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It doesn't seem that they're trying to actually build better workers, just that they want to select against poorer workers. I'd be more interested if someone tried to teach people the traits that make more effective workers rather than just using this data as a selection tool

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By selecting the right candidates for the right traits (traits previously unquantifiable and untenable before Big Data techniques) these companies might eventually, in the long term, build better workers. For example, if the selection criteria for a career as a developer favours people capable of getting a Computer Science degree, then more people who want to be developers will get CS degrees. But in reality, getting a CS degree does not always equal good developer. Assume there are some people without CS degrees, but with the skills and behaviours and personality more suited to developer work. These people would be better hires. Selecting for those criteria would not only allow your company to hire better developers, but would (like selection for CS degrees) encourage emerging professionals to develop the desirable traits and skills defined by the selection criteria. (In some weird social darwinist way, that I myself am not entirely convinced of.)

Id say selecting better workers is a challenge in individual character development (honesty, work ethic, trust, helpfulness) while making more edfective workers is about skills and environment.

As the old adage goes, "good help is hard to find."

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