![\"\"](\"http:\/\/therapytoronto.ca\/images\/blogpics\/SocialNetwork2.jpg\" "\\"crowdsourcing\\"")
In 1714, the British government held a contest. They offered a large cash prize to anyone who could solve the vexing \u201clongitude problem\u201d \u2014 how to determine a ship\u2019s east\/west position on the open ocean \u2014 since none of their naval experts had been able to do so.<\/p>\n
Lots of people gave it a try. One of them, a self-educated carpenter named John Harrison, invented the marine chronometer \u2014 a rugged and highly precise clock \u2014 that did the trick. For the first time, sailors could accurately determine their location at sea.<\/p>\n
A centuries-old problem was solved. And, arguably, crowdsourcing<\/strong> was born.<\/p>\n Crowdsourcing is basically what it sounds like: posing a question or asking for help from a large group of people<\/strong>. Coined as a term in 2006, crowdsourcing has taken off in the internet era. Think of Wikipedia, and its thousands of unpaid contributors, now vastly larger than the Encyclopedia Britannica.<\/p>\n Crowdsourcing has allowed many problems to be solved that would be impossible for experts alone. Astronomers rely on an army of volunteers to scan for new galaxies. At climateprediction.net, citizens have linked their home computers to yield more than a hundred million hours of climate modeling; it\u2019s the world\u2019s largest forecasting experiment.<\/p>\n But what if experts didn\u2019t simply ask the crowd to donate time or answer questions? What if the crowd was asked to decide what questions to ask in the first place?<\/p>\n Could the crowd itself be the expert?<\/strong><\/p>\n That\u2019s what a team at the University of Vermont decided to explore \u2014 and the answer seems to be yes.<\/p>\n Josh Bongard and Paul Hines, professors in UVM\u2019s College of Engineering and Mathematical Sciences, and their students, set out to discover if volunteers who visited two different websites could pose, refine, and answer questions of each other \u2014 that could effectively predict the volunteers\u2019 body weight and home electricity use.<\/p>\n The experiment, the first of its kind, was a success: the self-directed questions and answers by visitors to the websites led to computer models that effectively predict user\u2019s monthly electricity consumption and body mass index<\/strong>.<\/p>\n Their results, “Crowdsourcing Predictors of Behavioral Outcomes,\u201d were published in a recent edition of IEEE Transactions: Systems, Man and Cybernetics<\/em>, a journal of the Institute of Electrical and Electronics Engineers.<\/p>\n \u201cIt\u2019s proof of concept that a crowd actually can come up with good questions that lead to good hypotheses,\u201d says Bongard, an expert on machine science.<\/p>\n In other words, the wisdom of the crowd can be harnessed to determine which variables to study, the UVM project shows \u2014 and at the same time provide a pool of data by responding to the questions they ask of each other.<\/p>\n \u201cThe result is a crowdsourced predictive model,\u201d the Vermont scientists write.<\/p>\n Some of the questions the volunteers posed were obvious. For example, on the website dedicated to exploring body weight, visitors came up with the question: \u201cDo you think of yourself as overweight?\u201d And, no surprise, that proved to be the question with the most power to predict people\u2019s body weight.<\/p>\n But some questions posed by the volunteers were less obvious. \u201cWe had some eye-openers,\u201d Bongard says. \u201cHow often do you masturbate a month?\u201d might not be the first question asked by weight-loss experts, but it proved to be the second-most-predictive question of the volunteer\u2019s self-reported weights \u2014 more predictive than \u201chow often do you eat during a day?\u201d<\/p>\n \u201cSometimes the general public has intuition about stuff that experts miss \u2014 there\u2019s a long literature on this,\u201d Hines says.<\/p>\n \u201cIt\u2019s those people who are very underweight or very overweight who might have an explanation for why they\u2019re at these extremes \u2014 and some of those explanations might not be a simple combination of diet and exercise,\u201d says Bongard. \u201cThere might be other things that experts missed.\u201d<\/p>\n The researchers are quick to note that the variables revealed by the evolving Q&A on the experimental websites are simply correlated to outcomes \u2014 body weight and electricity use \u2014 not necessarily the cause.<\/p>\n “We\u2019re not arguing that this study is actually predictive of the causes,\u201d says Hines, \u201cbut improvements to this method may lead in that direction.\u201d<\/p>\n Nor do the scientists make claim to being experts on body weight or to be providing recommendations on health or diet (though Hines is an expert on electricity, and the EnergyMinder site he and his students developed for this project has a larger aim to help citizens understand and reduce their household energy use.)<\/p>\n \u201cWe\u2019re simply investigating the question: could you involve participants in the hypothesis-generation part of the scientific process?\u201d Bongard says. \u201cOur paper is a demonstration of this methodology.\u201d<\/p>\n \u201cGoing forward, this approach may allow us to involve the public in deciding what it is that is interesting to study,\u201d says Hines. \u201cIt\u2019s potentially a new way to do science.\u201d<\/p>\n And there are many reasons why this new approach might be helpful. In addition to forces that experts might simply not know about \u2014 \u201ccan we elicit unexpected predictors that an expert would not have come up with sitting in his office?\u201d Hines asks \u2014 experts often have deeply held biases.<\/p>\n But the UVM team primarily sees their new approach as potentially helping to accelerate the process of scientific discovery. The need for expert involvement \u2014 in shaping, say, what questions to ask on a survey or what variable to change to optimize an engineering design \u2014 \u201ccan become a bottleneck to new insights,\u201d the scientists write.<\/p>\n \u201cWe\u2019re looking for an experimental platform where, instead of waiting to read a journal article every year about what\u2019s been learned about obesity,\u201d Bongard says, \u201ca research site could be changing and updating new findings constantly as people add their questions and insights.\u201d<\/p>\n The goal: \u201cexponential rises,\u201d the UVM scientists write, in the discovery of what causes behaviors and patterns \u2014 probably driven by the people who care about them the most. For example, \u201cit might be smokers or people suffering from various diseases,\u201d says Bongard. The team thinks this new approach to science could \u201cmirror the exponential growth found in other online collaborative communities,\u201d they write.<\/p>\n \u201cWe\u2019re all problem-solving animals,\u201d says Bongard, \u201cso can we exploit that? Instead of just exploiting the cycles of your computer or your ability to say \u2018yes\u2019 or \u2018no\u2019 on a survey \u2014 can we exploit your creative brain?\u201d<\/p>\n<\/div>\n<\/blockquote>\n","protected":false},"excerpt":{"rendered":" From the University of Vermont press release: In 1714, the British government held a contest. They offered a large cash prize to anyone who could solve the vexing \u201clongitude problem\u201d… Read more »<\/a><\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[8],"tags":[12],"_links":{"self":[{"href":"https:\/\/therapytoronto.ca\/news\/wp-json\/wp\/v2\/posts\/5555"}],"collection":[{"href":"https:\/\/therapytoronto.ca\/news\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/therapytoronto.ca\/news\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/therapytoronto.ca\/news\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/therapytoronto.ca\/news\/wp-json\/wp\/v2\/comments?post=5555"}],"version-history":[{"count":2,"href":"https:\/\/therapytoronto.ca\/news\/wp-json\/wp\/v2\/posts\/5555\/revisions"}],"predecessor-version":[{"id":5616,"href":"https:\/\/therapytoronto.ca\/news\/wp-json\/wp\/v2\/posts\/5555\/revisions\/5616"}],"wp:attachment":[{"href":"https:\/\/therapytoronto.ca\/news\/wp-json\/wp\/v2\/media?parent=5555"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/therapytoronto.ca\/news\/wp-json\/wp\/v2\/categories?post=5555"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/therapytoronto.ca\/news\/wp-json\/wp\/v2\/tags?post=5555"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Prediction from the people<\/h4>\n
Unexpected angles<\/h4>\n
Cause and correlation<\/h4>\n
Faster discoveries<\/h4>\n