Ending Feb 09
Science research tries to "model" a complex system by something simple, accurate, amenable to math and predictive. My hypothesis is that in complex internet systems (such as search, ads), humans change the underlying system faster than researchers can abstract and understand models, and hence, we should abandon the "model" based approach to research. For example, someone models Internet search users, but alas, an Engineer adds a new vertical search (say showtimes, products, celebrity profiles, whatever) and the models no longer apply. Diehard modelers will tell you this means we are just not modeling things at right granularity. And then they ask, what is the alternative? Experiment and tweak. As Leslie pointed out, I seem to be making a giant case for Machine Learning research. With a giant tweak that humans in the loop means humans alter the system, strategically.
ps: David Parkes, ever smart even over dinner, pushed me to a corner, saying experiment-and-tweak might just have us hike (climb?) the hills. Without models (inaccurate, non-predictive, mathematically amenable), we might never have new starting points.