Current “big data” and “API-ification” trends can trace their roots to a definition Kant first coined in the 18th century. In his Critique of Pure Reason, Kant drew a dichotomy between analytic and synthetic truths, Venture Beat reports.
An analytic truth was one that could be derived from a logical argument, given an underlying model or axiomatization of the objects the statement referred to. Given the rules of arithmetic we can say “2+2=4” without putting two of something next to two of something else and counting a total of four.
A synthetic truth, on the other hand, was a statement whose correctness could not be determined without access to empirical evidence or external data. Without empirical data, I can’t reason that adding five inbound links to my webpage will increase the number of unique visitors 32%.
In this vein, the rise of big data and the proliferation of programmatic interfaces to new fields and industries have shifted the manner in which we solve problems. Fundamentally, we’ve gone from creating novel analytic models and deducing new findings, to creating the infrastructure and capabilities to solve the same problems through synthetic means.
… Google and Amazon serve as early examples of the shift from analytic to synthetic problem solving because their products exist on top of data that exists in a digital medium. Everything from the creation of data, to the storage of data, and finally to the interfaces scientists use to interact with data are digitized and automated.