Accepted for presentation at EC'26
@unpublished{liang2026creative,
author = {Annie Liang and Jay Lu},
title = {Creative Ownership in the Age of {AI}},
year = {2026},
note = {Working paper}
}
Annie Liang
Associate Professor of Economics (with tenure)
Associate Professor of Computer Science (by courtesy)
Northwestern University
Annie Liang is an economic theorist with a focus on artificial intelligence. Her research spans three broad areas: the economic and social implications of AI systems; the use of machine learning and other computational tools in economic modeling; and the optimal design and acquisition of information. Her recent work has examined questions such as how to delegate to AI systems with uncertain alignment, how AI "clones" affect search and matching, the predictive value of large language models across domains, and the implications of generative AI for creative ownership. More broadly, her research develops conceptual frameworks for understanding how AI and machine learning reshape incentives, information, and economic outcomes.
Annie received her S.B. in Mathematics and Economics from MIT and her Ph.D. in Economics from Harvard University, and is a recipient of the NSF CAREER Award.
Research
Working Papers
2026
Accepted for presentation at EC'26
@unpublished{golub2026human,
author = {Benjamin Golub and Annie Liang and Marciano Siniscalchi},
title = {Human or Machine? {A}ssessing {AI}'s Ability to Generate Game-Theory Questions},
year = {2026},
note = {Working paper}
}Accepted for presentation at EC'26
@unpublished{fudenberg2026friend,
author = {Drew Fudenberg and Annie Liang},
title = {Friend or Foe: Delegating to an {AI} whose Alignment is Unknown},
year = {2026},
note = {Working paper}
}Accepted for presentation at EC'26
@unpublished{gao2026llm,
author = {Wayne Gao and Sukjin Han and Annie Liang},
title = {How Well Do {LLMs} Predict Human Behavior? {A} Measure of their Pretrained Knowledge},
year = {2026},
note = {Working paper}
}Extended abstract at EC'25
@unpublished{liang2026clones,
author = {Annie Liang},
title = {Artificial Intelligence Clones},
year = {2026},
note = {Working paper}
}2025
Extended abstract at EC'25
@unpublished{iakovlev2025value,
author = {Andrei Iakovlev and Annie Liang},
title = {The Value of Context: Human versus Algorithmic Evaluators},
year = {2025},
note = {Working paper}
}R&R at Journal of Political Economy
@unpublished{auerbach2025testing,
author = {Eric Auerbach and Annie Liang and Kyohei Okumura and Max Tabord-Meehan},
title = {Testing the Fairness-Accuracy Improvability of Algorithms},
year = {2025},
note = {R\&R at Journal of Political Economy}
}Extended abstract at EC'25
@unpublished{andrews2025transfer,
author = {Isaiah Andrews and Drew Fudenberg and Lihua Lei and Annie Liang and Chaofeng Wu},
title = {The Transfer Performance of Economic Models},
year = {2025},
note = {Working paper}
}2021
@unpublished{liang2021games,
author = {Annie Liang},
title = {Games of Incomplete Information Played by Statisticians},
year = {2021},
note = {Working paper}
}Published Papers
Journal of Political Economy, forthcoming
Extended abstract at EC'22
@article{liang2026fairness,
author = {Annie Liang and Jay Lu and Xiaosheng Mu and Kyohei Okumura},
title = {Algorithm Design: A Fairness-Accuracy Frontier},
journal = {Journal of Political Economy},
note = {Forthcoming},
year = {2026}
}Journal of Economic Literature, accepted
@article{liang2026using,
author = {Annie Liang},
title = {Using Machine Learning to Generate, Clarify, and Improve Economic Models},
journal = {Journal of Economic Literature},
note = {Accepted},
year = {2026}
}Review of Economics and Statistics, 2026
Extended abstract at EC'21 — Exemplary AI and Computation Track Paper
@article{fudenberg2026flexible,
author = {Drew Fudenberg and Wayne Gao and Annie Liang},
title = {How Flexible is that Functional Form? {Q}uantifying the Restrictiveness of Theories},
journal = {Review of Economics and Statistics},
year = {2026}
}Theoretical Economics, 2024
Extended abstract at EC'20
@article{liang2024data,
author = {Annie Liang and Erik Madsen},
title = {Data and Incentives},
journal = {Theoretical Economics},
volume = {19},
number = {1},
pages = {407--448},
year = {2024}
}AEA Papers & Proceedings, 2024
@article{liang2024fairness,
author = {Annie Liang and Jay Lu},
title = {Algorithmic Fairness and Social Welfare},
journal = {AEA Papers and Proceedings},
volume = {114},
pages = {628--632},
year = {2024}
}Journal of Political Economy, 2022
Extended abstract at EC'17
@article{fudenberg2022measuring,
author = {Drew Fudenberg and Jon Kleinberg and Annie Liang and Sendhil Mullainathan},
title = {Measuring the Completeness of Economic Models},
journal = {Journal of Political Economy},
volume = {130},
number = {4},
pages = {956--990},
year = {2022}
}Econometrica, 2022
Extended abstract at EC'21
@article{liang2022dynamically,
author = {Annie Liang and Xiaosheng Mu and Vasilis Syrgkanis},
title = {Dynamically Aggregating Diverse Information},
journal = {Econometrica},
volume = {90},
number = {1},
pages = {47--80},
year = {2022}
}ACM SIGecom Exchanges, 2020
@article{fudenberg2020machine,
author = {Drew Fudenberg and Annie Liang},
title = {Machine Learning for Evaluating and Improving Theories},
journal = {ACM SIGecom Exchanges},
volume = {18},
number = {1},
pages = {4--11},
year = {2020}
}The Quarterly Journal of Economics, 2020
Extended abstract at EC'18
@article{liang2020complementary,
author = {Annie Liang and Xiaosheng Mu},
title = {Complementary Information and Learning Traps},
journal = {Quarterly Journal of Economics},
volume = {135},
number = {1},
pages = {389--448},
year = {2020}
}American Economic Review, 2019
Invited plenary at EC'19 ("Highlights Beyond EC")
@article{fudenberg2019predicting,
author = {Drew Fudenberg and Annie Liang},
title = {Predicting and Understanding Initial Play},
journal = {American Economic Review},
volume = {109},
number = {12},
pages = {4112--4141},
year = {2019}
}Journal of Economic Theory, 2019
@article{liang2019inference,
author = {Annie Liang},
title = {Inference of Preference Heterogeneity from Choice Data},
journal = {Journal of Economic Theory},
volume = {179},
pages = {275--311},
year = {2019}
}Extended abstract at EC'18
@inproceedings{liang2018optimal,
author = {Annie Liang and Xiaosheng Mu and Vasilis Syrgkanis},
title = {Optimal and Myopic Information Acquisition},
booktitle = {Proceedings of the 2018 ACM Conference on Economics and Computation},
year = {2018}
}Teaching
Information and Learning in Economic Theory
I teach a graduate course on information and learning.
Other
Russian Language Textbook
A conversation-first Russian handbook for intermediate and advanced learners.
Contact
Email: liang.annie.h@gmail.com
Kellogg Global Hub
2211 Campus Drive, Evanston IL 60208