Blog: The End of Theory: The Data Deluge Makes the Scientific Method Obsolete

The End of Theory: The Data Deluge Makes the Scientific Method Obsolete
Wired (07/08) Vol. 16, No. 7, P. 108; Anderson, Chris

Thirty years ago, statistician George Box said "all models are wrong, but some are useful." At that time imperfect models were the only option to explain complex theories involving topics such as cosmological equations and human behavior. However, researchers operating in today's era of massively abundant data do not have to settle for imperfect models, and can go without models completely. Speaking at the O'Reilly Emerging Technology Conference, Google research director Peter Norvig updated George Box's maxim to say, "All models are wrong, and increasingly you can succeed without them." The massive amounts of data that are readily accessible in today's high-tech, petaflop industry enable researchers to replace traditional tools with actual data and applied mathematics. The new information age is making the traditional approach to science--hypothesizing, modeling, and testing--obsolete. Petabytes of readily available information allow researchers to analyze data without hypotheses about what the data might show, and to instead simply submit massive amounts of information to the world's biggest computing clusters and let statistical algorithms find patterns. The best example is the shotgun gene sequencing done by J. Craig Venter. Using high-speed sequencers and supercomputers to statistically analyze data, Venter went from sequencing individual organisms to sequencing entire ecosystems. By sequencing the air, Venter discovered thousands of previously unknown species of bacteria and other life forms, without hypothesizing that they were there. Experts say that such techniques are about to become mainstream.
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