EC24 Workshop
Information Acquisition
Workshop Theme
In the modern data-driven world, information acquisition plays a critical role in informed decision-making. This event will explore recent works on acquiring, evaluating, and integrating information from strategic sources, with potential decision-making applications. The workshop will cover topics including elicitation, calibration, decision under falsifiable information, and learning with strategic agents, with invited talks and contributed presentations.
Elicitation. Effective decision-making often relies on gathering high-quality human feedback. The ever-increasing reliance on data-driven decision-making makes the ability to gather high-quality human feedback more critical than ever. This topic discusses how to elicit high-quality information with proper payment, with or without the existence of ground truth.
Calibration. Calibration separates decision-making from prediction into two problems. If a predictor is calibrated, a good performance on a particular decision problem (a.k.a. loss function) transfers to all other decision problems. Multicalibration implies fairness across subgroups. This topic covers recent work producing calibrated predictions in learning.
Decision under falsifiable information. Decision under falsifiable information involves making choices when the information sources are strategic. Decision makers categorize agents based on the information they provide, while the agents can strategically manipulate their information for favorable outcomes at a cost. Two lines of literature relate to this topic: the strategic classification in the CS community, and the fraud-proof mechanism design in the Economics theory community.
Learning with strategic agents. In many online decision problems, the principal's desired information is controlled by self-interested agents. An important question in this domain is designing good incentive schemes or information disclosure policies to influence agents' choices for optimal learning. This topic covers recent developments in searching and incentivized exploration.
Confirmed Speakers
Schedules: July 8
Invited Talks
8:30 - 9:15 am, Yiling Chen. Talk information coming soon.
9:15 - 10:00 am, Aaron Roth. Talk information coming soon.
10:00 - 10:30am, break.
10:30 - 11:15 am, Alex Slivkins. Exploration under myopic behavior: from social learning to incentivized exploration to clinical trials.
Abstract: When myopic decision-makers face a bandit problem, how well do they explore as a collective? We discuss how this issue plays out in several related scenarios, from social learning in bandit environments to incentivized exploration in recommendation systems to incentivized participation in clinical trials.
Based on three recent papers: NeurIPS'23, EC'24, working paper.
11:15 - 12:00 am, Bobby Pakzad-Hurson. Persuaded Search (joint work with Teddy Mekonnen and Zeky Murra-Anton).
Abstract: We consider sequential search by an agent who cannot observe the quality of goods but can acquire information by buying signals from a profit-maximizing principal with limited commitment power. The principal can charge higher prices for more informative signals in any period, but high prices in the future discourage continued search by the agent, thereby reducing the principal's future profits. A unique stationary equilibrium outcome exists, and we show that the principal (i) induces the socially efficient stopping rule, (ii) extracts the full surplus, and (iii) persuades the agent against settling for marginal goods, extending the duration of surplus extraction. However, introducing an additional, free source of information can lead to inefficiency in equilibrium.
Poster Session
July 8, 1-2 pm.
High-Effort Crowds: Limited Liability via Tournaments. Yichi Zhang, Grant Schoenebeck.
Persuading a Learning Agent. Tao Lin, Yiling Chen.
Bandit Social Learning: Exploration under Myopic Behavior. Kiarash Banihashem, Mohammad Taghi Hajiaghayi, Suho Shin, Aleksandrs Slivkins.
A Truth Serum for Eliciting Self-Evaluations in Scientific Reviews. Jibang Wu, Haifeng Xu, Yifan Guo, Weijie J. Su.
Competitive Information Design for Pandora’s Box. Bolin Ding, Yiding Feng, Chien-Ju Ho, Wei Tang, Haifeng Xu.
Prediction-sharing During Training and Inference. Yotam Gafni, Ronen Gradwohl, and Moshe Tennenholtz.
Learning from Imperfect Human Feedback: a Tale from Corruption-Robust Dueling. Yuwei Cheng, Fan Yao, Xuefeng Liu, Haifeng Xu.
Sharp Results for Hypothesis Testing with Risk-Sensitive Agents. Chen Shi, Stephen Bates, Martin J. Wainwright.
Forecasting Competitions with Correlated Events. Rafael Frongillo, Manuel Lladser, Anish Thilagar, Bo Waggoner.
Incentivizing Agents through Ratings. Peiran Xiao.
Call for Papers
We are now calling for poster submissions. We encourage two-page extended abstract submission but also welcome full-paper submissions of recent or unpublished work that are related to the topics above.
Submission Timelines
June 7th: paper submission deadline.
June 14th: acceptance/rejection notification.
The workshop will take place on Monday morining (July 8) during the EC conference.
Submission Instructions
Please email the submission to ec24workshop-information-acquisition@googlegroups.com.
