ElectionAudits 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 2008.
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