Workshop Papers
2021
AIES 2021
Paper Presentations
- Artificial Intelligence and the Purpose of Social Systems.
- A Multi-Agent Approach to Combine Reasoning and Learning for an Ethical Behavior.
- Gender Bias and Under-Representation in Natural Language Processing Across Human Languages.
- Blind Justice: Algorithmically Masking Race in Charging Decisions.
- Emergent Unfairness in Algorithmic Fairness-Accuracy Trade-Off Research.
- Fair Machine Learning Under Partial Compliance.
- Minimax Group Fairness: Algorithms and Experiments.
- Co-design and Ethical Artificial Intelligence for Health: Myths and Misconceptions.
- Blacklists and Redlists in the Chinese Social Credit System: Diversity, Flexibility, and Comprehensiveness.
- Reflexive Design for Fairness and Other Human Values in Formal Models.
- On the Validity of Arrest as a Proxy for Offense: Race and the Likelihood of Arrest for Violent Crimes.
- Hard Choices and Hard Limits in Artificial Intelligence.
- Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like Biases.
- Machine Learning Practices Outside Big Tech: How Resource Constraints Challenge Responsible Development.
- Fairness and Data Protection Impact Assessments.
- Towards Unbiased and Accurate Deferral to Multiple Experts.
- Algorithmic Hiring in Practice: Recruiter and HR Professional’s Perspectives on AI Use in Hiring.
- Scaling Guarantees for Nearest Counterfactual Explanations.
- Ethically Compliant Planning within Moral Communities.
- Precarity: Modeling the Long Term Effects of Compounded Decisions on Individual Instability.
- Moral Disagreement and Artificial Intelligence.
- FairOD: Fairness-aware Outlier Detection.
- Surveilling Surveillance: Estimating the Prevalence of Surveillance Cameras with Street View Data.
- On the Privacy Risks of Model Explanations.
- Measuring Automated Influence: Between Empirical Evidence and Ethical Values.
- Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communities.
- Alienation in the AI-Driven Workplace.
Poster Presentations
- The Grey Hoodie Project: Big Tobacco, Big Tech, and the Threat on Academic Integrity.
- Persistent Anti-Muslim Bias in Large Language Models.
- Are AI Ethics Conferences Different and More Diverse Compared to Traditional Computer Science Conferences?
- Ethical Implementation of Artificial Intelligence to Select Embryos in In Vitro Fertilization.
- Measuring Model Biases in the Absence of Ground Truth.
- Accounting for Model Uncertainty in Algorithmic Discrimination.
- Beyond Reasonable Doubt: Improving Fairness in Budget-Constrained Decision Making using Confidence Thresholds.
- Person, Human, Neither: The Dehumanization Potential of Automated Image Tagging.
- Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs.
- Automating Procedurally Fair Feature Selection in Machine Learning.
- Explainable AI and Adoption of Financial Algorithmic Advisors: An Experimental Study.
- Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty.
- Ensuring Fairness under Prior Probability Shifts.
- Envisioning Communities: A Participatory Approach Towards AI for Social Good.
- AI Alignment and Human Reward.
- Fairness and Machine Fairness.
- Reconfiguring Diversity and Inclusion for AI Ethics.
- Algorithmic Audit of Italian Car Insurance: Evidence of Unfairness in Access and Pricing.
- Modeling and Guiding the Creation of Ethical Human-AI Teams.
- What’s Fair about Individual Fairness?
- Learning to Generate Fair Clusters from Demonstrations.
- Ethical Obligations to Provide Novelty.
- Computing Plans that Signal Normative Compliance.
- An AI Ethics Course Highlighting Explicit Ethical Agents.
- The Dangers of Drowsiness Detection: Differential Performance, Downstream Impact, and Misuses.
- Designing Shapelets for Interpretable Data-Agnostic Classification.
- Computer Vision and Conflicting Values: Describing People with Automated Alt Text.
- Who Gets What, According to Whom? An Analysis of Fairness Perceptions in Service Allocation.
- The Earth Is Flat and the Sun Is Not a Star: The Susceptibility of GPT-2 to Universal Adversarial Triggers.
- Situated Accountability: Ethical Principles, Certification Standards, and Explanation Methods in Applied AI.
- Can We Obtain Fairness For Free?
- Monitoring AI Services for Misuse.
- Towards Equity and Algorithmic Fairness in Student Grade Prediction.
- The Ethical Gravity Thesis: Marrian Levels and the Persistence of Bias in Automated Decision-making Systems.
- Exciting, Useful, Worrying, Futuristic: Public Perception of Artificial Intelligence in 8 Countries.
- Age Bias in Emotion Detection: An Analysis of Facial Emotion Recognition Performance on Young, Middle-Aged, and Older Adults.
- AI and Shared Prosperity.
- Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End.
- Becoming Good at AI for Good.
- Measuring Group Advantage: A Comparative Study of Fair Ranking Metrics.
- A Framework for Understanding AI-Induced Field Change: How AI Technologies are Legitimized and Institutionalized.
- Ethical Data Curation for AI: An Approach based on Feminist Epistemology and Critical Theories of Race.
- Risk Identification Questionnaire for Detecting Unintended Bias in the Machine Learning Development Lifecycle.
- Participatory Algorithmic Management: Elicitation Methods for Worker Well-Being Models.
- Feeding the Beast: Superintelligence, Corporate Capitalism and the End of Humanity.
- The Deepfake Detection Dilemma: A Multistakeholder Exploration of Adversarial Dynamics in Synthetic Media.
- RAWLSNET: Altering Bayesian Networks to Encode Rawlsian Fair Equality of Opportunity.
- Fair Equality of Chances for Prediction-based Decisions.
- Towards Accountability in the Use of Artificial Intelligence for Public Administrations.
- How Do the Score Distributions of Subpopulations Influence Fairness Notions?
- More Similar Values, More Trust? - the Effect of Value Similarity on Trust in Human-Agent Interaction.
- Causal Multi-level Fairness.
- Unpacking the Expressed Consequences of AI Research in Broader Impact Statements.
- Measuring Lay Reactions to Personal Data Markets.
- Epistemic Reasoning for Machine Ethics with Situation Calculus.
- Disparate Impact of Artificial Intelligence Bias in Ridehailing Economy’s Price Discrimination Algorithms.
- Understanding the Representation and Representativeness of Age in AI Data Sets.
- Quantum Fair Machine Learning.
- Fair Bayesian Optimization.
- We Haven’t Gone Paperless Yet: Why the Printing Press Can Help Us Understand Data and AI.
- Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective.
- GAEA: Graph Augmentation for Equitable Access via Reinforcement Learning.
- Face Mis-ID: An Interactive Pedagogical Tool Demonstrating Disparate Accuracy Rates in Facial Recognition.
- The Theory, Practice, and Ethical Challenges of Designing a Diversity-Aware Platform for Social Relations.
- A Step Toward More Inclusive People Annotations for Fairness.
- Fairness in the Eyes of the Data: Certifying Machine-Learning Models.
- Rawlsian Fair Adaptation of Deep Learning Classifiers.
- FaiR-N: Fair and Robust Neural Networks for Structured Data.
- Machine Learning and the Meaning of Equal Treatment.
- Digital Voodoo Dolls.
- Comparing Equity and Effectiveness of Different Algorithms in an Application for the Room Rental Market.
- Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring.
- Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation.
- Governing Algorithmic Systems with Impact Assessments: Six Observations.
- A Human-in-the-loop Framework to Construct Context-aware Mathematical Notions of Outcome Fairness.
- Who’s Responsible? Jointly Quantifying the Contribution of the Learning Algorithm and Data.
- RelEx: A Model-Agnostic Relational Model Explainer.
- Skilled and Mobile: Survey Evidence of AI Researchers’ Immigration Preferences.
FATES 2021
- Automating Fairness Configurations for Machine Learning.
- Fairness beyond “equal”: The Diversity Searcher as a Tool to Detect and Enhance the Representation of Socio-political Actors in News Media.
- Characterizing and Comparing COVID-19 Misinformation Across Languages, Countries and Platforms.
- Political Polarization and Platform Migration: : A Study of Parler and Twitter Usage by United States of America Congress Members.
- Auditing Source Diversity Bias in Video Search Results Using Virtual Agents.
- AI Principles in Identifying Toxicity in Online Conversation: Keynote at the Third Workshop on Fairness, Accountability, Transparency, Ethics and Society on the Web.
Others
2020
AIES 2020
Paper Presentations
- Exploring AI Futures Through Role Play.
- Activism by the AI Community: Analysing Recent Achievements and Future Prospects.
- Fair Allocation through Selective Information Acquisition.
- The Problem with Intelligence: Its Value-Laden History and the Future of AI.
- Learning Occupational Task-Shares Dynamics for the Future of Work.
- Social Contracts for Non-Cooperative Games.
- The AI Liability Puzzle and a Fund-Based Work-Around.
- Algorithmic Fairness from a Non-ideal Perspective.
- Bayesian Sensitivity Analysis for Offline Policy Evaluation.
- Biased Priorities, Biased Outcomes: Three Recommendations for Ethics-oriented Data Annotation Practices.
- Defining AI in Policy versus Practice.
- “How do I fool you?”: Manipulating User Trust via Misleading Black Box Explanations.
- Normative Principles for Evaluating Fairness in Machine Learning.
- Good Explanation for Algorithmic Transparency.
- Does AI Qualify for the Job?: A Bidirectional Model Mapping Labour and AI Intensities.
- An Empirical Approach to Capture Moral Uncertainty in AI.
- When Trusted Black Boxes Don’t Agree: Incentivizing Iterative Improvement and Accountability in Critical Software Systems.
- When Your Only Tool Is A Hammer: Ethical Limitations of Algorithmic Fairness Solutions in Healthcare Machine Learning.
- Ethics for AI Writing: The Importance of Rhetorical Context.
- Diversity and Inclusion Metrics in Subset Selection.
- Learning Norms from Stories: A Prior for Value Aligned Agents.
- Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours.
- Technocultural Pluralism: A “Clash of Civilizations” in Technology?
- Beyond Near- and Long-Term: Towards a Clearer Account of Research Priorities in AI Ethics and Society.
- Algorithmized but not Atomized? How Digital Platforms Engender New Forms of Worker Solidarity in Jakarta.
- Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing.
- Human Comprehension of Fairness in Machine Learning.
- What’s Next for AI Ethics, Policy, and Governance? A Global Overview.
- Trade-offs in Fair Redistricting.
- CERTIFAI: A Common Framework to Provide Explanations and Analyse the Fairness and Robustness of Black-box Models.
- The Offense-Defense Balance of Scientific Knowledge: Does Publishing AI Research Reduce Misuse?
- Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods.
- U.S. Public Opinion on the Governance of Artificial Intelligence.
- Different “Intelligibility” for Different Folks.
Poster Presentations
- AI and Holistic Review: Informing Human Reading in College Admissions.
- Robot Rights?: Let’s Talk about Human Welfare Instead.
- Artificial Artificial Intelligence: Measuring Influence of AI ‘Assessments’ on Moral Decision-Making.
- A Just Approach Balancing Rawlsian Leximax Fairness and Utilitarianism.
- Should Artificial Intelligence Governance be Centralised?: Design Lessons from History.
- An Invitation to System-wide Algorithmic Fairness.
- Hard Choices in Artificial Intelligence: Addressing Normative Uncertainty through Sociotechnical Commitments.
- Toward Implementing the Agent-Deed-Consequence Model of Moral Judgment in Autonomous Vehicles.
- Investigating the Impact of Inclusion in Face Recognition Training Data on Individual Face Identification.
- Proposal for Type Classification for Building Trust in Medical Artificial Intelligence Systems.
- Adoption Dynamics and Societal Impact of AI Systems in Complex Networks.
- Auditing Algorithms: On Lessons Learned and the Risks of Data Minimization.
- More Than “If Time Allows”: The Role of Ethics in AI Education.
- A Geometric Solution to Fair Representations.
- Measuring Fairness in an Unfair World.
- Towards Just, Fair and Interpretable Methods for Judicial Subset Selection.
- Monitoring Misuse for Accountable ‘Artificial Intelligence as a Service’.
- “The Global South is everywhere, but also always somewhere”: National Policy Narratives and AI Justice.
- Ethics of Food Recommender Applications.
- Artificial Intelligence and Indigenous Perspectives: Protecting and Empowering Intelligent Human Beings.
- The Windfall Clause: Distributing the Benefits of AI for the Common Good.
- Steps Towards Value-Aligned Systems.
- Contextual Analysis of Social Media: The Promise and Challenge of Eliciting Context in Social Media Posts with Natural Language Processing.
- The Perils of Objectivity: Towards a Normative Framework for Fair Judicial Decision-Making.
- FACE: Feasible and Actionable Counterfactual Explanations.
- Balancing the Tradeoff Between Clustering Value and Interpretability.
- Data Augmentation for Discrimination Prevention and Bias Disambiguation.
- Meta Decision Trees for Explainable Recommendation Systems.
- Why Reliabilism Is not Enough: Epistemic and Moral Justification in Machine Learning.
- Social and Governance Implications of Improved Data Efficiency.
- Conservative Agency via Attainable Utility Preservation.
- A Deontic Logic for Programming Rightful Machines.
- A Fairness-aware Incentive Scheme for Federated Learning.
- Joint Optimization of AI Fairness and Utility: A Human-Centered Approach.
- Assessing Post-hoc Explainability of the BKT Algorithm.
- Deepfakes for Medical Video De-Identification: Privacy Protection and Diagnostic Information Preservation.
- Arbiter: A Domain-Specific Language for Ethical Machine Learning.
FATES 2020
- A Unifying Framework for Fairness-Aware Influence Maximization.
- Convex Fairness Constrained Model Using Causal Effect Estimators.
- Fairness of Classification Using Users’ Social Relationships in Online Peer-To-Peer Lending.
- Fairness through Equality of Effort.
- Quantifying Gender Bias in Different Corpora.
- Studying Political Bias via Word Embeddings.
- Representativeness of Abortion Legislation Debate on Twitter: A Case Study in Argentina and Chile.
- Mitigating Cognitive Biases in Machine Learning Algorithms for Decision Making.
- Biases on Social Media Data: (Keynote Extended Abstract).
Others
SafeAI 2020
- Fair Enough: Improving Fairness in Budget-Constrained Decision Making Using Confidence Thresholds.
- A Study on Multimodal and Interactive Explanations for Visual Question Answering.
- You Shouldn’t Trust Me: Learning Models Which Conceal Unfairness From Multiple Explanation Methods.
- Algorithmic Discrimination: Formulation and Exploration in Deep Learning-based Face Biometrics.
2019
AIES 2019
Accepted oral papers of AIES 2019
- Killer Robots and Human Dignity
- Legible Normativity for AI Alignment: The Value of Silly Rules
- Reinforcement learning and inverse reinforcement learning with system 1 and system 2
- Building Jiminy Cricket: An Architecture for Moral Agreements Among Stakeholders
- Guiding Prosecutorial Decisions with an Interpretable Statistical Model
- Human Trust Measurement Using an Immersive Virtual Reality Autonomous Vehicle Simulator
- Shared Moral Foundations of Embodied Artificial Intelligence
- Invisible Influence: Artificial Intelligence and the Ethics of Adaptive Choice Architectures
- Active Fairness in Algorithmic Decision Making
- Speaking on Behalf of: Representation, Delegation, and Authority in Computational Text Analysis
- AI + Art = Human
- Fair Transfer Learning with Missing Protected Attributes
- AI Extenders: The Ethical and Societal Implications of Humans Cognitively Extended by AI
- A framework for benchmarking discrimination-aware models in machine learning
- On Influencing Individual Behavior for Reducing Transportation Energy Expenditure in a Large Population
- Robots Can Be More Than Black And White: Examining Racial Bias Towards Robots
- TED: Teaching AI to Explain its Decisions
- How Technological Advances Can Reveal Rights
- Towards a Just Theory of Measurement: A Principled Social Measurement Assurance Program
- Using deceased-donor kidneys to initiate chains of living donor kidney paired donations: algorithm and experimentation
- Regulating Lethal and Harmful Autonomy: Drafting a Protocol VI of the Convention on Certain Conventional Weapons
- Understanding Black Box Model Behavior through Subspace Explanations
- Theories of parenting and their application to artificial intelligence
- Learning Existing Social Conventions via Observationally Augmented Self-Play
- Inferring Work Task Automatability from AI Expert Evidence
- The Role and Limits of Principles in AI Ethics: Towards a Focus on Tensions
- Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements
- Balancing the Benefits of Autonomous Vehicles
- Tact in Noncompliance: The Need for Pragmatically Apt Responses to Unethical Commands
- Paradoxes in Fair Computer-Aided Decision Making
- Actionable Auditing: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products
- How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness
- Compensation at the Crossroads: Autonomous Vehicles and Alternative Victim Compensation Schemes
- Incomplete Contracting and AI Alignment
Accepted poster papers of AIES 2019
- (When) Can AI Bots Lie?
- Crowdsourcing with Fairness, Diversity and Budget Constraints
- Modelling and Influencing the AI Bidding War: A Research Agenda
- IMLI: An Incremental Framework for MaxSAT-Based Learning of Interpretable Classification Rules
- The Heart of the Matter: Patient Autonomy as a Model for the Wellbeing of Technology Users
- Counterfactual Fairness in Text Classification through Robustness
- Taking Advantage of Multitask Learning for Fair Classification
- Explanatory Interactive Machine Learning
- Multiaccuracy: Black-Box Post-Processing for Fairness in Classification
- Mapping Informal Settlements in Developing Countries using Machine Learning and Low Resolution Multi-spectral Data
- Equalized Odds Implies Partially Equalized Outcomes Under Realistic Assumptions
- Costs and Benefits of Fair Representation Learning
- Ethically Aligned Opportunistic Scheduling for Productive Laziness
- Semantics Derived Automatically from Language Corpora Contain Human-like Moral Choices
- The Right To Confront Your Accuser: Opening the Black Box of Forensic DNA Software
- Algorithmic greenlining: An approach to increase diversity
- Requirements for an Artificial Agent with Norm Competence
- Loss-Aversively Fair Classification
- Epistemic Therapy for Bias in Automated Decision-Making
- Mapping Missing Population in Rural India: A Deep Learning Approach with Satellite Imagery
- Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk
- A Comparative Analysis of Emotion-Detecting AI Systems with Respect to Algorithm Performance and Dataset Diversity
- Framing Artificial Intelligence in American Newspapers
- Degenerate Feedback Loops in Recommender Systems
- Global Explanations of Neural Networks: Mapping the Landscape of Predictions
- “Scary Robots”: Examining Public Responses to AI
- TrolleyMod v1.0: An Open-Source Simulation and Data-Collection Platform for Ethical Decision Making in Autonomous Vehicles
- Uncovering and Mitigating Algorithmic Bias through Learned Latent Structure
- Human-AI Learning Performance in Multi-Armed Bandits
- Perceptions of Domestic Robots’ Normative Behavior Across Cultures
- Toward the Engineering of Virtuous Machines
- A Formal Approach to Explainability
- Rightful Machines and Dilemmas
- The Seductive Allure of Artificial Intelligence-Powered Neurotechnology
- What are the biases in my word embedding?
FATES 2019
- Achieving Differential Privacy and Fairness in Logistic Regression
- Unsupervised Topic Extraction from Privacy Policies
- Collaborative Explanation of Deep Models with Limited Interaction for Trade Secret and Privacy Preservation
- Algorithms for Fair Team Formation in Online Labour Marketplaces
- Fairness in the social influence maximization problem
- Hegemony in Social Media and the effect of recommendations
- Managing Bias in AI
- Privacy-aware Linked Widgets
- Privacy and Transparency within the 4IR: Two faces of the same coin
- Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification
- On Preserving Sensitive Information of Multiple Aspect Trajectories In-House
- Quantifying the Impact of User Attention on Fair Group Representation in Ranked Lists
- Trust and trustworthiness in social recommender systems
- Empirical analysis of bias in voice based personal assistants
- Black Hat Trolling, White Hat Trolling, and Hacking the Attention Landscape
- Uncovering Social Media Bots: a Transparency-focused Approach
- Can Location-Based Searches Create Exposure Bias?, discussion paper
- What’s in a Name? The Need for Scalable External Audit Infrastructure, discussion paper
- In Defense of Synthetic Data, discussion paper
2018
AIES 2018
Accepted oral papers of AIES 2018
- Measuring and Mitigating Unintended Bias in Text Classification
- Value Alignment, Fair Play, and the Rights of Service Robots
- Regulating Artificial Intelligence: Proposal for a Global Solution
- Using Education as a Model to Capture Good-Faith Effort for Autonomous Systems
- Exploiting moral values to choose the right norms
- Software Malpractice in the Age of AI: A Guide for the Wary Tech Company
- Non-Discriminatory Machine Learning through Convex Fairness Criteria
- Fair Forests: Regularized Tree Induction to Minimize Model Bias
- A framework for grounding the moral status of intelligent machines
- Rethinking AI Strategy and Policy as Entangled Super Wicked Problems
- An Agile Ethical/Legal Model for the International and National Governance of AI and Robotics
- Incorrigibility in the CIRL Framework
- When Do People Want AI to Make Decisions?
- Toward Non-Intuition-Based Machine Ethics
- Embodiment, Anthropomorphism, and Intellectual Property Rights for AI Creations
- Partially Generative Neural Networks for Gang Crime Classification with Partial Information
- Detecting Bias in Black-Box Models Using Transparent Model Distillation
- Designing Non-greedy Reinforcement Learning Agents with Diminishing Reward Shaping
- The Dark side of Ethical Robots
- Jill Watson Doesn’t Care if You’re Pregnant: Grounding AI Ethics in Empirical Studies
- Purple Feed: Identifying High Consensus News Posts on Social Media
- A Formalization of Kant’s Second Formulation of the Categorical Imperative
- Regulating Autonomous Vehicles: A Policy Proposal
- Towards an “Ethics by Design” methodology for AI research projects
- Regulating for ‘normal AI accidents’: operational lessons for the responsible governance of AI deployment
- On the distinction between implicit and explicit ethical agency
- A Computational Model of Commonsense Moral Decision Making
- Socially-Aware Navigation Using Topological Maps and Social Norm Learning
- Transparency and Explanation in Deep Reinforcement Learning Neural Networks
- Ethical Challenges in Data-Driven Dialogue Systems
- An AI Race: Rhetoric and Risks
- Preferences and Ethical Principles in Decision Making
Accepted poster papers of AIES 2018
- An Autonomous Architecture that Protects the Right to Privacy
- Utilizing Housing Resources for Homeless Youth Through the Lens of Multiple Multi-Dimensional Knapsacks
- Real-Time Inference of User Types to Assist with more Inclusive and Diverse Social Media Activism Campaigns
- Understanding Convolutional Networks with APPLE : Automatic Patch Pattern Labeling for Explanation
- Companion Robots: the Hallucinatory Danger of Human-Robot Interactions
- From Algorithmic Black Boxes to Adaptive White Boxes: Declarative Decision-Theoretic Ethical Programs as Codes of Ethics
- Privacy-preserving Machine Learning Based Data Analytics on Edge Devices
- Inverse norm conflict resolution
- Fairness in Relational Domains
- Sociotechnical Systems and Ethics in the Large
- Margins and opportunity
- Opportunities and Challenges for Artificial Intelligence in India
- Mitigating Unwanted Biases with Adversarial Learning
- Fairness in Deceased Organ Matching
- What’s up with Privacy? : User Preferences and Privacy Concerns in Intelligent Personal Assistants
- Data Driven Platform for Organizing Scientific Articles Relevant to Biomimicry
- Towards Provably Moral AI Agents in Bottom-up Learning Frameworks
- Meritocratic Fairness for Infinite and Contextual Bandits
- Socialbots supporting human rights
- Ethics by Design: Necessity or Curse?
- Always Lurking: Understanding and Mitigating Bias in Online Human Trafficking Detection
- Modeling Epistemological Principles for Bias Mitigation in AI Systems: An Illustration in Hiring Decisions
- Impacts on Trust of Healthcare AI
- Sub-committee Approval Voting and Generalized Justified Representation Axioms
- Rationalization: A Neural Machine Translation Approach to Generating Natural Language Explanations
- Norms, Rewards, and the Intentional Stance: Comparing Machine Learning Approaches to Ethical Training
- Cake, death, and trolleys: dilemmas as benchmarks of ethical decision-making
- Adapting a Kidney Exchange Algorithm to Align with Human Values
- Towards Composable Bias Rating of AI Systems
FAT/ML 2018
- Achieving Fairness through Adversarial Learning: an Application to Recidivism Prediction
- Actionable Recourse in Linear Classification
- Axiomatic Characterization of Data-Driven Influence Measures for Classification
- Blind Justice: Fairness with Encrypted Sensitive Attributes
- Darling or Babygirl? Investigating Stylistic Bias in Sentiment Analysis
- Datasheets for Datasets
- Debiasing Representations by Removing Unwanted Variation Due to Protected Attributes
- Does Removing Stereotype Priming Remove Bias? A Pilot Human-Robot Interaction Study
- Enhancing Human Decision Making via Assignment Optimization
- Equal Protection Under the Algorithm: A Legal-Inspired Framework for Identifying Discrimination in Machine Learning
- “Fair” Risk Assessments: A Precarious Approach for Criminal Justice Reform
- Fairness Through Computationally-Bounded Awareness
- Game-theoretic Interpretability for Temporal Modeling
- Gradient Reversal Against Discrimination
- Group Fairness Under Composition
- Individual Fairness Under Composition
- InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender Diversity
- Learning under selective labels in the presence of expert consistency
- Modelling Mistrust in End-of-Life Care
- On Formalizing Fairness in Prediction with ML
- Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
- Probably Approximately Metric-Fair Learning
- A Broader View on Bias in Automated Decision-Making: Reflecting on Epistemology and Dynamics
- Training Fairness-Constrained Classifiers To Generalize
- Turing Box: An Experimental Platform for the Evaluation of AI Systems
- Using image fairness representations in diversity-based re-ranking for recommendations
- Welfare and Distributional Impacts of Fair Classification
- Women also Snowboard: Overcoming Bias in Captioning Models
2017
FAT/ML 2017
- From Parity to Preference-based Notions of Fairness in Classification
- The Authority of “Fair” in Machine Learning
- Logics and practices of transparency and opacity in real-world applications of public sector machine learning
- Learning Fair Classifiers: A Regularization Approach
- A Convex Framework for Fair Regression
- Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations
- Multisided Fairness for Recommendation
- Fairer and more accurate but for whom?
- Decoupled classifiers for fair and efficient ML
- Decision making with limited feedback: Error bounds for recidivism prediction and predictive policing
- On Fairness Diversity and Randomness in Algorithmic Decision Making
- Better Fair Algorithms for Contextual Bandits
- Fair Algorithms for Infinite Contextual Bandits
- The causal impact of bail on case outcomes for indigent defendants
- New Fairness Metrics for Recommendation that Embrace Differences
2016
FAT/ML 2016
- Iterative Orthogonal Feature Projection for Diagnosing Bias in Black-Box Models
- Price of Transparency in Strategic Machine Learning
- Fairness as a Program Property
- Exploring or Exploiting? Social and Ethical Implications of Autonomous Experimentation in AI
- How to Be Fair and Diverse
- Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments
- The Case for Temporal Transparency: Detecting Policy Change Events in Black-Box Decision Making Systems
- Fair Learning in Markovian Environments
- Rawlsian Fairness for Machine Learning
- Inherent Trade-Offs in the Fair Determination of Risk Scores
- A Statistical Framework for Fair Predictive Algorithms
- Measuring Fairness in Ranked Outputs
- Fairness Beyond Disparate Treatment and Disparate Impact: Learning Classification without Disparate Mistreatment
2015
FAT/ML 2015
- Fairness Constraints: A Mechanism for Fair Classification
- A Confidence-Based Approach for Balancing Fairness and Accuracy
- Towards Diagnosing Accuracy Loss in Discrimination-Aware Classification: An Application to Predictive Policing
- On the Relation between Accuracy and Fairness in Binary Classification
2014
FAT/ML 2014
null
2013
Privacy Aspects of Data Mining (PADM 2013) with ICDM 2013
2012
Discrimination and Privacy-Aware Data Mining (DPADM 2012) with ICDM 2012
- Exploring Discrimination: A User-centric Evaluation of Discrimination-Aware Data Mining
- A Study on the Impact of Data Anonymization on Anti-discrimination
- Injecting Discrimination and Privacy Awareness Into Pattern Discovery
- Classifying Socially Sensitive Data Without Discrimination: An Analysis of a Crime Suspect Dataset
- Considerations on Fairness-Aware Data Mining
- Discriminatory Decision Policy Aware Classification
- Discovering Gender Discrimination in Project Funding