Synopsis

Incentives for information procurement are integral to a wide range of applications including peer grading, peer review, prediction markets, crowd-sourcing, or conferring scientific credit. Meanwhile, mechanisms for information procurement have made large theoretical advances in recent years. This workshop will draw together practitioners that have deployed solutions in this space and experts in incentives and mechanisms to talk about existing connections, look for unexploited connections, and develop the next generation of information procurement research that will allow the theory to be further applied in these areas.

Speakers

Kevin Leyton-Brown (Univ. of British Columbia), Raul Castro Fernandez (UChicago), Yiling Chen (Harvard Univ.), and Nihar Shah (Carnegie Mellon Univ.).

Logistics

Date: Friday, October 14, 2022

Location: Northwestern University

Rooms: Mudd Library 3514

Registration: click here to register

Virtual: gather.town (details provided to registered participants)

Schedule (Tentative)

10:30-11:00: Breakfast

11:00-11:05: Opening Remarks

11:05-11:45: Yiling Chen Predicting the Replication and Publication Outcomes of Scientific Studies

11:50-12:30: Raul Castro Fernandez Protecting Data Markets from Strategic Buyers

12:35-2:00: Lunch Break

2:00 - 2:40: Nihar Shah Peer review, Incentives, and Open Problems

2:45 - 3:25: Kevin Leyton-Brown Better Peer Review via AI

3:30 - 4:00: Coffee Break

4:00 - 5:30: Individual/group meetings with students, faculty, postdoc attendees

About the Series

The IDEAL workshop series brings in experts on topics related to the foundations of data science to present their perspective and research on a common theme. Chicago area researchers with an interest in the foundations of data science. The workshop is part of the IDEAL Fall 2022 Special Quarter on Data Economics.