Citizen science - the involvement of hundreds of thousands of people in the research process - is a radical response to the challenge of dealing with the ever-growing size of modern datasets. With the advent of the World Wide Web, tens of thousands of people across the globe can be enlisted to help scientists with tasks that are impossible to automate. The combined assessment of many non-expert human classifiers with minimal training often equal or improves that of a trained expert and in many cases outperform the best automated algorithms. In the past decade, citizen science has been applied to nearly all areas in astronomy and planetary science including projects engaging the public to study galaxy morphology, map seasonal fans on the South pole of Mars, identify exoplanet transits, search for supernovae, locate star formation bubbles in our Galaxy, discover gravitational lenses, and map star clusters in Andromeda.

In this talk, I will give an overview of the current state of citizen science in astronomy and how researchers are utilizing human pattern recognition to mine large astronomy and planetary science-based datasets. I'll present some of the science results derived from the contributions of hundreds and thousands of volunteers who participate in these projects. In particular, I'll highlight two projects I've been involved in: Planet Four (http://www.planetfour.org - to probe the seasonal processes on the South Pole of Mars) and Planet Hunters (http://www.planethunters.org- to study the exoplanet population). I'll also touch on how citizen science will be one of the ways forward to tackle the data deluge produced by the next generation observatories coming online in the next decade and how crowdsourcing will have to evolve in the era of LSST and SKA.