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Worldview Analysis, World Models, and Predicting the Future
in the news: Consider two recent articles: "The Wisdom of Crowds." in the December 17th issue of The Economist and "The Department of Pre-Crime" in the January 2012 issue of Scientific American. What do they have in common? A hint is provided by a third article, "The Machine That Would Predict the Future" in the December 2011 Scientific American. Give up? All three articles are concerned with data mining and using computer aided modeling to predict some type of future behavior involving humans. The first two discuss how to better control crowds/improve traffic flow and how predictive policing techniques work. The efforts described are narrowly focused and concerned with predicting how pedestrians move and where the next crimes are likely to occur. The effort described in the third article, by contrast, is mind-boggling in its scope and ambition. As author David Weinberger summarizes the Futur ICT / Living Earth Simulator project, "Researchers plan to build a computing system that would model the entire world to predict the future." This monumental effort, expected to employ hundreds of scientists for an initial duration of ten years, has recently secured promises of over one billion Euros in funding!
commentary and analysis (by Stephen P. Cook, project Worldview, www.projectworldview.org): The first thing one sees on the Futur ICT website is the logo "Unleashing the Power of Information for a Sustainable Future" (think "Sustainability," worldview theme #23A). They plan on combining data mined from all over (including social networks and an ever growing number of physical sensors) with statistical techniques to uncover trends. Expect them to have unsurpassed skill at modeling complex socio-economic systems--see "Dancing with Systems," theme 13. And expect them to struggle mightily with the "impact of behavioral change on our environment" (a phrase I pulled off the website's Q&A page).
To better understand those difficulties, consider how this predictive task differs from simpler ones. In modeling pedestrian traffic, if people behave like the mindless particles in an ensemble that a theoretical physicist might study so much the better. But people have minds of their own--and their interactions are almost infinitely more complicated than molecules bouncing off the walls of a container. So I expect the prospects for successful predictions coming out of models (like the Living Earth Simulator) that significantly depend upon the distant future behavior of lots of people to be orders of magnitude more difficult to achieve than success with modeling crowd movement or geographically predicting crime locations.
What role might worldview characterization and analysis play in using world models to make future global predictions? It depends on both the type of problem and time frame being considered. For some problems, data from diverse sources will be abundant and can be used to establish short-term trends. Thus gauging future global warming due to human activity can be tackled by defining the expected mix of such activity, using government, industry, and consumer data, and assessing its overall carbon footprint by using energy production/consumption, related pollution data, etc. Trends uncovered would be projected into the future. Worldview related input would not be needed. For other types of problems--or even similar ones considered over longer time frames (centuries not decades) where extrapolating current trends hits limits--using it might make more sense.
Certainly it could be important in answering "what
if?" type questions like, 1) How might average global temperatures
change over the next two hundred years as the world's numerous poor people
become more affluent consumers given various scenarios in which
beliefs/values guide behavior? or 2) How might any of several global
variables of interest (related to energy, environ-
While descriptive qualitative characterization of worldviews has value, quantitative input is what computer programs need. Assembling this using data from public opinion surveys is an approach which many (including Project Worldview) have employed in the past. The basic problem with it is that you're depending on people to both understand and honestly answer questions. Some may delude themselves and give "idealized" answers that uphold phony values--answers based on the way things (like their behavior) ought to be (not their actual behavior). Taking a dim view of human nature (see "Cynicism," theme #36A), we might even suspect certain answers from intelligent, psychologically well balanced citizens. Then there are the opposite class of people...In thinking about them I'm reminded of what marketing strategy pioneer Ernest Dichter said. He felt that asking shoppers why they bought a certain product was like "asking people why they thought they were neurotic!"
I'd say that future methods of characterizing and quantifying worldviews should go beyond individual brainstorming and relying on public opinion surveys, and make every effort to employ the latest data mining, social media, and related technologies. In this regard consider two developments. First, we have just put online the beginning of our version 3.0 worldview characterization and analysis structure. While it builds on version 2.0, its also employs hundreds of links to Wikipedia articles. With help from others could it eventually evolve into a wiki format? Given the trends described in a 2008 Nature news feature "Big data: Wikiomics" I suppose this is a possibility! Second, according to an article about social media in the December 31 2011 issue of The Economist, Andreas Weigend, founder of Stanford's Social Data Lab has developed a product that allows one to experience someone else's digital identity--like metaphorically "wearing the hat" of an Islamic fundamentalist for example. Sounds like global educational efforts aimed at teaching students about differences in worldviews could benefit from this!
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