is an open source application that facilitates scientific
audits of elections. It was used to report on and drive
audits for an unprecedented number of contests in the
2008 general election in Boulder Colorado. The audits were “risk-sensitive”: we
audited more samples in close races so as to limit the risk of
announcing the wrong winner.
Come get a sense for the fascinating algorithms behind modern election
auditing, and how this software helps make up for limitations of
current election management systems.
Computer professionals have long been prominently pointing out the
flaws of “black box” voting machines that have no paper trail, and we’re
finally winning that battle. But few jurisdictions are doing a good job of
actually looking at those paper records and scientifically auditing
our elections. That is beginning to change. Now a set of
Principles and Best Practices for Post-Election Audits
is available, and we are getting lawmakers to call for scientific audits.
In her keynote talk last year, Christine Peterson challenged us to
apply our insights, practices and tools as open source professionals
to other problems in society. Our understanding of the interplay
between security, privacy, transparency, and freedom is crucial for
moving forward to the next level of confidence in our elections -
achieving software independence
via auditable paper records and good audits.
Present election management systems make it difficult to report election
results in ways that can be audited efficiently. ElectionAudits
reshapes existing election reports into auditable batch reports,
publishes them on the web, and then implements the latest statistical
methods for efficiently sampling the batches even when they vary in
size (NEGEXP , PPEBWR, etc.). These methods can require thousands of
random selections, so ElectionAudits also supports extending a limited
number of dice throws during a carefully designed public ceremony into
the publicly verifiable random selection of all the necessary batches
via Rivest’s Sum of Square Roots method.
ElectionAudits is written in Python using the Django web framework.
It can run standalone on a laptop and also drive a public web site.
The talk will clarify the problems of auditing and demo how they were
addressed with the software in Boulder. Armed with this, you’ll be
ready to help to improve the public’s confidence in future elections in
your area. And if you have expertise in areas like web design, XML,
packaging or query optimization, you’ll see how you can get involved
in improving the software.
Neal McBurnett specializes in “Technology Serving Community”. At Bell
Labs in the 80’s and 90’s he helped the Business Communications
division to recognize the importance and benefits of the Internet,
open standards, free software, security and Linux. In 1993 he
co-founded the Boulder Community Network, the world’s second web-based
geographical community network. He is now an independent consultant,
contributes as an Ubuntu member on the server team, and is having a
ball with the Android mobile phone platform.
Neal has been working on improving election audits since 2002. He was
a major contributor to the “Principles and Best Practices for
Post-Election Audits” (September 2008) and has been a leader in the
election auditing community. Using his open source ElectionAudits
software, Boulder County, Colorado did a nationally recognized audit in
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