Citizen Science Salon is a partnership between Discover and SciStarter.org.
Working together, humans and computers can do great things. Humans and computers are safeguarding ecosystems, predicting hazards, and diagnosing and treating deadly diseases. Here are just a few of our favorite human computer partnerships that welcome your participation.
An App to Identify Species
Seek by iNaturalist is a mobile tool that does a remarkable job of identifying any organism, using powerful computer vision algorithms fueled by photos and identifications made by the global iNaturalist community. Simply download the app and start exploring plants and animals, earning badges and, optionally, sharing what you find back to the project to improve the algorithm.
Help Find a Treatment for Alzheimer's with Stall Catchers
With the help of citizen scientists, the Stall Catchers project now has three research papers being completed for publication, all focused on new treatments for Alzheimer's disease. But there's so much more to discover, and Stall Catchers is already pioneering new machine learning techniques in combination with the analysis of citizen scientists like you. Put your brainpower to work fighting a leading cause of death and disability.
Become a Genetic Detective
Help scientists study the evolution and function of DNA, RNA and protein sequences by optimizing genetic multiple sequence alignments, or MSAs. Fortunately for non-geneticists, the Phylo project abstracts the data into colored shapes and presents them in a game-like interface that anyone can play.
Help Track Whale Sharks and Other Animals
Wildbook blends structured wildlife research with artificial intelligence, citizen science and computer vision to speed population analysis and develop new insights to help fight extinction. The project identifies and tracks individual animals (such as whale sharks) using photos submitted by citizen scientists.
Improve Training With Space Fortress
Your activity on Space Fortress will help researchers learn about learning: how players preserve their gaming skills after periods of non-use. The results will be used for developing a model for optimizing training regimens for professionals across different industries, so that lessons will be provided just in time: not too early, not too late.