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When the Hiring Boss Is an Algorithm
Hugh Pickens writes "Joseph Walker writes at the WSJ that although personality tests have a long history in hiring, sophisticated software has now made it possible to evaluate more candidates, amass more data and peer more deeply into applicants' personal lives and interests. This allows employers to predict specific outcomes, such as whether a prospective hire will quit too soon, file disability claims, or steal. For example after a half-year trial that cut attrition by a fifth, Xerox now leaves all hiring for its 48,700 call-center jobs to software. Xerox used to pay lots of attention to applicants who had done the job before. Then, an algorithm told the company that experience doesn't matter. It determined what does matter in a good call-center worker — one who won't quit before the company recoups its $5,000 investment in training. By putting applicants through a battery of tests and then tracking their job performance, Evolv has developed a model for the ideal call-center worker (PDF). The data recommend a person who lives near the job, has reliable transportation and uses one or more social networks, but not more than four. He or she tends not to be overly inquisitive or empathetic, but is creative. 'Some of the assumptions we had weren't valid,' says Connie Harvey, Xerox's chief operating officer of commercial services. However, data-based hiring can expose companies to legal risk. Practices that even unintentionally filter out older or minority applicants can be illegal under federal equal opportunity laws. If a hiring practice is challenged in court as discriminatory, a company must show the criteria it is using are proven to predict success in the job."
tends not to be overly inquisitive or empathetic
Well, if the bean counters consider the lack of those qualities to be what makes for a good callcenter worker then it's no wonder that the quality of support has gone down as fast as it has. Six or seven years ago when I called into support there was about a 50% chance of reaching someone who was smart and could solve my problem without relying on a script (which never solve my problem because if it can be found in available documentation I've already tried it before calling support), today there's maybe a 5% change if that.
There are 4 boxes to use in the defense of liberty: soap, ballot, jury, ammo. Use in that order. Starting now.
Yeah. This basically acclerates the process that's already started with H.R. drones. Getting hired is already about who can game the process the best and H.R. bozos try to use a strict set of rules to put people into boxes instead using simple human judgement. This just codifies it even further.
There's a growing trend of hiring intelligent Japanese, Chinese and Indian workers at a fraction of cost to U.S. ones
You think labor rates are cheap in Japan? GDP per-capita in Japan is about 4X that of China and about 10X that of India. Japan has plenty of talent but it isn't particularly cheap or abundant talent. Japan, like the US, relies heavily on automation. Labor intensive industries left Japan years ago just like they did in the US.
The U.S. ranks 23rd among developed nations in the percentage of students with undergraduate degrees in science or engineering who are employed in related fields
Now figure out what that means. It's not at all clear what significance is in having a lower percentage of engineers at a portion of the population. The US is also the third largest country in terms of population so even if they produce a lower percentage of engineers than some other countries they still will produce larger absolute numbers than most of them. You seem to be implying that graduating a lower percentage of engineers/scientists will result in negative consequences. While that might be true you have to back it up with more than just vague implications.
That $5k is an average number for call center training. For professional positions, it's between 1 and 1.5x annual salary.
Sadly, your brother needs to adopt better parents, because that's how you get jobs. Do you think Mitt Romney, son of a Mexican immigrant who was a migrant farmer and never made more than a subsistence wage and never interacted outside of the migrant community would have had job offers in big firms or ready-made partnerships with well-connected businessmen? Of course not. Take your brother, add in a network of hundreds of friends and colleagues in various fields, have someone prominent in the community and in business vouch personally for his abilities, and I can almost guarantee him a job in under a month, and a 6 figure job in under 5 years - far less if it turns out your brother is both personable and responsible. Add in some ability (numbers, management skills, sales ability) - it doesn't even need to be technical in any way, and he'll be on his way to a very comfortable lifestyle.
Can you claw your way up from the bottom? Yes, but you have to be exceptionally lucky in finding a job with growth and a manager who sees ability and is not threatened by it. Or you have to just be downright good and start your own enterprise from the ground up. The latter generally requires the moral flexibility to spend a lot of time in the gray area of the law (skirt regulation as much as you can) and personal relationships (be a ruthless backstabbing sonofabitch).
Is it just my observation, or are there way too many stupid people in the world?
As usual, most of the respondents either did not RTFA, or simply did not understand it because many of the respondents have got it exactly backwards.
Management did not just make up a set of characteristics they thought would be good (in this case hire local drone) and hire those after doing a drone-test. That's the way it had been done for the last few thousand years.
So here's what happened.
A company tests applicants for a very broad set of characteristics.
They track the performance of the hires.
They compare the success of the hires back to the characteristics found in the test.
They make a model of the successful hires and then use that model to select future hires.
Scientific model:
Construct hypotheses
Gather data
Conduct test
compare result to hypotheses
refine hypotheses
Anyone that is complaining about the algorithmic process and it's outcome has no idea how most people are typically hired.
For the most part, It still boils down to 1: being someone's buddy/relative and 2: looking like someone the HR boss would like to hang out with.
So I, for one, welcome our new algorithmic masters. ( having neither buddy nor looking like someone you would want to hang out with)
Also, this is very far from being new. I know of one upscale hotels started doing this a couple or three decades ago.
They gave all their employees a variety of tests and observed what characteristics were associated with the successful ones in the various positions.
Then, when people apply, they assign them to the position they'll be successful in. The end result is that successful floor-cleaners are happy and productive floor-cleaners, and people whose profile fits the front desk are happy and successful there. And it should be obvious that swapping those two people might create two very resentful employees. It really shows, too, if you ever stayed in a place like that how the good moods of the employees is almost Stepford-spooky.
I've heard my share of stories of Japanese workers not doing much the first many hours, then cramming at the end only because it's taboo to leave before your superior, so long hours with not much more accomplished.
Not sure how true, but if it sounds too good to be true, it probably is. I can't see Japanese not getting burnt out if they actually worked 2x as much.
No shit, he works for the company. And while you're spouting the standard crap about how codified tests can't possibly detect how awesome you are as an individual, his company has statistics that prove their system works, continually feed them back into their system to improve it, and are confident enough to have made it their core business model. Are you going to put your money where your mouth is, or just keep denying that humans as a group are fairly predictable?
In all fairness, algorithmic hiring will work best for jobs where you want someone who's good enough, and not necessarily the best. Call centre staff, grunt-level programmers, IT, that sort of thing. If getting the absolute best candidate from all applicants will make or break your company, trusting an algorithm (or heuristic) to do the job is a bad idea.
Oh, and the word is reeks.