Hoda Heidari

Orcid: 0000-0003-3710-4076

According to our database1, Hoda Heidari authored at least 55 papers between 2011 and 2024.

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Bibliography

2024
Beneficent Intelligence: A Capability Approach to Modeling Benefit, Assistance, and Associated Moral Failures Through AI Systems.
Minds Mach., December, 2024

A Comparison of the Analysis of Methods for Feature Extraction and Classification in SSVEP BCIs.
SN Comput. Sci., April, 2024

Studying Up Public Sector AI: How Networks of Power Relations Shape Agency Decisions Around AI Design and Use.
Proc. ACM Hum. Comput. Interact., 2024

Rethinking Distance Metrics for Counterfactual Explainability.
CoRR, 2024

'Simulacrum of Stories': Examining Large Language Models as Qualitative Research Participants.
CoRR, 2024

On The Stability of Moral Preferences: A Problem with Computational Elicitation Methods.
CoRR, 2024

On the Pros and Cons of Active Learning for Moral Preference Elicitation.
CoRR, 2024

Red-Teaming for Generative AI: Silver Bullet or Security Theater?
CoRR, 2024

Fine-Tuning Games: Bargaining and Adaptation for General-Purpose Models.
Proceedings of the ACM on Web Conference 2024, 2024

AI Failure Cards: Understanding and Supporting Grassroots Efforts to Mitigate AI Failures in Homeless Services.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

The Fall of an Algorithm: Characterizing the Dynamics Toward Abandonment.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

The Situate AI Guidebook: Co-Designing a Toolkit to Support Multi-Stakeholder, Early-stage Deliberations Around Public Sector AI Proposals.
Proceedings of the CHI Conference on Human Factors in Computing Systems, 2024

2023
Perspectives on incorporating expert feedback into model updates.
Patterns, July, 2023

Assessing AI Impact Assessments: A Classroom Study.
CoRR, 2023

RELand: Risk Estimation of Landmines via Interpretable Invariant Risk Minimization.
CoRR, 2023

Recentering Validity Considerations through Early-Stage Deliberations Around AI and Policy Design.
CoRR, 2023

A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithms.
Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning, 2023

Informational Diversity and Affinity Bias in Team Growth Dynamics.
Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023

The AI Incident Database as an Educational Tool to Raise Awareness of AI Harms: A Classroom Exploration of Efficacy, Limitations, & Future Improvements.
Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023

Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools.
Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023

From Preference Elicitation to Participatory ML: A Critical Survey & Guidelines for Future Research.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

Moral Machine or Tyranny of the Majority?
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Local Justice and Machine Learning: Modeling and Inferring Dynamic Ethical Preferences toward Allocations.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
On modeling human perceptions of allocation policies with uncertain outcomes.
SIGecom Exch., July, 2022

A Unifying Framework for Combining Complementary Strengths of Humans and ML toward Better Predictive Decision-Making.
CoRR, 2022

A Sandbox Tool to Bias(Stress)-Test Fairness Algorithms.
CoRR, 2022

Bayesian Persuasion for Algorithmic Recourse.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Allocating Opportunities in a Dynamic Model of Intergenerational Mobility (Extended Abstract).
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responses.
Proceedings of the International Conference on Machine Learning, 2022

Four Years of FAccT: A Reflexive, Mixed-Methods Analysis of Research Contributions, Shortcomings, and Future Prospects.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021
Stateful Strategic Regression.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Addressing the Long-term Impact of ML Decisions via Policy Regret.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Allocating Opportunities in a Dynamic Model of Intergenerational Mobility.
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

A Human-in-the-loop Framework to Construct Context-aware Mathematical Notions of Outcome Fairness.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

Fair Equality of Chances for Prediction-based Decisions.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020
On the Desiderata for Online Altruism: Nudging for Equitable Donations.
Proc. ACM Hum. Comput. Interact., 2020

2019
Competitive contagion in networks.
Games Econ. Behav., 2019

A Human-in-the-loop Framework to Construct Context-dependent Mathematical Formulations of Fairness.
CoRR, 2019

Economic Theories of Distributive Justice for Fair Machine Learning.
Proceedings of the Companion of The 2019 World Wide Web Conference, 2019

On the Impact of Choice Architectures on Inequality in Online Donation Platforms.
Proceedings of the World Wide Web Conference, 2019

Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

A Moral Framework for Understanding Fair ML through Economic Models of Equality of Opportunity.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

2018
Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets.
ACM Trans. Economics and Comput., 2018

Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Preventing Disparate Treatment in Sequential Decision Making.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017
A Convex Framework for Fair Regression.
CoRR, 2017

A General Framework for Evaluating Callout Mechanisms in Repeated Auctions.
CoRR, 2017

2016
Tight Policy Regret Bounds for Improving and Decaying Bandits.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Pricing a Low-regret Seller.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2014
Learning from Contagion (Without Timestamps).
Proceedings of the 31th International Conference on Machine Learning, 2014

New Models for Competitive Contagion.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Depth-Workload Tradeoffs for Workforce Organization.
Proceedings of the First AAAI Conference on Human Computation and Crowdsourcing, 2013

2011
Toward optimal vaccination strategies for probabilistic models.
Proceedings of the 20th International Conference on World Wide Web, 2011


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