Disparate Effects of Strategic Manipulation
Why Am I Not Seeing It? Understanding Users' Needs for Counterfactual Explanations in Everyday Recommendations
Gone With the Bits: Revealing Racial Bias in Low-Rate Neural Compression for Facial Images
Honor Ethics: The Challenge of Globalizing Value Alignment in AI
A Critical Survey on Fairness Benefits of Explainable AI
The Medium is the Message: How Non-Clinical Information Shapes Clinical Decisions in LLMs
DualCF: Efficient Model Extraction Attack from Counterfactual Explanations
The Slow Violence of Surveillance Capitalism: How Online Behavioral Advertising Harms People
Multi-layered explanations from algorithmic impact assessments in the GDPR
Perceptive Visual Urban Analytics is Not (Yet) Suitable for Municipalities
Keep Your Friends Close and Your Counterfactuals Closer: Improved Learning From Closest Rather Than Plausible Counterfactual Explanations in an Abstract Setting
Location matching on shaky grounds: Re-evaluating algorithms for refugee allocation
Search Engines in the AI Era: A Qualitative Understanding to the False Promise of Factual and Verifiable Source-Cited Responses in LLM-based Search
Trustworthy AI and the Logics of Intersectional Resistance
This Whole Thing Smacks of Gender: Algorithmic Exclusion in Bioimpedance-based Body Composition Analysis
Explainable AI is Dead, Long Live Explainable AI!: Hypothesis-driven Decision Support using Evaluative AI
A Bayesian Model of Cash Bail Decisions
Doctor XAI: an ontology-based approach to black-box sequential data classification explanations
LEAD: Towards Learning-Based Equity-Aware Decarbonization in Ridesharing Platforms
Value-laden disciplinary shifts in machine learning
SIDEs: Separating Idealization from Deceptive 'Explanations' in xAI
Limits of Individual Consent and Models of Distributed Consent in Online Social Networks
AI Ethics Statements: Analysis and Lessons Learnt from NeurIPS Broader Impact Statements
XAI-Units: Benchmarking Explainability Methods with Unit Tests
In the Walled Garden: Challenges and Opportunities for Research on the Practices of the AI Tech Industry
Rethinking AI Safety: Provocations from the History of Community-based Practices of Road and Driver Safety
Roles for computing in social change
Model Multiplicity: Opportunities, Concerns, and Solutions
What TikTok Claims, What Bold Glamour Does: A Filter's Paradox
Value Cards: An Educational Toolkit for Teaching Social Impacts of Machine Learning through Deliberation
Bias in word embeddings
AI Trust Reshaping Administrative Burdens: Understanding Trust-Burden Dynamics in LLM-Assisted Benefits Systems
FAT* '20: Conference on Fairness, Accountability, and Transparency, Barcelona, Spain, January 27-30, 2020
Can Querying for Bias Leak Protected Attributes? Achieving Privacy With Smooth Sensitivity
Auditing Political Exposure Bias: Algorithmic Amplification on Twitter/X During the 2024 U.S. Presidential Election
Pragmatic Fairness: Evaluating ML Fairness Within the Constraints of Industry
Classification Metrics for Image Explanations: Towards Building Reliable XAI-Evaluations
The Dark Side of Dataset Scaling: Evaluating Racial Classification in Multimodal Models
Queer In AI: A Case Study in Community-Led Participatory AI
Fairness Beyond the Algorithmic Frame: Actionable Recommendations for an Intersectional Approach
Preference-informed fairness
Algorithmically encoded identities: reframing human classification
A Critical Analysis of the Largest Source for Generative AI Training Data: Common Crawl
Representation in AI Evaluations
Taxonomy of Risks posed by Language Models
Misgendered During Moderation: How Transgender Bodies Make Visible Cisnormative Content Moderation Policies and Enforcement in a Meta Oversight Board Case
AI Regulation Is (not) All You Need
Exploring Language Patterns of Prompts in Text-to-Image Generation and Their Impact on Visual Diversity
Evaluating Model Explanations without Ground Truth
Diagnosing AI Explanation Methods with Folk Concepts of Behavior
Data Leverage: A Framework for Empowering the Public in its Relationship with Technology Companies
Ethical Concerns and Perceptions of Consumer Neurotechnology from Lived Experiences of Mental Workload Tracking
Conference on Fairness, Accountability and Transparency, FAT 2018, 23-24 February 2018, New York, NY, USA
Data, Annotation, and Meaning-Making: The Politics of Categorization in Annotating a Dataset of Faith-based Communal Violence
Group Fairness: Independence Revisited
The "Who", "What", and "How" of Responsible AI Governance: A Systematic Review and Meta-Analysis of (Actor, Stage)-Specific Tools
Measuring the Biases that Matter: The Ethical and Casual Foundations for Measures of Fairness in Algorithms
Talking past each other? Navigating discourse on ethical AI: Comparing the discourse on ethical AI policy by Big Tech companies and the European Commission
Adversarial Scrutiny of Evidentiary Statistical Software
MiMICRI: Towards Domain-centered Counterfactual Explanations of Cardiovascular Image Classification Models
The Dataset Multiplicity Problem: How Unreliable Data Impacts Predictions
Fairness Auditing in Urban Decisions using LP-based Data Combination
Hardwiring discriminatory police practices: the implications of data-driven technological policing on minority (ethnic and religious) people and communities
AI's Regimes of Representation: A Community-centered Study of Text-to-Image Models in South Asia
Social Bias in Vision Transformers: A Comparative Study Across Architectures and Learning Paradigms
De-biasing "bias" measurement
Aggregating Concepts of Fairness and Accuracy in Prediction Algorithms
C2Explainer: Customizable Mask-based Counterfactual Explanation for Graph Neural Networks
Perils of Label Indeterminacy: A Case Study on Prediction of Neurological Recovery After Cardiac Arrest
When Predictions are More Than Predictions: Self-Fulfilling Performativity and the Road Towards Morally Responsible Predictive Systems
Fairness Feedback Loops: Training on Synthetic Data Amplifies Bias
The Case for a Legal Compliance API for the Enforcement of the EU's Digital Services Act on Social Media Platforms
A Framework for Deprecating Datasets: Standardizing Documentation, Identification, and Communication
What Does it Mean for a Language Model to Preserve Privacy?
Documenting Computer Vision Datasets: An Invitation to Reflexive Data Practices
Toward situated interventions for algorithmic equity: lessons from the field
Does AI-Assisted Fact-Checking Disproportionately Benefit Majority Groups Online?
Group Fairness via Group Consensus
Detecting discriminatory risk through data annotation based on Bayesian inferences
Marrying Fairness and Explainability in Supervised Learning
The Problem of Generics in LLM Training
Reliability Gaps Between Groups in COMPAS Dataset
Responsible AI in Education: Understanding Teachers' Priorities and Contextual Challenges
Sensible AI: Re-imagining Interpretability and Explainability using Sensemaking Theory
Interrogating LLM design under copyright law
Transforming Dutch: Debiasing Dutch Coreference Resolution Systems for Non-binary Pronouns
Learning about Responsible AI On-The-Job: Learning Pathways, Orientations, and Aspirations
Designing an Online Infrastructure for Collecting AI Data From People With Disabilities
'We can't find fault with a friend': The Mediation of Accountability on Instant Loan Platforms in India
Agent Allocation of Moral Decisions in Human-Agent Teams: Raise Human Involvement and Explain Potential Consequences
Integrating FATE/critical data studies into data science curricula: where are we going and how do we get there?
Towards Geographic Inclusion in the Evaluation of Text-to-Image Models
Who Speaks for Ethics? How Demographics Shape Ethical Advocacy in Software Development
Beyond Use-Cases: A Participatory Approach to Envisioning Data Science in Law Enforcement
My Future with My Chatbot: A Scenario-Driven, User-Centric Approach to Anticipating AI Impacts
Affirmative Algorithms: Relational Equality as Algorithmic Fairness
Personalized Pricing with Group Fairness Constraint
Frameworks, Methods and Shared Tasks: Connecting Participatory AI to Trustworthy AI Through a Systematic Review of Global Projects
The Gradient of Generative AI Release: Methods and Considerations
Value is in the Eye of the Beholder: A Framework for an Equitable Graph Data Evaluation
Gender and Racial Bias in Visual Question Answering Datasets
Critical Tools for Machine Learning: Working with Intersectional Critical Concepts in Machine Learning Systems Design
Downstream Effects of Affirmative Action
A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions
SIREN: A Simulation Framework for Understanding the Effects of Recommender Systems in Online News Environments
Interdisciplinarity, Gender Diversity, and Network Structure Predict the Centrality of AI Organizations
Towards Fair Deep Anomaly Detection
The Distributive Effects of Risk Prediction in Environmental Compliance: Algorithmic Design, Environmental Justice, and Public Policy
Equitable Public Bus Network Optimization for Social Good: A Case Study of Singapore
Fair ranking: a critical review, challenges, and future directions
Mixed Messages? The Limits of Automated Social Media Content Analysis
Predictability and Surprise in Large Generative Models
Algorithmic Fairness, Decision Thresholds, and the Separateness of Persons
Proceedings of the Conference on Fairness, Accountability, and Transparency, FAT* 2019, Atlanta, GA, USA, January 29-31, 2019
Now you see it, Now you don't: Damage Label Agreement in Drone & Satellite Post-Disaster Imagery
Bridging Voting and Deliberation with Algorithms: Field Insights from vTaiwan and Kultur Komitee
Algorithmic Unfairness through the Lens of EU Non-Discrimination Law: Or Why the Law is not a Decision Tree
Breaking Down Bias: On The Limits of Generalizable Pruning Strategies
An Empirical Study of Rich Subgroup Fairness for Machine Learning