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Sharing insurance costs with the sharing economy

One consequence of the “sharing economy” that hasn’t been widely discussed, at least as far as I’ve seen, is how the externalities are being absorbed. Specifically, insurance costs.

Maybe because it’s an ongoing process, but for both Uber and AirBnB, the companies tell individuals who drive that their primary car insurance should be in use, and they tell individual home- or apartment-dwellers that their renters insurance should apply.

In other words, if something goes wrong, the wishful thinking goes, the private, individual insurance plans should kick in.

When people have tried to verify this, however, they responses have been mixed and mostly negative. The insurance companies obviously don’t want to cover a huge number of people for circumstances they didn’t expect when they offered the coverage.

So, if an Uber driver gets into an accident while ferrying a passenger, it’s not clear whether their primary insurance will cover it. It’s even less clear if the driver is using the Uber app and is on their way to get a passenger. Similarly, if an AirBnB guest falls because of a broken staircase, it’s not clear who is supposed to pay for the damages to the person or the staircase. What if the guest burns down the house?

So far I don’t think it’s been fully decided, but I think one of two things could happen.

In the first scenario, the insurance companies will really refuse to cover such things. To do this they will have to have a squad of investigators who somehow make sure the customer in question was or was not hosting a guest or driving a customer. That would involve suspicion and some amount of harassment, which customers don’t like.

In the second scenario, which I think is more likely given the above, the insurance companies will quietly pay for the damages accrued by Uber and AirBnB usage. They won’t advertise this, and if asked, they will discourage any customer from doing stuff like that, but they also won’t actually refuse to pay the costs, which they will simply transfer to the larger pool of customers. It doesn’t really matter to them at all, in fact, as long as they are not the only insurance company with this problem.

That will mean that the quants who figure out the costs of insurance will see their numbers change over time, depending on how much more the insurance is being called into action. I expect this to happen a lot more for Uber drivers, because if you are an Uber driver 40 hours a week, that means you’re always in your car. So our insurance costs will go up in proportion to how many people become Uber drivers. I expect this to happen somewhat more for AirBnB renters, because the house or apartment is in constant use; if it’s being rented by rowdy partiers, all the more. Our renters insurance will go up in proportion to how many people are AirBnB renters.

That reminds me of a story my dad used to like telling, whereby a friend of his rented out his Cambridge house to a Harvard professor, and when he came back it was totally trashed, including what looked like a bonfire pit in the living room. The professor in question was Timothy Leary.

Anyhoo, my overall conclusion is that the new “sharing economy” businesses really will end up sharing something with the rest of us soon, namely the cost of insurance. We will all be paying more for car insurance and home- or renters-insurance if my guess is accurate. Thanks, guys.

Categories: economics, rant, statistics

The Police State is already here.

The thing that people like Snowden are worried about with respect to mass surveillance has already happened. It’s being carried out by police departments, though, not the NSA, and its targets are black men, not the general population.

Take a look at this incredible Guardian article written by Rose Hackman. Her title is, Is the online surveillance of black teenagers the new stop-and-frisk? but honestly that’s a pretty tame comparison if you think about the kinds of permanent electronic information that the police are collecting about black boys in Harlem as young as 10 years old.

Some facts about the program:

  • 28,000 residents are being surveilled
  • 300 “crews,” a designation that rises to “gangs” when there are arrests,
  • Officers trawl Facebook, Instagram, Twitter, YouTube, and other social media for incriminating posts
  • They pose as young women to gain access to “private” accounts
  • Parents are not notified
  • People never get off these surveillance lists
  • In practice, half of court cases actually use social media data to put people away
  • NYPD cameras are located all over Harlem as well

We need to limit the kind of information police can collect, and put limits on how discriminatory their collection practices are. As the article points out, white fraternity brothers two blocks away at Columbia University are not on the lists, even though there was a big drug bust in 2010.

For anyone who wonders what a truly scary police surveillance state looks like, they need look no further than what’s already happening for certain Harlem residents.

Workplace Personality Tests: a Cynical View

There’s a frightening article in the Wall Street Journal by Lauren Weber about personality tests people are now forced to take to get shitty jobs in customer calling centers and the like. Some statistics from the article include: 8 out of 10 of the top private employers use such tests, and 57% of employers overall in 2013, a steep rise from previous years.

The questions are meant to be ambiguous so you can’t game them if you are an applicant. For example, yes or no: “I have never understood why some people find abstract art appealing.”

At the end of the test, you get a red light, a yellow light, or a green light. Red lighted people never get an interview, and yellow lighted may or may not. Companies cited in the article use the tests to disqualify more than half their applicants without ever talking to them in person.

The argument for these tests is that, after deploying them, turnover has gone down by 25% since 2000. The people who make and sell personality tests say this is because they’re controlling for personality type and “company fit.”

I have another theory about why people no longer leave shitty jobs, though. First of all, the recession has made people’s economic lives extremely precarious. Nobody wants to lose a job. Second of all, now that everyone is using arbitrary personality tests, the power of the worker to walk off the job and get another job the next week has gone down. By the way, the usage of personality tests seems to correlate with a longer waiting period between applying and starting work, so there’s that disincentive as well.

Workplace personality tests are nothing more than voodoo management tools that empower employers. In fact I’ve compared them in the past to modern day phrenology, and I haven’t seen any reason to change my mind since then. The real “metric of success” for these models is the fact that employers who use them can fire a good portion of their HR teams.

Categories: data science, modeling, rant

Fingers crossed – book coming out next May

As it turns out, it takes a while to write a book, and then another few months to publish it.

I’m very excited today to tentatively announce that my book, which is tentatively entitled Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, will be published in May 2016, in time to appear on summer reading lists and well before the election.

Fuck yeah! I’m so excited.

p.s. Fight for 15 is happening now.

Predatory credit score-based insurance fees

I’ve been looking into who uses credit scores – FICO scores or other alternative scores – and I’ve found that the insurance industry is a major user.

Homeowners insurance rates, for example, varies wildly by state depending on what kind of credit score you have, often more than doubling for people with poor credit versus people with excellent credit. This is in spite of the fact that homeowners insurance applies not to the payments of mortgages but rather to the contents of an apartment or home.

Similarly, auto insurance rates vary by credit score, even though someone with a poor credit score isn’t obviously a bad driver. For example, in Maryland, people with bad credit scores can be charged 40% more just for having bad credit scores.

Statistics like this make me wonder, how much of this price discrimination comes from the insurance companies trying to understand and account for actual risk, and how much comes from their understanding that poorer people have fewer options and will simply pay predatory rates?

And just in case you’re a believer in free markets and fair competition, and think such predatory behavior would be whisked away in a competitive market, insurance companies actually target people who don’t shop around and charge them more. In other words, it’s not a free market if not everyone actually has good information.

Tell me if you have more examples like this, I’m a collector!

Everyone hates college administrators

If you were wondering why I didn’t blog yesterday, which you probably weren’t (confession: I don’t read other peoples’ blogs and I don’t listen to any podcasts. So I would never, ever ask anyone to read my blog or listen to my podcast), it was because I was completely confused and irritated by this NYTimes opinion piece on the rising cost of college, written by University of Colorado Law Professor Paul Campos.

I really think the Times needs to either have footnotes or hyperlinks in their opinion pieces, because this guy was playing so fast and loose with his numbers that I had really no idea what he was talking about most of the time. That’s saying something considering that this, the cost of college and its causes, is something I have spent many hours thinking about and researching.

So what happened was, I didn’t have time to completely formulate my opposition to why his reasoning was muddled and confusing. I spent way too much time trying to figure out where he was getting his data. Waste of time.

Good news, though, my Slate Money co-host Jordan Weissman has done all that work for us, in his piece aptly entitled The New York Times Offers One of the Worst Explanations You’ll Read of Why College Is So Expensive. Who says procrastination doesn’t work?

As usual, if you’ve ever listened to my podcast (and this isn’t a request for you to do so!), I don’t agree completely with Jordan. However, my delta of agreement with Jordan is very manageable compared to the delta of disagreement I had with Campos. Basically I would quibble with laying any of the blame at the feet of instructors, but since he barely does that, let’s just go with his awesome take-down.

Take-down of what? Well, Campos basically hates college administrators, and pretends there’s no other problems in the world except them. It’s a mistake that he doesn’t have to make.

I mean really, who doesn’t hate college administrators? As a former college administrator myself, I know it’s universal; I certainly hated myself the entire time.

But that doesn’t mean there’s no other factors at all. Reduced public money for colleges is in fact a huge problem, especially when you pair it with the increased federal aid money going to students at corrupt for-profit colleges. Corinthian obtained $1.4 billion in federal grant and loan dollars in 2010 alone, more than the 10 University of California campuses combined for that same year. This system is in terrible need of repair.

Instead of simply hating on college admin, or rather, in addition to hating on admin, can we start thinking about an alternative no-frills state college system that is truly affordable and gives honest and basic instructions without trying to compete on the US News & World Reports stage?

Categories: education, rant

The arbitrary punishment of New York teacher evaluations

The Value-Added Model for teachers (VAM), currently in use all over the country, is a terrible scoring system, as I’ve described before. It is approximately a random number generator.

Even so, it’s still in use, mostly because it wields power over the teacher unions. Let me explain why I say this.

Cuomo’s new budget negotiations with the teacher’s union came up with the following rules around teacher tenure, as I understand them (readers, correct me if I’m wrong):

  1. It will take at least 4 years to get tenure,
  2. A teacher must get at least 3 “effective” or “highly effective” ratings in those three years,
  3. A teacher’s yearly rating depends directly on their VAM score: they are not allowed to get an “effective” or “highly effective” rating if their VAM score comes out as “ineffective.”

Now, I’m ignoring everything else about the system, because I want to distill the effect of VAM.

Let’s think through the math of how likely it is that you’d be denied tenure based only on this random number generator. We will assume only that you otherwise get good ratings from your principal and outside observations. Indeed, Cuomo’s big complaint is that 98% of teachers get good ratings, so this is a safe assumption.

My analysis depends on what qualifies as an “ineffective” VAM score, i.e. what the cutoff is. For now, let’s assume that 30% of teachers receive “ineffective” in a given year, because it has to be some number. Later on we’ll see how things change if that assumption is changed.

That means that 30% of the time, a teacher will not be able to receive an “effective” score, no matter how else they behave, and no matter what their principals or outside observations report for a given year.

Think of it as a biased coin flip, and 30% of the time – for any teacher and for any year – it lands on “ineffective”, and 70% of the time it lands on “effective.” We will ignore the other categories because they don’t matter.

How about if you look over a four year period? To avoid getting any “ineffective” coin flips, you’d need to get “effective” every year, which would happen 0.70^4 = 24% of the time. In other words, 76% of the time, you’d get at least one “ineffective” rating just by chance. 

But remember, you don’t need to get an “effective” rating for all four years, you are allowed one “ineffective rating.” The chances of exactly one “ineffective” coin flip and three “effective” flips is 4 (1-0.70) 0.70^3 =  41%.

Adding those two scenarios together, it means that 65% of the time, over a four year period, you’d get sufficient VAM scores to receive tenure. But it also means that 35% of the time you wouldn’t, through no fault of your own.

This is the political power of a terrible scoring system. More than a third of teachers are being arbitrarily chosen to be punished by this opaque and unaccountable test.

Let’s go back to my assumption, that 30% of teachers are deemed “ineffective.” Maybe I got this wrong. It directly impacts my numbers above. If the overall probability of being deemed “effective” is p, then the overall chance of getting sufficient VAM scores will be p^4 + 4 p^3 (1-p).

So if I got it totally wrong, and 98% of teachers are described as effective by the VAM model, this would mean almost all teachers get sufficient VAM scores.

On the other hand, remember that the reason VAM is being pushed so hard by people is that they don’t like it when evaluations systems think too many people are effective. In fact, they’d rather see arbitrary and random evaluation than see most people get through unscathed.

In other words, it is definitely more than 2% of teachers that are called “ineffective,” but I don’t know the true cutoff.

If anyone knows the true cutoff, please tell me so I can compute anew the percentage of teachers that are arbitrarily being kept from tenure.

Categories: education, rant, statistics
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