Toward a Science of Citizen Science

I will discuss opportunities to harness methods from computer science and statistics in pursuit of a science of citizen science, via leveraging principles of probability and decision theory. I will focus particularly on the use of machine learning and automated planning under uncertainty to mesh the intellects of human and machines, fuse inputs from multiple citizen scientists, make decisions about continuing versus halting to seek input on tasks, and predicting and extending the engagement of volunteer citizen scientists on tasks.