// Posted by Renee on 04/14/2012 (8:17 PM)
As a final project for this class, I have created this blog which focuses on the theme of collective intelligence, specifically in scientific research. The blog represents several weeks worth of research exploring how CI currently works in science… Read more
As a final project for this class, I have created this blog which focuses on the theme of collective intelligence, specifically in scientific research. The blog represents several weeks worth of research exploring how CI currently works in science and what are the problems/prospects of CI in the future.
The initial questions which shaped my research were:
- What is collective intelligence?
- What can we learn from the history of CI?
- How does digital media amplify our abilities to work collectively?
- How has AIDS research utilized CI? Where was AIDS research before CI?
- Is AIDS research possible without CI?
- What is the relationship between CI and American capitalism?
- How has CI changed the business landscape?
- As social beings are we naturally inclined to think/work collaboratively?
- Have we created a social system that goes against our own evolution?
Using the game Foldit as a case study, I examine how Collective Intelligence can enhance science. Foldit was a game created by professors at the University of Washington to utilize the human brain’s problem solving abilities in order to find the lowest energy structure of a given protein. Similar to the game of Tetris, gamers reshaped proteins and were awarded points for finding correct arrangements. In my description and analysis of Foldit, I incorporate different types of media by using screen shots from the game, a video of MSNC coverage of the results, as well as a video about the game made by the University of Washington.
Foldit is a great example of collective intelligence because over 200,000 players downloaded the game, many of the top players had no background in biochemistry ( in fact one player who excelled was a 13 year old boy who played under the name Cheese), and players could communicate and build off each other’s solutions. In addition, Foldit is a great example because without the game, scientists may never have found the solution. Scientists worked for twelve years, exhausting numerous different approaches. Once they opened the problem up collectively and tapped into the spatial reasoning abilities of volunteers, gamers found the solution in a mere ten days. I then talk about how digital media enhances the ability of collective intelligence by provided a third space that is free of time constraints, geographic limitations, age, gender, or sex qualifications, and provides access to a multitude of resources.
The next part of my argument deals with why collective intelligence is so difficult in science. My original intention was to talk about collective intelligence in business but I ended up talking about science because Foldit was more applicable. I may still extend the scope of my argument to include business as well. I use an article published in the Boston globe as well as the scholarship of Michael Neilson to argue that currently, scientists have a disincentive to share their research with others because they are competing to be the first to make a discovery and to publish their work. Publishing papers results in known benefits such as credit for their discoveries and securing grant money for future research. On the other hand, although sharing data is highly beneficial, the rewards of doing so are so far unclear and undefined. To date, the most successful examples of CI in science such as Foldit have been conservative in that they used collective means to find a solution but their final result was still a traditional academic paper. The rare exception is the Human Genome Project, which was successful only because top scientists in the field came together and formed an open data agreement which was backed by the grant agencies.
In response to the current structure, Neilson imagines a future where all scientific data can be made open and available through the use of the internet. He, and others who support CI, are the leaders in the Open Science Movement. They propose that any publicly funded science should be open science. According to Neilson, this can be changed in two ways. Firstly, scientists can get involved in open science programs, start an open science project, or encourage and give credit to their colleagues who are doing open science. Secondly, non scientists should create general awareness about the importance of open science to pressure the scientific community to work openly. These methods should be successful because the only current barrier to open science is the way that conservative scientists currently look down on CI as lacking prestige and being beneath them.
I then briefly engage psychology theory which demonstrates that our brains are designed to work collectively. And this leads me to the biggest question of my research which I will tackle during phase II. Given the fact that our brains are naturally designed to work collaboratively, and the system we currently work in does not encourage collaborative efforts, have we created a system which goes against our own evolution?
In contrast to my argument that science is structured away from CI, I would like to discuss how some businesses have realized that it is in their self interest to adopt collective intelligence practices. Perhaps as this becomes a larger trend in business (i.e. grant companies) it will become a more accepted practice in science as well. In addition I would like to use both Howard Rheingold and Clay Shirky to talk about the current state of CI and the prospects for the future. What CI projects are being created/implemented today and what is the potential of future projects? How far can we take CI in science or in other words, how open can we make science and what kind of discoveries could be possible?
For my group assignment, I have asked my classmates to help me format my blog. I have asked for advice on themes or formatting techniques which would make my layout reflect the theme of collection intelligence: i.e. less heirarchical and more web-like. So far the advice that I have received has pertained to specific themes to try out and a website that generates custom themes. I plan to test drive each of these themes and attempt to create my own.