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In a variety of problem domains, it has been observed that the aggregate opinions of groups are often more accurate than those of the constituent individuals, a phenomenon that has been termed the "wisdom of the crowd." Yet, perhaps surprisingly, there is still little consensus on how generally the phenomenon holds, how best to aggregate crowd judgements, and how social influence affects estimates. We investigate these questions by taking a meta wisdom of crowds approach. With a distributed team of over 100 student researchers across 17 institutions in the United States and India, we develop a large-scale online experiment to systematically study the wisdom of crowds effect for 1,000 different tasks in 50 subject domains. These tasks involve various types of knowledge (e.g., explicit knowledge, tacit knowledge, and prediction), question formats (e.g., multiple choice and point estimation), and inputs (e.g., text, audio, and video). To examine the effect of social influence, participants are randomly assigned to one of three different experiment conditions in which they see varying degrees of information on the responses of others. In this ongoing project, we are now preparing to recruit participants via Amazon?s Mechanical Turk.

While the ability to see colours is innate, their perception is a guided process. Varying across languages and cultures, linguistic vocabulary is one such influence that guides our perception. In colour specifically, the names of colours in a language act as verbal cues that help us memorize and later recognize colours of the spectrum. This makes colour a cultural and local phenomenon. This paper presents a novel method to perform colour transfer, given an image and an elaborate colour palette as inputs. Image segmentation is employed, followed by a region based colour transfer to ensure accurate local colour mapping. The method is used to bias the given image with colours that are perceptually closest to it in a reference language. This is done in an attempt to make the colour transfer reflect the changes in colour vocabularies of people from different languages and cultures.