Digital Media Changing the Way We Do Science?
Post created for my digital media course, #MC7019
“We can use the internet to build tools that actually expand our ability to solve the most challenging intellectual problems. Or to put it another way, we can build tools which actively amplify our collective intelligence in much the same way as for millennia we’ve used physical tools to amplify our strength.” - Michael Nielsen
In January 2009, a world-renowned mathematician decided to use his blog to test a uniquely 21st century idea, that massively collaborative mathematics could be possible. Tim Gowers decide to announce an intellectual invitation on his WordPress blog, encouraging mathematicians the world over to help him openly solve a complex, unsolved problem by posting comments at the bottom of the site.
The experiment, now known as the Polymath Project, resulted in over 800 comments that eventually lead to the publication of several scientific papers, and the solution of a harder generation of the original problem.
Today, polymathprojects.org serves as a platform for crowdsourced solutions to difficult mathematical problems, inspired by Gowers’ original open-science experiment.
But the Polymath Project is far from alone. Could traditional ways of doing science – a single scientist in a single lab – become outdated as the power of collaborative online action surpasses anything society has even known?
Here Comes Everybody
“Today we have new technologies, we have new opportunities, to share our knowledge in new ways, and the ability to create tools that actually allow us to solve problems in entirely new ways.” - Michael Nielsen
In 2008, Clay Shirky identified a revolution in “organizing without organizations” in his book Here Comes Everybody. Inside its pages, Shirky gives compelling examples of how new technologies, particularly new communication technologies including the internet in general and social media platforms specifically, have changed the very nature of groups and group action. Shirky’s examples include websites dedicated to particular causes, sharing and aggregating sites like Flickr, and user-generated knowledge efforts such as Wikipedia.
He writes, “[b]y making it easier for groups to self-assemble and for individuals to contribute to group effort without requiring formal management (and its attendant overhead), these [digital communications] tools have radically altered the old limits on the size, sophistication, and scope of unsupervised effort…” (p. 21)
Shirky describes how internet-based communication tools have challenged traditional media models, transforming consumer-based audiences into mass publishers and even collaborative producers of content, from blogs to amateur photographs, videos and more. The outcomes of these collaborative efforts are often more than their individual parts: collections of individuals online can solve complex problems unattainable by an individual or even a highly-managed organization due to constraints of time and/or resources. What Shirky calls the “collapse of transaction costs” has led to massive nonfinancially-driven outcomes including sharing, cooperative production and collective action.
One of the results of the mass amateurization of media production is the fact that today, platforms including Twitter, Reddit and blogs can “break” news. Everyone with a smartphone becomes a potential reporter and photographer in the midst of a breaking news event. From blogs to news tweets, "from now on news can break into public consciousness without the traditional press weighing in" (p. 64).
There are of course consequences to a radically changing media landscape. For science communication, it is very apparent that a bulk of the growth of science news, and the “popularization” of science, has been driven by science blogging and content on specialized digital media platforms. The growth of science in the blogosphere and in social media has occurred at the same time that traditional newspaper science sections have dwindled.
The result is that while public audiences have more science news at their fingertips than ever before, a certain extent of media literacy is increasingly required of these audiences. What is the difference between a Wiki article about the human genome project, a blog post and an online newspaper article? What are the communication norms and routines that go into producing on or the other? How are audiences supposed to gauge the accuracy and credibility of these different forms of online content?
According to Bora Zivkovic, Blog Editor at Scientific American, it is increasingly the job of the reader to orient him or her-self as to the nature of the content he or she is seeing online:
“So, a lot of my agenda now is actually modifying the way people use the website. And [Scientific American] has fused blogs and, you know, mainstream news site, probably more than any other media organization. Most of them are keeping them much more separate, and much more obvious, these are blogs and this is news. We are trying to mix them up and break that border and barrier between them, and in the process educate our audiences how the new media works. That those things are mixed up, and that the same person can write a straight up news story, and that afternoon a blog post, which is going to be much more different. And you need to… the first thing you do when you come to a page, you know, from Twitter or what not, is to orient yourself, what material this is going to be. It can be the same person, but this is, you know, official news piece from Scientific American, and this is that same person on [a] personal blog, which is part of a more continuous communication than a stand-alone article. And I think it’s better that way, because you can provide context. And context comes through links, and, you know, through previous stuff, and looking around the archives. And it’s an uphill battle, but a lot of people are looking up to us, to Scientific American, to how we are doing it." – Interview with Paige Brown
But media about science isn’t the only area of science being changed by the revolution in digital and social media.
Open Source
“Linux got to be world-changingly good not by promising to be great, or by bringing paid developers together under the direction of some master plan, but by getting incrementally better, through voluntary contributions, one version at a time” (p. 239).
In Here Comes Everybody, Shirky describes the operating system Linux as one of the most successful and trend-setting examples of collaboratively created, or “open source,” software. The idea of open source software is that it is not only freely available, but freely improvable, as Shirky puts it. Linux’s model has now extended in many different areas, including science and public health. For instance, the sequencing of the sudden acute respiratory syndrome (SARS) virus in 2003 by the Genome Science Centre relied on open source bioinformatics tools running on the “open” Linus operating system.
But while Shirky gives these examples, most of his book’s 321 pages are devoted to examples of digital communication technologies benefitting and revolutionizing primarily communication industries themselves (e.g. traditional news media), and/or social and political activist movements. I think the discussion of how communication technologies may be changing the very way we go about science deserves a more in-depth look.
Crowdsourcing Science
“Wikipedia is able to aggregate individual and often tiny contributions, hundreds of millions of them annually, made by millions of contributors, all performing different functions” (p. 118).
What if the way we think about how science is done is changing, just as the way we think about “news” has changed with the advent of blogs and social media platforms such as Twitter?
In 2000, the private company Celera Genomics surprised the world by beating the public Human Genome Project to be the first to sequence the human genome. When Craig Venter founded Celera Genomics with a mission to sequence the entire genome within two years, many people did not believe that the company could beat the National Institute of Health (NIH) and the public Human Genome Project to the task. But using “the largest civilian supercomputer and a ‘shotgun’ technique to piece together the sequences that make up the double helix of DNA,” Celera did just that.
Just like a private company shocked other scientists by quickly developing solutions to a complex problem, I think that scientists today might soon be shocked by the efficiency and value of crowdsourcing and online collaboration for science.
A group at Stanford is using the very premise Shirky talks about in Here Come’s Everybody to solve problems for protein folding research, with applications in therapeutic targets for diseases including Alzheimer’s and Parkinson’s. The premise is rather simple: take a very large and complex computational problem – developing algorithms for how proteins fold into their 3-D shapes – and divide it into tiny chunks that citizens anywhere, or rather their personal computers, can handle.
“Folding@home software aids research by simulating protein folding. The calculations are immense so we break them into small ‘work units" and pass them to individual computers like yours to solve. Stanford computers assemble data from thousands of work units into meaningful answers to important scientific questions.”
All anyone who wants to contribute has to do is navigate to the Folding@home website, download the protein folding simulation software onto their personal machines, run the installation and allow their computers to communicate with Stanford servers. The result is a massive array of free resources open to Stanford scientists, in the name of science.
But collaboration for science can go beyond these types of projects that demand little input or effort on the part of the “audience.”
Foldit offers more intriguing scientific possibilities for video-game lovers all over the world. Foldit “is a revolutionary new computer game enabling you to contribute to important scientific research.” As it turns out, a platform where any person can contribute their basic pattern-recognition and puzzle-solving abilities, in the context of an online game, can result in more efficient solutions to the 3-D shape and folding structure of proteins. A BoingBoing science editor described the premise of the game in 2009: “Computer programs could calculate all the possible protein shapes, but it would take far longer than the average researcher's life span. Instead, the University of Washington team that developed Foldit is hoping that human game-players can figure things out faster.” Players compete against one another to develop folded versions of specific proteins that win the most number of points by requiring the least amount of “energy” necessary to hold that version together in real-life. In essence, the rules of the game are physics as applied at the scale of proteins in real-life – and yet the game requires nothing more than a good eye and a competitive nature.
From mapping the shapes of neurons (brain cells), to browsing and funding cool research projects, to counting and taking pictures of birds, lay audiences can increasingly collaborate on science projects using new internet-based technologies. The best crowdsourcing science projects are taking advantage of people’s inherent social tendencies, or their passions for video-games or bird-watching.
“People are rewarded for giving the same answers as others, and that’s how they learn. That’s how they’re incentivized to be accurate – and it also makes the game inherently social.” – EyeWire, A Game to Map the Brain
But what do these new ways of doing science mean for science as a whole? Perhaps more than most scientists today expect. Over the summer, I wrote a blog post about citizen science that pointed out many areas where scientists should be trying harder to engage “potential audiences.” In fact, scientists and science research labs that ignore these tools may increasingly be left in the dust by the enormous power of collective action for scientific discovery.
For example, a huge proportion of US citizens walk around nearly 24-7 with mini-computers in their hands and pockets, i.e. their smartphones. Max Little, director of Parkinson’s Voice Initiative and Wellcome Trust/MIT fellow currently at the Media Lab, MIT, is working on a project to use smartphones as diagnostic devices for Parkinson’s disease, by using the GPS and acceleration sensors embedded in most cell phones to detect disease symptoms related to daily body movements. And this is only the tip of the iceberg as far as citizen science goes.
“If you said years ago, ‘One day you will be on Facebook sharing all your photos and personal information with people,’ they wouldn’t believe you,” he said. “We’re just at the beginning. The change is coming.” – Virologist Ijad Madisch, in NYT article on open science.
Could this change challenge the model of science as we know it today? The single-scientist-single-lab model has already been exchanged for larger and more multidisciplinary research teams: environmental scientists collaborating with sociologists and communication researchers to address sustainable development and resilience of coastal communities; chemists, programmers and designers collaborating on high-performance computational solutions to drug design. But these multidisciplinary teams might need more: they might need the power of “everybody” on the internet.