13 January 2012

Can Humans Invent New Ways of Knowing and Discovery In Time?

Michael Nielsen is a pioneer of quantum computing and a champion of open-source science. Nielsen sees the Polymath Projects -- an open online group effort by mathematicians around the world to solve interesting problems on the edge of mathematical knowledge -- as a prototype for what is possible in open-source science as a whole.
A project that I really like a lot is one called the Polymath Project, which has involved a large number of people, mostly mathematicians, from all over the world. They have started using blogs and wikis to collaborate together on difficult, unsolved mathematical problems. It’s a place where they can pool all their different types of expertise, hopefully get a conversation going, and maybe make some progress on problems that any individual amongst them might find very, very challenging. They have had some big successes. They have also had some other projects that haven’t gone so well, which is about par for the course in research. If you’re not having a lot of failures, it means you’re trying problems that are too easy. But it is exciting to see them doing this and pioneering a new way of doing research.

...By and large, [universities are] not standing in the way except through inertia. As a scientist, you build your career by publishing papers, basically. If you’re spending a lot of time doing that, it’s hard to make time to, say, share your ideas online or to share computer code online or any of the other things you might potentially be doing, even though those things have tremendous scientific value. So, in some sense, the entrenched system of reward that universities use is standing in the way of open science, but it’s not because of anything malicious on anybody’s part. It’s just that we have this established system, and it’s very difficult to get everybody to change at the same time. _Boston Review: Michael Nielsen
Reinventing Discovery by Michael Nielsen

Nielsen's open-source group approach to problem solving and discovery is one possible answer to the daunting problem of a rapidly building data glut in science. Scientists have been aware of this problem at least since the 1960s, but it is becoming particularly acute in the 21st century:
When the datasets are so large that they become unwieldy even for the Internet, innovators are spurred to invent new forms of sharing. For example, Tranche, the system behind ProteomeCommons, created its own technical protocol for sharing terabytes of data over the Net, so that a single source isn't responsible for pumping out all the information; the process of sharing is itself shared across the network. And the new Linked Data format makes it easier than ever to package data into small chunks that can be found and reused. The ability to access and share over the Net further enhances the new economics of deletion; data that otherwise would not have been worth storing have new potential value because people can find and share them.

...the biological system of an organism is complex beyond imagining. Even the simplest element of life, a cell, is itself a system. A new science called systems biology studies the ways in which external stimuli send signals across the cell membrane. Some stimuli provoke relatively simple responses, but others cause cascades of reactions. These signals cannot be understood in isolation from one another. The overall picture of interactions even of a single cell is more than a human being made out of those cells can understand. In 2002, when Hiroaki Kitano wrote a cover story on systems biology for Science magazine -- a formal recognition of the growing importance of this young field -- he said: "The major reason it is gaining renewed interest today is that progress in molecular biology ... enables us to collect comprehensive datasets on system performance and gain information on the underlying molecules." Of course, the only reason we're able to collect comprehensive datasets is that computers have gotten so big and powerful. Systems biology simply was not possible in the Age of Books.

...The problem -- or at least the change -- is that we humans cannot understand systems even as complex as that of a simple cell. It's not that were awaiting some elegant theory that will snap all the details into place. The theory is well established already: Cellular systems consist of a set of detailed interactions that can be thought of as signals and responses. But those interactions surpass in quantity and complexity the human brains ability to comprehend them. The science of such systems requires computers to store all the details and to see how they interact. Systems biologists build computer models that replicate in software what happens when the millions of pieces interact. It's a bit like predicting the weather, but with far more dependency on particular events and fewer general principles.

Models this complex -- whether of cellular biology, the weather, the economy, even highway traffic -- often fail us, because the world is more complex than our models can capture. But sometimes they can predict accurately how the system will behave. At their most complex these are sciences of emergence and complexity, studying properties of systems that cannot be seen by looking only at the parts, and cannot be well predicted except by looking at what happens.
_theatlantic: David Weinberger_via_J.Curry_via_WUWT
Too Big to Know by David Weinberger. Weinberger is a philosopher, author, marketing guru, and more.

In the early 1950s, psychologists of learning attempted to describe different levels of thinking and learning:
Recognizing that there are different levels of thinking behaviors that are important to learning, Bloom, Englehart, Furst, Hill, and Krathwohl (1956), developed a classification of levels of intellectual behaviors. This taxonomy... contains three domains: the cognitive, psychomotor and affective. The cognitive domain had six levels: knowledge, comprehension, application analysis, synthesis, and evaluation. _ Synergy PDF
Moving up the levels from primary recall knowledge up to comprehension, application, synthesis etc. represents increasing levels of understanding and ability to interconnect and utilise knowledge in productive ways.

Here is an example of an attempt to climb up the levels of knowledge, from the field of climate science: A physicist attempts to build a mental model of the radiation balance of the Earth from basic principles. Following physicist Robert Brown's (Duke U.) logic as he tries to make sense of a complex dynamic system, may give you an idea of the process of moving from general knowledge to the early stages of understanding in science.

Nielsen and Weinberger would like to help find ways around the impasse with which modern human societies are confronted. But it is not clear that entrenched modern institutions -- academia, government, media etc -- are as willing to help. In many ways, humans that are good with their brains -- and capable of teaming up with others who are also good with their brains -- represent a significant threat to current ways of doing things, or of preventing things from getting done in many cases.

Human societies are confronted with some very serious problems which may prove to be the end of us all. For example, most governments of advanced societies are wasting time and enormous resources fighting phantom, non-existent problems such as carbon hysteria. To fight this phantom problem, they are committing their citizens to a progressive energy starvation which will inevitably handicap their societies just at the moment that they are being hit the hardest by the twin problems of debt and demographic decline. Tragically, the institutions of academia and the media appear to be solidly behind governments in this suicidal agenda.

It seems a bit futile to worry about the problems and solutions presented by Weinberger and Nielsen, when our own governments and societal institutions are busy doing us in. But in reality, humans can use the powerful networking resources of modern technologies to move beyond their governments and other institutions -- at least to an important, if limited, extent.

Consider this a wakeup call of sorts. A marvelous future waits for us, if we will only wake up and make it happen.

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