To some extent, Silver became a proxy for discussions about the possibilities and pitfalls in big data. Those who agreed with Silver’s approach said his work demonstrated irrefutably that opinion-based punditry was dead, unable to compete with the claimed objectivity of statistics. Those who challenged Silver pointed out that a range of models co-exist and not all can be correct.
For his part, Silver told The Observer, “I’d be the first to say you want diversity of opinion. You don’t want to treat any one person as oracular.”
Science reporters know that, and the explosion in big data offers a way for newsroom managers to rethink how they can use those journalists’ reservoir of knowledge. There aren’t many science writers left at American newspapers, unfortunately, but they should be called in on big-data stories wherever they exist.
I am a computational multibody dynamicist with 30+ years in modeling and simulation of highly nonlinear differential equations of motion. One thing I've learned about difficult formulations is the easy chance of computing spurious solutions. Find the right answers can be very difficult when numerical chaos controls the predictor-corrector approach for solution. While Hollywood obtains money for movie making STEM struggles to get sufficient funding to attack critical math modeling and simulation issues. But at least physical science provides "checking functions" by which one can estimate the error. Using math in other applications like business may require numerical methods for controlling rampant error. Computing correct results is still something of an art form. I recommend investing in SIAM numerical method researchers.
#1 Posted by Al Kovacs, CJR on Tue 15 Jan 2013 at 12:29 PM