Chinese Train Derailment

On July 23^rd, two-high speed trains collided in China causing 40 deaths and 192 injuries.  The crash is being blamed on government corruption and the ensuing cover-up has caused a public furor.  Many see the situation as a metaphor for the unchecked growth that the Chinese government is pursuing.

Let me be clear, I admire the Chinese for using the government to build up their infrastructure.  The 20^th century American investment in our highway system has returned untold dividends.  There are a few things that I believe are difficult to fund too much: preventive maintenance and upgrades to basic infrastructure, basic science, and education (this does not include the current debauchery of the student loan system, but that’s a post for another day).

So I don’t fault the Chinese for building up their infrastructure.  Where I do find blame is their rampant government corruption.  Reports have come out stating that the Chinese government has been taking people’s land without fair compensation.  The WSJ reports that there have been two recent firings of high ranking members of the Chinese railways ministry for graft.  I think in the coming weeks we’ll find that the Chinese trains and their tracks weren’t built to spec with the government officials pocketing the difference between public safety and peril.

Listen, I live in Chicago, so I know a corrupt government (Some attribute “Vote early and vote often.” to our own Al Capone, but it was used earlier).  Power corrupts, and that is certain.  But there are ways to check government power and therefore corruption.

It’s said that “Sunlight is the best disinfectant.”  A system of checks and balances for the government is needed, with an educated public and the media playing a vital role.  And on a positive note, the Chinese people are increasingly connected and working together to hold the government accountable.

As noted in this WSJ article, in 2000 there were 10 million Chinese on the Internet.  Now there are estimated to be 485 million.  The Chinese version of Twitter, Weibo, is an increasingly popular communication tool.  The WSJ notes

The government censors much content on the Internet, but it has allowed a surprising degree of openness on Weibo and other sites. In part, experts say, that's because it sees online commentary as a release valve for the public, but the government also fears the fury that would erupt if it took away those outlets.

I disagree with the experts here.  The Chinese government doesn’t censor Weibo to allow a release valve for the public.  Weibo isn’t censored because it’s not feasible to censor it and still allow it to exist.  How can you monitor, much less politically censor, a Twitter clone that has nearly eight times more users than Twitter?  To me there are two choices for the Chinese government in this situation: shut down Weibo outright or have a trivial amount of censorship of the site that amounts to nothing.

While the Internet is relatively open, China is cracking down on traditional state media reporting of the train accident, as reported by the New York Times today.

The sudden order from the Communist Party’s publicity department, handed down late Friday, forced newspaper editors to frantically tear up pages of their Saturday editions, replacing investigative articles and commentaries about the accident that killed 40 people in eastern China with cartoons or unrelated features.

Replacing tragic news with cartoons?  This would be funny if it weren’t so sad.  Because the Chinese people won’t be able to get news from the state-run media, they’ll increasingly look to the Internet.  I just hope that they’ll still be able to access it.

Cars That Drive Themselves!

I can’t wait until I can get in the driver’s seat of a car, input my destination into the GPS, and then take a nap as my car drives me there.  This sci-fi future, I believe, is closer than many people think.

Americans won’t just accept a fully autonomous self-driving car from out of nowhere.  It will have to happen piece by piece, where AI takes over one small thing then the next.  And indeed, this is what we find happening. 

In 2006, Lexus introduced a car that could parallel park itself.  That feature is becoming more and more common.  Intelligent braking if the driver is not acting is another recent example of cars driving themselves.  This feature has been extolled by the Insurance Institute for Highway Safety.  In a recently released report, IIHS announce that this intelligent braking outright prevents 25% of low-speed crashes in the vehicles in which it is installed.

It’s better that computers will eventually drive.  Humans just aren’t good at it.  The World Health Organization estimates that around 1.2 million people are killed in car crashes each year with around 45,000 of those deaths taking place in the US.  Almost all of these are due to human error, something that will be eliminated with self-driving cars. 

But how far away are cars that completely drive themselves?  Well, I can’t go out and buy one today.  But check out this TED talk.

Self-driving cars are already here!  Google’s self-driving cars have logged 140,000 miles across cities and highways through both day and night without an accident.  And if you think that Google accomplished this feat by relying on their cars driving meekly and 20 mph less than the speed limit, here’s one of their cars screeching tires and hauling ass through an obstacle course.

Once cars are completely driving themselves, even more opportunities open up.  Scientists in Italy are working on software that allows cars to talk to each other, with the end goal of connecting every single car on the road.  What would this system be used for? 

When a car in an accident experiences a sudden change in acceleration, this change would be captured by the sensor and alert cars and drivers approaching the same spot.

In addition to preventing accidents in the first place, self-driving cars will better react to accidents when they do occur, preventing even more accidents.  This double whammy, I believe, will have an incredibly dramatic effect on the number of deaths and injuries from auto accidents each year.  Once self-driving cars are widespread a 95% reduction of traffic deaths is within the realm of possibility.

One last bit of good news: traffic will also be lessened once self-driving cars are the norm.  Every time I sit in a traffic jam, I dream that self-driving cars are already here.  There aren’t any idiots switching lanes to try to get ahead only to end up slowing everyone down.  There are no rubberneckers braking to stare at the gore of an auto accident.  There is no one suddenly accelerating and then stopping, disrupting the flow of traffic.

Instead, there are thousands of self-driving cars proceeding at a quick and steady clip on the highway.  People now get to their destination much sooner and rush hours have been greatly alleviated, in some places entirely eliminated.  Self-driving cars are following each other closer than would be possible if driven by humans.  No one brakes for no reason.  There is no road rage.  When a two-lane highway merges into one lane, the cars evenly space themselves and merge while barely losing any speed, like a zipper being zipped.  Everything is beautiful.  Nothing hurts.

So how will this paradise come about?  I expect cabs and buses might be the first early adopters, for economic reasons.  Maintaining a mass-produced AI will be cheaper than paying individual drivers.  There would be some differences, sure.  Video surveillance would have to be used to prevent and prosecute hooligans.  But in the end, we’d be much better off with self-driving cars.  And I believe (or at least want to believe) that I will ride in my first self-driving car before 2020.

My Complete Lending Club Strategy

For future reference, I’m going to chronicle my initial Lending Club posts into one article.  Without further ado:

Part 1: a quick introduction to the concept of P2P lending

Part 2: why I decided to use Lending Club over Prosper

Part 3: the final filters that I apply to find the best loans to fund

Part 4, Part 5, Part 6, and Part 7: the primary filters that I apply to weed out borrowers first

I will also continue my monthly updates on my Lending Club return, to see if these filters really work.

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