All, David Parkes and Sharon Goldberg will be giving talks at CITP next Tuesday and Wednesday afternoons, respectively. Please find their talk abstracts below. -Nick ———————— Routing Around the Legal Restrictions on Internet Surveillance Date: Tuesday, May 16, 2017 Time: 4:30 p.m. Location: 101 Sherrerd Hall Internet surveillance for national-security purposes is largely regulated by two legal authorities. The Foreign Intelligence Surveillance Act (FISA) largely regulates surveillance on US territory, while Executive Order (EO) 12333 largely regulates surveillance abroad. Surveillance programs conducted under FISA are subject to legal restrictions imposed by Congress and the courts, while surveillance programs under EO 12333 are conducted solely under the authority of the President. The talk considers that possibility that the legal protections built into in FISA can be circumvented by exploiting the Internet’s routing protocols. Specifically, we consider the possibility that routing hijacks can be used to deliberately divert American traffic abroad, where it can be collected under EO 12333. We analyze the lawfulness of using routing hijacks to circumvent FISA, and discuss how several newly-developed secure routing protocols might (or might not) prevent these hijacks. We conclude with a policy recommendation: Congress should expand FISA to cover the surveillance of any and all Internet traffic collected abroad. ———————— Robust Methods to Elicit Informative Feedback Date: Tuesday, May 16, 2017 Time: 4:30 p.m. Location: 101 Sherrerd Hall Streaming Live: http://mediacentrallive.princeton.edu/ Hashtag: #citptalk Suppose we want to score contributions of information to a platform and thus promote effort amongst participants, but have no easy way to verify the quality of information. Responses may be subjective, or simply too costly to verify; e.g., what emotion do you feel watching video content, is a restaurant good for a family, what grade does a student deserve for an essay, should a paper be accepted to a conference, is a social media story real or fake? Peer prediction (Miller, Resnick and Zeckhauser 2005) seeks to promote effort by scoring contributions based on how predictive they are of contributions by others. But the challenge has been to score contributions without promoting unintended “group think” equilibria or coordinated misreports. In this talk, the correlated agreement mechanism will be described, which uses reports on multiple questions to provide a remarkably robust method of peer prediction. Its properties will be demonstrated on statistical models derived from reports on places in a city and peer-evaluation on a MOOC platform. Time permitting, it will also be explained how it can be coupled with methods from machine learning to handle the heterogeneity of participants. Joint work with Arpit Agarwal (U Penn), Rafael Frongillo (CU Boulder), Matthew Leifer (Harvard), Debmalya Mandal (Harvard), Galen Pickard (Google), Nisarg Shah (Harvard), and Victor Shnayder (Harvard).