Crowd-sourcing is increasingly being used for providing answers to online polls and surveys. However, existing systems, while taking care of the mechanics of attracting crowd workers, poll building, and payment, provide little to help the survey-maker or pollster in obtaining statistically significant results devoid of even the obvious selection biases.

This paper proposes InterPoll, a platform for programming of crowd-sourced polls. Polsters express polls as embedded LINQ queries and the runtime correctly reasons about uncertainty in those polls, only polling as many people as required to meet statistical guarantees. To optimize the cost of polls, InterPoll performs query optimization, as well as bias correction and power analysis. The goal of InterPoll is to provide a system that can be reliably used for research into marketing, social and political science questions.

This paper highlights some of the existing challenges and how InterPoll is designed to address most of them. In this paper we summarize some of the work we have already done and give an outline for future work.