As the volume of the world’s big data grows at a staggering speed, so too does the need for people who know how to extract knowledge, insights, or solutions from it. Today’s data scientist must have both the technical skills to solve complex data problems and the curiosity to seek out the hidden problems data can solve.
For all of AI’s promises, we still need people to do a lot of work behind the scenes to make it all possible. People collect, enrich, clean, and prepare data for AI systems to operate accurately and optimally. In fact, data scientists spend countless hours cleaning and combining datasets, a process commonly referred to as “data wrangling.”
The term "Crowdsourcing" which was coined by Jeff Howe in 2006 in Wired Magazine is now becoming a mainstream business. Today crowdsourcing is a billion dollar industry and is being used by several small, medium and big sizes firm to solve their business problems.