- Machine Explanations and Human Understanding.
- Broadening AI Ethics Narratives: An Indic Art View.
- How to Explain and Justify Almost Any Decision: Potential Pitfalls for Accountability in AI Decision-Making.
- 'We are adults and deserve control of our phones': Examining the risks and opportunities of a right to repair for mobile apps.
- Fairness in machine learning from the perspective of sociology of statistics: How machine learning is becoming scientific by turning its back on metrological realism.
- Two Reasons for Subjecting Medical AI Systems to Lower Standards than Humans.
- Optimization's Neglected Normative Commitments.
- Welfarist Moral Grounding for Transparent AI.
- Humans, AI, and Context: Understanding End-Users' Trust in a Real-World Computer Vision Application.
- Multi-dimensional Discrimination in Law and Machine Learning - A Comparative Overview.
- Reconciling Individual Probability Forecasts✱.
- The Gradient of Generative AI Release: Methods and Considerations.
- In the Name of Fairness: Assessing the Bias in Clinical Record De-identification.
- "How Biased are Your Features?": Computing Fairness Influence Functions with Global Sensitivity Analysis.
- Preventing Discriminatory Decision-making in Evolving Data Streams.
- WEIRD FAccTs: How Western, Educated, Industrialized, Rich, and Democratic is FAccT?
- Trustworthy AI and the Logics of Intersectional Resistance.
- In her Shoes: Gendered Labelling in Crowdsourced Safety Perceptions Data from India.
- The Dataset Multiplicity Problem: How Unreliable Data Impacts Predictions.
- "I wouldn't say offensive but...": Disability-Centered Perspectives on Large Language Models.
- Walking the Walk of AI Ethics: Organizational Challenges and the Individualization of Risk among Ethics Entrepreneurs.
- Algorithmic Transparency from the South: Examining the state of algorithmic transparency in Chile's public administration algorithms.
- Who Should Pay When Machines Cause Harm? Laypeople's Expectations of Legal Damages for Machine-Caused Harm.
- Diagnosing AI Explanation Methods with Folk Concepts of Behavior.
- Certification Labels for Trustworthy AI: Insights From an Empirical Mixed-Method Study.
- The ethical ambiguity of AI data enrichment: Measuring gaps in research ethics norms and practices.
- Making Intelligence: Ethical Values in IQ and ML Benchmarks.
- Saliency Cards: A Framework to Characterize and Compare Saliency Methods.
- Multi-Target Multiplicity: Flexibility and Fairness in Target Specification under Resource Constraints.
- Ghosting the Machine: Judicial Resistance to a Recidivism Risk Assessment Instrument.
- 'Affordances' for Machine Learning.
- Explainable AI is Dead, Long Live Explainable AI!: Hypothesis-driven Decision Support using Evaluative AI.
- Stronger Together: on the Articulation of Ethical Charters, Legal Tools, and Technical Documentation in ML.
- Simplicity Bias Leads to Amplified Performance Disparities.
- On the Independence of Association Bias and Empirical Fairness in Language Models.
- Envisioning Equitable Speech Technologies for Black Older Adults.
- Group-Fair Classification with Strategic Agents.
- The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice.
- Domain Adaptive Decision Trees: Implications for Accuracy and Fairness.
- Algorithmic Transparency and Accountability through Crowdsourcing: A Study of the NYC School Admission Lottery.
- Rethinking Transparency as a Communicative Constellation.
- On the Praxes and Politics of AI Speech Emotion Recognition.
- It's about power: What ethical concerns do software engineers have, and what do they (feel they can) do about them?
- Does AI-Assisted Fact-Checking Disproportionately Benefit Majority Groups Online?
- Algorithms as Social-Ecological-Technological Systems: an Environmental Justice Lens on Algorithmic Audits.
- The Privacy-Bias Tradeoff: Data Minimization and Racial Disparity Assessments in U.S. Government.
- AI's Regimes of Representation: A Community-centered Study of Text-to-Image Models in South Asia.
- A Theory of Auditability for Allocation and Social Choice Mechanisms.
- Representation in AI Evaluations.
- Detecting disparities in police deployments using dashcam data.
- Delayed and Indirect Impacts of Link Recommendations.
- Striving for Affirmative Algorithmic Futures: How the Social Sciences can Promote more Equitable and Just Algorithmic System Design.
- Can Workers Meaningfully Consent to Workplace Wellbeing Technologies?
- Invigorating Ubuntu Ethics in AI for healthcare: Enabling equitable care.
- Honor Ethics: The Challenge of Globalizing Value Alignment in AI.
- Power and Resistance in the Twitter Bias Discourse.
- Runtime Monitoring of Dynamic Fairness Properties.
- Data Collaboratives with the Use of Decentralised Learning.
- Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms that Optimize Predictive Accuracy.
- Care and Coordination in Algorithmic Systems: An Economies of Worth Approach.
- You Sound Depressed: A Case Study on Sonde Health's Diagnostic Use of Voice Analysis AI.
- Harms from Increasingly Agentic Algorithmic Systems.
- How Redundant are Redundant Encodings? Blindness in the Wild and Racial Disparity when Race is Unobserved.
- On the Site of Predictive Justice.
- Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making.
- Investigating Practices and Opportunities for Cross-functional Collaboration around AI Fairness in Industry Practice.
- Your Browsing History May Cost You: A Framework for Discovering Differential Pricing in Non-Transparent Markets.
- Add-Remove-or-Relabel: Practitioner-Friendly Bias Mitigation via Influential Fairness.
- FairAssign: Stochastically Fair Driver Assignment in Gig Delivery Platforms.
- Algorithmic Decisions, Desire for Control, and the Preference for Human Review over Algorithmic Review.
- Gender Animus Can Still Exist Under Favorable Disparate Impact: a Cautionary Tale from Online P2P Lending.
- "I Think You Might Like This": Exploring Effects of Confidence Signal Patterns on Trust in and Reliance on Conversational Recommender Systems.
- Algorithmic Unfairness through the Lens of EU Non-Discrimination Law: Or Why the Law is not a Decision Tree.
- On (assessing) the fairness of risk score models.
- UNFair: Search Engine Manipulation, Undetectable by Amortized Inequity.
- Datafication Genealogies beyond Algorithmic Fairness: Making Up Racialised Subjects.
- Maximal fairness.
- Augmented Datasheets for Speech Datasets and Ethical Decision-Making.
- To Be High-Risk, or Not To Be - Semantic Specifications and Implications of the AI Act's High-Risk AI Applications and Harmonised Standards.
- Implementing Fairness Constraints in Markets Using Taxes and Subsidies.
- AI in the Public Eye: Investigating Public AI Literacy Through AI Art.
- Questioning the ability of feature-based explanations to empower non-experts in robo-advised financial decision-making.
- On the Impact of Explanations on Understanding of Algorithmic Decision-Making.
- Addressing contingency in algorithmic (mis)information classification: Toward a responsible machine learning agenda.
- "We try to empower them" - Exploring Future Technologies to Support Migrant Jobseekers.
- Robustness Implies Fairness in Causal Algorithmic Recourse.
- Bias on Demand: A Modelling Framework That Generates Synthetic Data With Bias.
- ACROCPoLis: A Descriptive Framework for Making Sense of Fairness.
- Towards Labor Transparency in Situated Computational Systems Impact Research.
- Measuring and mitigating voting access disparities: a study of race and polling locations in Florida and North Carolina.
- Which Stereotypes Are Moderated and Under-Moderated in Search Engine Autocompletion?
- Ethical considerations in the early detection of Alzheimer's disease using speech and AI.
- Co-Design Perspectives on Algorithm Transparency Reporting: Guidelines and Prototypes.
- More Data Types More Problems: A Temporal Analysis of Complexity, Stability, and Sensitivity in Privacy Policies.
- Emotions and Dynamic Assemblages: A Study of Automated Social Security Using Qualitative Longitudinal Research.
- Regulating ChatGPT and other Large Generative AI Models.
- On the Richness of Calibration.
- The role of explainable AI in the context of the AI Act.
- The Dimensions of Data Labor: A Road Map for Researchers, Activists, and Policymakers to Empower Data Producers.
- Going public: the role of public participation approaches in commercial AI labs.
- Contrastive Language-Vision AI Models Pretrained on Web-Scraped Multimodal Data Exhibit Sexual Objectification Bias.
- Understanding accountability in algorithmic supply chains.
- Explainability in AI Policies: A Critical Review of Communications, Reports, Regulations, and Standards in the EU, US, and UK.
- Disentangling and Operationalizing AI Fairness at LinkedIn.
- Enhancing AI fairness through impact assessment in the European Union: a legal and computer science perspective.
- "I'm fully who I am": Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation.
- AI Regulation Is (not) All You Need.
- Diverse Perspectives Can Mitigate Political Bias in Crowdsourced Content Moderation.
- The Devil is in the Details: Interrogating Values Embedded in the Allegheny Family Screening Tool.
- A Systematic Review of Ethics Disclosures in Predictive Mental Health Research.
- An Empirical Analysis of Racial Categories in the Algorithmic Fairness Literature.
- A Sociotechnical Audit: Assessing Police Use of Facial Recognition.
- Fairer Together: Mitigating Disparate Exposure in Kemeny Rank Aggregation.
- Can Querying for Bias Leak Protected Attributes? Achieving Privacy With Smooth Sensitivity.
- Towards a Science of Human-AI Decision Making: An Overview of Design Space in Empirical Human-Subject Studies.
- (Anti)-Intentional Harms: The Conceptual Pitfalls of Emotion AI in Education.
- Organizational Governance of Emerging Technologies: AI Adoption in Healthcare.
- Navigating the Audit Landscape: A Framework for Developing Transparent and Auditable XR.
- Group fairness without demographics using social networks.
- Taking Algorithms to Courts: A Relational Approach to Algorithmic Accountability.
- Co-Designing for Transparency: Lessons from Building a Document Organization Tool in the Criminal Justice Domain.
- Examining risks of racial biases in NLP tools for child protective services.
- Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale.
- What's fair is... fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning: JustEFAB.
- Personalized Pricing with Group Fairness Constraint.
- Auditing Cross-Cultural Consistency of Human-Annotated Labels for Recommendation Systems.
- The Progression of Disparities within the Criminal Justice System: Differential Enforcement and Risk Assessment Instruments.
- The Misuse of AUC: What High Impact Risk Assessment Gets Wrong.
- Counterfactual Prediction Under Outcome Measurement Error.
- Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods.
- Arbitrary Decisions are a Hidden Cost of Differentially Private Training.
- Interrogating the T in FAccT.
- Reducing Access Disparities in Networks using Edge Augmentation✱.
- The Many Faces of Fairness: Exploring the Institutional Logics of Multistakeholder Microlending Recommendation.
- Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and Equity.
- Help or Hinder? Evaluating the Impact of Fairness Metrics and Algorithms in Visualizations for Consensus Ranking.
- Bias Against 93 Stigmatized Groups in Masked Language Models and Downstream Sentiment Classification Tasks.
- Representation, Self-Determination, and Refusal: Queer People's Experiences with Targeted Advertising.
- Capturing Humans' Mental Models of AI: An Item Response Theory Approach.
- Representation Online Matters: Practical End-to-End Diversification in Search and Recommender Systems.
- Using Supervised Learning to Estimate Inequality in the Size and Persistence of Income Shocks.
- Skin Deep: Investigating Subjectivity in Skin Tone Annotations for Computer Vision Benchmark Datasets.
- Discrimination through Image Selection by Job Advertisers on Facebook.
- On The Impact of Machine Learning Randomness on Group Fairness.
- Detection and Mitigation of Algorithmic Bias via Predictive Parity.
- Fairness Auditing in Urban Decisions using LP-based Data Combination.
- The Slow Violence of Surveillance Capitalism: How Online Behavioral Advertising Harms People.
- Bias as Boundary Object: Unpacking The Politics Of An Austerity Algorithm Using Bias Frameworks.
- Legal Taxonomies of Machine Bias: Revisiting Direct Discrimination.
- Achieving Diversity in Counterfactual Explanations: a Review and Discussion.
- Disparities in Text-to-Image Model Concept Possession Across Languages.
- Reconciling Governmental Use of Online Targeting With Democracy.
- Queer In AI: A Case Study in Community-Led Participatory AI.
- Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling.
- Mean Parity Fair Regression in RKHS.
- Fair Representation Learning with Unreliable Labels.
- Efficient fair PCA for fair representation learning.
- Revisiting Fair-PAC Learning and the Axioms of Cardinal Welfare.
- Scalable Spectral Clustering with Group Fairness Constraints.
- Fast Feature Selection with Fairness Constraints.
- Improved Approximation for Fair Correlation Clustering.
- MMD-B-Fair: Learning Fair Representations with Statistical Testing.
- Doubly Fair Dynamic Pricing.
- Stochastic Methods for AUC Optimization subject to AUC-based Fairness Constraints.
- Reinforcement Learning with Stepwise Fairness Constraints.
- Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition.