I relate this to decide-in-a-fraction-of-seconds stress, when having only poor information available. See Unstressed In The Air. Decision support requires model and simulation support. Technology development often comes in jumps. And in many fields there are phases where uncertainties dominate comfort. Take automation, bioinformatics, quantitative finance , ... any incomplete decision support (control) need multitaskers to run ...
For reliable decision support you often need to extract models from data, combine them with known theories and do cross-model validation, in line precision control and what have you to analyze features, predict behavior or control processes.
Wolfram|Alpha is not just an incremental innovation. It is radical in the sense that it collects data and applies every known model, method and algorithm and allows for computing whatever can be computed about anything.
Gadgets that run a computational knowledge engine should become un-stressers?
IMO, Wolfram|Alpha has provided an unparalleled framework that allows for a broader coverage of domains, theories and content. Its technology is generic in the sense of data prepararttion an computation (symbolic code in Mathematica, webMathematica and gridMathematica, data analytics, ..)
Recently I read, a typical car contains about 2000 components, 30,000 parts and 10 million lines of software code. I am sure this software complexity is driven by performance demands and safety regulations (with a lot of redundancies). I see a car as a net of sensors and actors. A computational knowledge engine could ....