By Michael Nielsen
Princeton University Press (October 3, 2011)
Michael Nielsen is one of the founders of the field of quantum information and among the pioneers of quantum computation. I had some overlap with him at Perimeter Institute, where we organized a conference together. Michael resigned from his tenured faculty position in 2008 to dedicate his time to the future of science, to studying how it will work best in the era of rapid information exchange, high connectivity, and large capacity for data storage and handling. His book "Reinventing Discovery" is a careful argument, as much as a vision and a manifest.
For his book, Michael has collected a large number of examples how the new software and hardware is changing the way we do science, and the way scientists interact with each other and the public. He has probably looked at and studied many more examples than he wrote about. He has sorted these examples into tools that amplify collective intelligence by creating an "architecture of attention" for a community of practice and tools that integrate science into our societies, like open access, citizen science, and the generally improved exchange between scientists and the public. In each case, he has analyzed successes and failures, and draws conclusions from it, pointing out shortcomings and risks, and making suggestions for improvement.
It is impossible not to see the academic shine through the lines of the book. This isn't your typical popular science book, it's original research by a smart and dedicated scientist who spent a lot of time studying the facts and thinking about them. Michael's main point is that new tools allow us to use our knowledge much more efficiently, thus tapping upon a presently unused potential, and that this is a quiet revolution
"It's a slow revolution that has quietly been gathering steam for years. Indeed, it's a change that many scientists have missed or underestimated, being so focused on their own speciality that they don't appreciate just how broad-ranging the impact of new online-tools is."
Collective intelligence, Michael argues, works by bringing together many people's "microexpertise," that is a specialized knowledge in a specific area. New software can tell them when their microexpertise is needed and where and how they can add their contribution. To that end, it is preferable if problems are brought into a modular structure, so that parts can be tackled independently. Suitable tools, some of which already exist, then allow scientists to scale up collaborations, helping them solve problems much faster, wasting less time and effort. These are exciting developments for every scientist that promise to make scientific research smoother, faster and less frustrating.
Michael also covers many amazing examples of citizen science that are redefining the way science is integrated into our societies, which he believes taps on a large but still mostly unused potential:
"Cynics will say that most people aren't smart enough or interested enough to make a contribution to science. I believe that projects such as Galaxy Zoo and Foldit show those cynics are wrong. Most people are plenty smart enough to make a contribution to science, and many of them are interested. All that's lacking are tools that helo connect them to the scientific community in ways that let them make that contribution. Today, we can build those tools."
In his book, Michael doesn't merely summarize how online tools have changed science, but he also lays out a vision for the future, making a compelling case for just how big a different these developments can make. In the last chapters he addresses concerns and finally obstacles on the way to make his vision come true, most notably the collective action problem: Scientists have in the present system little incentives to contribute to open science or to share and discuss their ideas openly. Michael seems to find a top down approach (guidelines by founding agencies) to be most promising, but also has suggestions for little pragmatic steps that everybody individually, scientist or not, can take.
Michael's argument is so convincing indeed that I almost forgot my own reservations about open science. Good thing I write a blog. I agree with Michael on almost all points. Science is undergoing a dramatic change right now, and new software opens up new possibilities that have the potential to lead to a sudden and large knowledge gain, both for scientists as well as for the general public. My biggest concern is that too much exchange can actually be harmful to creativity and originality. To Michael's credit, he briefly addresses this point, saying that it's "serious but not insurmountable." Basically, he says, software needs to be smart so scientists can filter the information they receive. In principle that's true. But my concern is addressed by this as much as obesity is addressed by saying people can just buy less food.
That having been said, my point is essentially that the creation of any tool that is supposed to improve science should be informed by sociologists and psychologists likewise, and be continuously monitored in its effects, in a process that should be integrated into the system. We have a lot to lose. There are several other points in Michael's book that I don't entirely agree with; they might make fodder for more blogposts.
In any case, though I don't agree with Michael on everything, it is a brilliant book. Despite the many examples, it is reads well. With 200 pages, it's neither too long nor to short, and it has an extensive list of references. If you are interested in open science, Michael Nielsen's book is mandatory literature for you. If not, even more so! You should read this book if you're a scientist in the 21st century, or if you want to know how science in the 21st century works, or if you want to know why this is a relevant question to begin with. In short, you all should read Michael's book because he's right: We're on and about to reinvent discovery. And that reinvention will decide whether or not we'll be able to manage the problems that the future will bring.