Jennifer Wortman Vaughan

Orcid: 0000-0002-7807-2018

Affiliations:
  • University of California, Los Angeles, USA


According to our database1, Jennifer Wortman Vaughan authored at least 93 papers between 2004 and 2024.

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Bibliography

2024
Tinker, Tailor, Configure, Customize: The Articulation Work of Contextualizing an AI Fairness Checklist.
Proc. ACM Hum. Comput. Interact., 2024

An Equivalence Between Fair Division and Wagering Mechanisms.
Manag. Sci., 2024

Supporting Industry Computing Researchers in Assessing, Articulating, and Addressing the Potential Negative Societal Impact of Their Work.
CoRR, 2024

(De)Noise: Moderating the Inconsistency Between Human Decision-Makers.
CoRR, 2024

Canvil: Designerly Adaptation for LLM-Powered User Experiences.
CoRR, 2024

"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

2023
Greedy Algorithm Almost Dominates in Smoothed Contextual Bandits.
SIAM J. Comput., April, 2023

Incentive-Compatible Forecasting Competitions.
Manag. Sci., March, 2023

Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations.
Proc. ACM Hum. Comput. Interact., 2023

Open Datasheets: Machine-readable Documentation for Open Datasets and Responsible AI Assessments.
CoRR, 2023

Has the Machine Learning Review Process Become More Arbitrary as the Field Has Grown? The NeurIPS 2021 Consistency Experiment.
CoRR, 2023

AI Transparency in the Age of LLMs: A Human-Centered Research Roadmap.
CoRR, 2023

Generation Probabilities Are Not Enough: Exploring the Effectiveness of Uncertainty Highlighting in AI-Powered Code Completions.
CoRR, 2023

GAM Coach: Towards Interactive and User-centered Algorithmic Recourse.
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experience.
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

2022
Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support.
Proc. ACM Hum. Comput. Interact., 2022

Understanding Machine Learning Practitioners' Data Documentation Perceptions, Needs, Challenges, and Desiderata.
Proc. ACM Hum. Comput. Interact., 2022

How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions?
CoRR, 2022

Interpretable Distribution Shift Detection using Optimal Transport.
CoRR, 2022

Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021
Truthful aggregation of budget proposals.
J. Econ. Theory, 2021

Summarize with Caution: Comparing Global Feature Attributions.
IEEE Data Eng. Bull., 2021

GAM Changer: Editing Generalized Additive Models with Interactive Visualization.
CoRR, 2021

A Human-Centered Interpretability Framework Based on Weight of Evidence.
CoRR, 2021

Datasheets for datasets.
Commun. ACM, 2021

Responsible computing during COVID-19 and beyond.
Commun. ACM, 2021

Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning.
Proceedings of the 3rd Workshop on Data Science with Human in the Loop, 2021

From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence.
Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing, 2021

Manipulating and Measuring Model Interpretability.
Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020
The Possibilities and Limitations of Private Prediction Markets.
ACM Trans. Economics and Comput., 2020

Toward fairness in AI for people with disabilities SBG@a research roadmap.
ACM SIGACCESS Access. Comput., 2020

Oracle-efficient Online Learning and Auction Design.
J. ACM, 2020

No-Regret and Incentive-Compatible Online Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI.
Proceedings of the CHI '20: CHI Conference on Human Factors in Computing Systems, 2020

2019
Weight of Evidence as a Basis for Human-Oriented Explanations.
CoRR, 2019

Toward Fairness in AI for People with Disabilities: A Research Roadmap.
CoRR, 2019

Using Search Queries to Understand Health Information Needs in Africa.
Proceedings of the Thirteenth International Conference on Web and Social Media, 2019

The Disparate Effects of Strategic Manipulation.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

Understanding the Effect of Accuracy on Trust in Machine Learning Models.
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019

Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need?
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019

An Equivalence between Wagering and Fair-Division Mechanisms.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Group Fairness for the Allocation of Indivisible Goods.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

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

The Externalities of Exploration and How Data Diversity Helps Exploitation.
Proceedings of the Conference On Learning Theory, 2018

2017
Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research.
J. Mach. Learn. Res., 2017

Incentives and the crowd.
XRDS, 2017

The Double Clinching Auction for Wagering.
Proceedings of the 2017 ACM Conference on Economics and Computation, 2017

A Decomposition of Forecast Error in Prediction Markets.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Tutorial: Making Better Use of the Crowd.
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016
Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems.
J. Artif. Intell. Res., 2016

Oracle-Efficient Learning and Auction Design.
CoRR, 2016

Mathematical foundations for social computing.
Commun. ACM, 2016

The Communication Network Within the Crowd.
Proceedings of the 25th International Conference on World Wide Web, 2016

Bounded Rationality in Wagering Mechanisms.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

2015
Incentivizing high quality crowdwork.
SIGecom Exch., 2015

An axiomatic characterization of wagering mechanisms.
J. Econ. Theory, 2015

2014
Computational social science and social computing.
Mach. Learn., 2014

Market Making with Decreasing Utility for Information.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Removing arbitrage from wagering mechanisms.
Proceedings of the ACM Conference on Economics and Computation, 2014

A general volume-parameterized market making framework.
Proceedings of the ACM Conference on Economics and Computation, 2014

2013
Efficient Market Making via Convex Optimization, and a Connection to Online Learning.
ACM Trans. Economics and Comput., 2013

Online decision making in crowdsourcing markets: theoretical challenges.
SIGecom Exch., 2013

Online Decision Making in Crowdsourcing Markets: Theoretical Challenges (Position Paper).
CoRR, 2013

An axiomatic characterization of adaptive-liquidity market makers.
Proceedings of the fourteenth ACM Conference on Electronic Commerce, 2013

Cost function market makers for measurable spaces.
Proceedings of the fourteenth ACM Conference on Electronic Commerce, 2013

Adaptive Task Assignment for Crowdsourced Classification.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Designing Informative Securities.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Towards Social Norm Design for Crowdsourcing Markets.
Proceedings of the 4th Human Computation Workshop, 2012

Online Task Assignment in Crowdsourcing Markets.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011
An optimization-based framework for automated market-making.
Proceedings of the Proceedings 12th ACM Conference on Electronic Commerce (EC-2011), 2011

2010
Connections between markets and learning.
SIGecom Exch., 2010

A theory of learning from different domains.
Mach. Learn., 2010

The true sample complexity of active learning.
Mach. Learn., 2010

Censored exploration and the dark pool problem.
Commun. ACM, 2010

Maintaining Equilibria During Exploration in Sponsored Search Auctions.
Algorithmica, 2010

A new understanding of prediction markets via no-regret learning.
Proceedings of the Proceedings 11th ACM Conference on Electronic Commerce (EC-2010), 2010

Evolution with Drifting Targets.
Proceedings of the COLT 2010, 2010

Regret Minimization With Concept Drift.
Proceedings of the COLT 2010, 2010

2009
Behavioral experiments on biased voting in networks.
Proc. Natl. Acad. Sci. USA, 2009

2008
Regret to the best vs. regret to the average.
Mach. Learn., 2008

Learning from Multiple Sources.
J. Mach. Learn. Res., 2008

Self-financed wagering mechanisms for forecasting.
Proceedings of the Proceedings 9th ACM Conference on Electronic Commerce (EC-2008), 2008

Complexity of combinatorial market makers.
Proceedings of the Proceedings 9th ACM Conference on Electronic Commerce (EC-2008), 2008

Exploration scavenging.
Proceedings of the Machine Learning, 2008

Learning from Collective Behavior.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

2007
Sponsored Search with Contexts.
Proceedings of the Internet and Network Economics, Third International Workshop, 2007

Privacy-Preserving Belief Propagation and Sampling.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Learning Bounds for Domain Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006
Risk-Sensitive Online Learning.
Proceedings of the Algorithmic Learning Theory, 17th International Conference, 2006

2005
Learning from Data of Variable Quality.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2004
Run the GAMUT: A Comprehensive Approach to Evaluating Game-Theoretic Algorithms.
Proceedings of the 3rd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2004), 2004


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