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Google's Answer to Filling Jobs Is an Algorithm
An anonymous reader tipped us to a New York Times article about Google's newest HR tool: an algorithm. Starting soon, the company (which gets roughly 100,000 applications a month) will require all interested applicants to fill out an in-depth survey. They'll be using a sophisticated algorithm to work through the submitted surveys, matching applicants with positions. The company has apparently doubled in size in each of the last three years. Even though it's already 10,000 employees strong Laszlo Bock, Google's vice president for people operations, sees no reason the company won't reach 20,000 by the end of the year. This will mean hiring something like 200 people a week, every week, all year. From the article: "Even as Google tries to hire more people faster, it wants to make sure that its employees will fit into its freewheeling culture. The company boasts that only 4 percent of its work force leaves each year, less than other Silicon Valley companies. And it works hard to retain people, with copious free food, time to work on personal projects and other goodies. Stock options and grants certainly encourage employees to stay long enough to take advantage of the company's surging share price. Google's hiring approach is backed by academic research showing that quantitative information on a person's background -- called 'biodata' among testing experts -- is indeed a valid way to look for good workers."
It depends how good their algorithm is - let's say it looks at what proportion of your life since graduating you've been in work, where more is better. That's a disadvantage to women because they (generally) take time off to have/raise kids and so on, even though the algorithm isn't specifically designed to discriminate against them.
(OK, so it's a trivial case, but you get the general idea)
I suspect there could be plenty of arguments in court about whether some nuance of the algorithm treats some group unfairly or not...
It's easy to maintain a low turnover of staff as long as the vast majority of your staff isn't fully vested, and the stock is moving upwards. As soon as the growth in staff numbers slow down, though, you're going to see the turnover percentage increase significantly as a larger and larger percentage of staff have been there for the full 4 year vesting period of their options, and the company starts seeing pressure for lower refresher grants.
You can't hide bad questions behind an algorythm. The interview process has lots of laws around it now, and it's well established that there are only some questions you can ask. Here's a great example:
The questions range from the age when applicants first got excited about computers...
This question doesn't directly reveal your age, but a clever interviewer can glean much from it. "Oh, got excited in computers at 22, eh? Probably older than I thought. We don't want old employees we want young ones."
It is illegal to ask some questions in an interview. Age related questions are one of them. You are only allowed to ask questions that pertain to your performance of the job at hand. For example, I can ask someone "would you have a problem lifting heavy boxes?" but I can't ask how old you are and make a judgement because you are 40 that you can't lift heavy boxes. The above question you as a logical geek might think is iffy, but to a lawyer, it's shark bait and they'll be all over it, so don't ask it. If you ask a question that falls into this category, you open yourself up to a gender/age/racial discrimination lawsuit. These and many others are protected classes under the law.
And there's a great reason why an interview is a poor indicator of performance... because people lie!!! It's a sales process. They want your job, and you want the best candidate. Last two people I let go both gave great interviews, but when they actually worked, they sucked. They had all the right answers in the interview, but there is no escaping performance reviews.
0% firing rate is impossible, as is 100% retention. 96% retention is a stellar figure, even for silicon valley. I think they should be pretty happy that number.
"All great wisdom is contained in .signature files"
No. See Griggs v. Duke Power Co., 401 U.S. 424, 431-2 (1971). A plaintiff can show that some employment criterion or criteria results in a disparate impact upon a protected group, regardless of whether discrimination is overtly intended or not. The burden of proof then shifts to the employer to show that said criteria are a necessary requirement for the job(s) in question. If they can't, they lose. Even if they can, if the plaintifss can come up with an alternate business practice that satisfies the employer's interests without resulting in a disparate impact, they lose. Good or bad, that's the law.
ABSURDITY, n.: A statement or belief manifestly inconsistent with one's own opinion.
10,000 employees at $200k each is $2 billion a year, not $20 billion a year. Google is making enough to cover those costs even if they double the number of employees and do not increase revenue at all. You can look at a summary of their revenue, and their expenses as a portion of revenue here: http://biz.yahoo.com/e/061108/goog10-q.html
They are making a handsome profit.
As you might guess, there is a whole tangle of legal and ethical issues surrounding testing in personnel selection.
My understanding (IANAL etc) is that you are supposed to assess only the skills, aptitude, etc. that you can defend as related to the job. If that happens to be correlated with sex, race, age, etc., the correlation is not a problem, but you cannot use those things as a proxy for what you're really interested in. For example, in a job that requires quick responses, you can test people's reaction times, but you cannot automatically exclude people based on age (even though age may be correlated with reaction time).
More direct assessment is better anyway. Suppose you are hiring for a job that requires math skills, which you believe is correlated with gender, which you believe is correlated with cat ownership. Even if those correlations exist, you'd still get more accurate results measuring the math skills directly rather than measuring cat ownership which is correlated with something that is correlated with what you need.
No problem. Then, they can devise an algorithm to decide who to lay off.