Ultimately, all of these new developments raise philosophical questions. As professional performance becomes easier to measure and see, will we become slaves to our own status and potential, ever-focused on the metrics that tell us how and whether we are measuring up? Will too much knowledge about our limitations hinder achievement and stifle our dreams? All I can offer in response to these questions, ironically, is my own gut sense, which leads me to feel cautiously optimistic. But most of the people I interviewed for this story—who, I should note, tended to be psychologists and economists rather than philosophers—share that feeling.

Scholarly research strongly suggests that happiness at work depends greatly on feeling a sense of agency. If the tools now being developed and deployed really can get more people into better-fitting jobs, then those people’s sense of personal effectiveness will increase. And if those tools can provide workers, once hired, with better guidance on how to do their jobs well, and how to collaborate with their fellow workers, then those people will experience a heightened sense of mastery. It is possible that some people who now skate from job to job will find it harder to work at all, as professional evaluations become more refined. But on balance, these strike me as developments that are likely to make people happier.

Nobody imagines that people analytics will obviate the need for old-fashioned human judgment in the workplace. Google’s understanding of the promise of analytics is probably better than anybody else’s, and the company has been changing its hiring and management practices as a result of its ongoing analyses. (Brainteasers are no longer used in interviews, because they do not correlate with job success; GPA is not considered for anyone more than two years out of school, for the same reason—the list goes on.) But for all of Google’s technological enthusiasm, these same practices are still deeply human. A real, live person looks at every résumé the company receives. Hiring decisions are made by committee and are based in no small part on opinions formed during structured interviews.

One only has to look to baseball, in fact, to see where this all may be headed. In their forthcoming book, The Sabermetric Revolution, the sports economist Andrew Zimbalist and the mathematician Benjamin Baumer write that the analytical approach to player acquisition employed by Billy Beane and the Oakland A’s has continued to spread through Major League Baseball. Twenty-six of the league’s 30 teams now devote significant resources to people analytics. The search for ever more precise data—about the spin rate of pitches, about the muzzle velocity of baseballs as they come off the bat—has intensified, as has the quest to turn those data into valuable nuggets of insight about player performance and potential. Analytics has taken off in other pro sports leagues as well. But here’s what’s most interesting. The big blind spots initially identified by analytics in the search for great players are now gone—which means that what’s likely to make the difference again is the human dimension of the search.

The A’s made the playoffs again this year, despite a small payroll. Over the past few years, the team has expanded its scouting budget. “What defines a good scout?,” Billy Beane asked recently. “Finding out information other people can’t. Getting to know the kid. Getting to know the family. There’s just some things you need to find out in person.”