Date Published: 2018-11-21
Mayuri Sridhar, Massachusetts Institute of Technology
Ronald L. Rivest, Massachusetts Institute of Technology
Moreover, we present and analyze a simple approximate sampling method, "k-cut", for picking a ballot randomly from a stack, without counting.Our method involves doing k "cuts," each involving moving a random portion of ballots from the top to the bottom of the stack, and then picking the ballot on top. Unlike conventional methods of picking a ballot at random, k-cut does not require identification numbers on the ballots or counting many ballots per draw. We analyze how close the distribution of chosen ballots is to the uniform distribution, and design different mitigation procedures. We show that k = 6 cuts is enough for an risk-limiting election audit, based on empirical data, which would provide a significant increase in efficiency.