Title:
Evidence-Based Elections

dc.contributor.author Stark, Philip B.
dc.contributor.corporatename Georgia Institute of Technology. Institute for Information Security & Privacy en_US
dc.contributor.corporatename University of California, Berkeley. Dept. of Statistics en_US
dc.date.accessioned 2022-02-14T18:44:08Z
dc.date.available 2022-02-14T18:44:08Z
dc.date.issued 2022-02-04
dc.description Presented online via Bluejeans Events and in-person in the CODA building, 9th floor on February 4, 2022 at 12:30 p.m. en_US
dc.description Philip B. Stark is a Distinguished Professor of Statistics at the University of California, Berkeley. His research centers on inference problems, primarily in physical and social sciences. He is especially interested in confidence procedures tailored for specific goals and in quantifying the uncertainty in inferences that rely on numerical models of complex systems en_US
dc.description Runtime: 71:57 minutes en_US
dc.description.abstract Elections rely on people, hardware, and software, all of which are fallible and subject to manipulation. Voting equipment is built by private vendors using foreign parts. Many states outsource election results reporting. Advanced persistent threats and insider threats are real. Uncertainty about the outcome of elections has been weaponized politically recently. We need to conduct elections in a way that provides affirmative evidence that the reported winners really won–despite malfunctions, errors, and malfeasance. Evidence-based elections require voter-verified (generally, hand-marked) paper ballots kept demonstrably secure throughout the canvass and manual audits of election results against the trustworthy paper trail. Compliance audits establish whether the paper trail is complete and trustworthy. Risk-limiting audits (RLAs) check the outcome by testing the hypothesis that one or more reported winners did not win. For a broad variety of social choice functions, including plurality, multi-winner plurality, supermajority, Borda count, approval voting, all scoring rules, instant-runoff voting (ranked-choice voting), and D'Hondt and Hamiltonian proportional representation, the hypothesis that at least one reported winner did not win can be reduced to the hypothesis that the mean of one or more lists of nonnegative numbers is not greater than 1/2. Martingale tests of these nonparametric hypotheses sequentially are especially practical. Methods to accommodate different sampling plans, equipment capability, logistical constraints, and laws and regulations have been developed and piloted in more than a dozen states in jurisdictions of all sizes, including roughly 10 audits of statewide contests. RLAs are in law in several states. en_US
dc.format.extent 71:57 minutes
dc.identifier.uri http://hdl.handle.net/1853/66285
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.relation.ispartofseries Cybersecurity Lecture Series
dc.subject Election integrity en_US
dc.subject Martingale tests en_US
dc.subject Risk-limiting election audits en_US
dc.subject Statistics en_US
dc.title Evidence-Based Elections en_US
dc.type Moving Image
dc.type.genre Lecture
dspace.entity.type Publication
local.contributor.corporatename School of Cybersecurity and Privacy
local.contributor.corporatename College of Computing
local.relation.ispartofseries Institute for Information Security & Privacy Cybersecurity Lecture Series
relation.isOrgUnitOfPublication f6d1765b-8d68-42f4-97a7-fe5e2e2aefdf
relation.isOrgUnitOfPublication c8892b3c-8db6-4b7b-a33a-1b67f7db2021
relation.isSeriesOfPublication 2b4a3c7a-f972-4a82-aeaa-818747ae18a7
Files
Original bundle
Now showing 1 - 4 of 4
No Thumbnail Available
Name:
stark.mp4
Size:
138.28 MB
Format:
MP4 Video file
Description:
Download video
No Thumbnail Available
Name:
stark_videostream.html
Size:
1.1 KB
Format:
Hypertext Markup Language
Description:
Streaming video
No Thumbnail Available
Name:
transcript.txt
Size:
68.29 KB
Format:
Plain Text
Description:
Transcription
Thumbnail Image
Name:
thumbnail.jpg
Size:
29.61 KB
Format:
Joint Photographic Experts Group/JPEG File Interchange Format (JFIF)
Description:
Thumbnail
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
3.13 KB
Format:
Item-specific license agreed upon to submission
Description:
Collections