Resorting to YouTube and Wikipedia for definitions of both Crowdsourcing and Collective Intelligence, I quickly realised that I was actually using Web 2.0 applications that were utilising these techniques to understand the two definitions as both YouTube and Wikipedia are examples of Web 2.0 applications.
I found watching Jeff Howe describe Crowdsourcing (BrightSightGroup, 2008) and a video on the corporate vision of Collective Intelligence (psbobj, 2007) helped in simplifying both of these phrases to:
A web 2.0 application that has harnessed collective intelligence is an application which encourages user participation and has the ability to leverage the participants to improve the product or content.
Viewing interesting medical imaging cases is my passion, I am fortunate to work at a large teaching hospital that has a large number of interesting cases available. Teaching hospitals throughout the world use a variety of recording devices to ensure appropriate cases are available for teaching at anytime. In the Web 1.0 environment, only studies performed in the particular hospital are available to be stored and recorded in the hospital’s library. Health professionals working in small hospitals are not exposed to this number of cases and education has to be sourced elsewhere. Welcome Web 2.0.
As the definition of a collective intelligence states, a good Web 2.0 application should encourage worldwide participation and continually improve the application’s content. When focussing on Web 2.0 medical imaging teaching libraries, MyPACS.net (McKesson Medical Imaging Group, 2008) is a perfect example. The application enables over 50 thousand users from over 60 countries to upload interesting cases to one central location. The site has over 25 thousand cases that are freely available to anyone across the world, far more than any single library could ever provide its users. Furthermore, if a user has an account, they can set case quizzes or rank cases and leave comments for other authors, increasing the quality of the content.
Are users aware they may be breaking the law if they have not obtained the patient’s consent? There is also a question about whether a patient can be identified by a phenomenon called ‘inference’ where information from deduction of non-sensitive data has been made (Tinazzi, 2011).
Interestingly, the Australian privacy act dictates the images are owned by the health service provider (Office of Australian Information Commissioner, 2011).
BrightSightGroup. (2008). Jeff Howe – Crowdsourcing. Retrieved 3rd March, 2012, from http://www.youtube.com/watch?v=F0-UtNg3ots&feature=youtu.be
McKesson Medical Imaging Group. (2008). MyPACS.net – Reference Case Manager. Retrieved 10th March, 2012, from http://www.mypacs.net/repos/mpv3_repo/static/m/Home/
Office of Australian Information Commissioner. (2011). Who owns my medical records? Retrieved 12th March, 2012, from http://www.privacy.gov.au/faq/health/q34
psbobj. (2007). Collective Intelligence – The Vision. Retrieved 3rd March, 2012, from http://www.youtube.com/watch?v=IQe8dWTbE2U&feature=youtu.be
Tinazzi, A. (2011). Social networking in healthcare – security and privacy implications. Pulse IT magazine,40-41 from