 PRESIDENT’S WEB LOG Tim Mack, President |
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Study the Future
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No. 4 One of the most interesting questions to come before us is What is happening to the Study of the Future? Is it getting easier or harder to understand change and all its nuances? The assumption underlying this question is that progress, although it has been getting a bad name the past few decades, is not only a real possibility but might be driven by discoveries in information technology….not just in hardware and software, but in dataware….how we are able to manage very large amounts of complex information. Certainly one of the most interesting developments (beyond third order data theory) is the growing sophistication of the virtual world. By this I don’t necessarily mean optical virtuality (such as 3-D holographics), but more modeling of the real world in the digital one. Moving beyond cartoon worlds like Second Life into serious attempts to capture the activity of a business or even a government….And when businesses start setting up conference facilities and offices in a Second Life or similar format, does that immediately make the model ‘fully real?’ I would love to hear your own experiences in this arena, but let me also voice my biggest concern about modeling of any sort, starting with the MIT godfather model of world resources, created for the Club of Rome and their "Limits to Growth" project. The underlying assumptions (the rules under which the model operates) must be shared and the model should ideally be transparent. That is, the user (as distinguished from the builder) needs to understand why it acts the way it does, for verification purposes. Useful models need to be models one can trust or at least understand or they confuse the situation rather than clarifying it. That said, I would also add that the more
complex the model (i.e. the more collateral factors that it includes
in its calculations) the more it approximates how futures research
actually ought to operate. It is a complicated interactive world out
there and simplifying the situation for the sake of a quick
conclusion is a serious disservice to all involved. Now these two
goals are pretty obviously in contradiction (more complexity/more
transparency) and that is were advances in data ordering (data about
data) come in handy. If you are engaged in this important work,
please tell the rest of us all about it (within the limits of
intellectual property and common sense).
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