In Super Crunchers, Ayres, 2007, 260pp, number crunching has advanced enough in size, speed and scale to surpass intuition for realworld decision-making in many cases. This has beneficial effects since the accuracy of data mining, analysis, and predictions is increased because the machine is more capable than humans of determining causal weights in equations. Kryder’s law states that the storage capacity of drives doubles every 2 years. Large stores of medical records aggregate data for realtime epidemiology. Risk assessment and management are implemented through information integration. Randomized testing allows access to new data beyond regression, e.g. alternating between a couple of ads with the more popular being emphasized more as time goes on. People are rewarded for certain types of behavior, e.g. the most profitable customers of a firm, or prevented from other types as in law enforcement. Intuitions complement statistics since people are good at hypothesizing and excluding potential factors. Determining types of data or factors that are missing often requires intuition. Both approaches can also be combined, e.g. systems knowing when certain types of data are best handled by humans, or experts basing decisions on results of statistical tools. This may also have undesirable effects. “Data huggers” are concerned about privacy. “Smart dust” or other forms of nanotechnology will be used for ubiquitous surveillance. Sellers have the advantage of systems that second-guess buyers to maximize profits. Front-line workers lose discretionary choices. Super crunching will change expertise from traditional practices to predictability. Author site. The author emphasizes that these systems can also conduct experiments through randomized tests where selections are made by chance from a set of options. The effects can be measured or additional steps can affect the sample population and be compared to a matched distribution to determine the results. For example, a web page might use a different icon style or placement in each use to determine which yields the highest likelihood of a desired outcome. This might challenge the axioms of usability experts. There can be more variables than a person would usually deal with and many observations since the data analysis is automated and instantaneous. Human creativity still has a role to play in the choice of which options to provide.