Friday, April 21, 2017

Airlines, Algorithms, and Accidents | Connecting the Dots Investment Newsletter | Mauldin Economics

Airlines, Algorithms, and Accidents | Connecting the Dots Investment Newsletter | Mauldin Economics



...United Airlines had a rough week, but not as rough as one of its passengers. Dr. David Dao received a concussion, a broken nose, and two broken teeth after airport police forcibly dragged him off the plane he had boarded only a short while earlier.

As you have probably heard by now, the airline needed to get four crew members from Chicago, IL to Louisville, KY for a flight the next day and decided to boot four passengers off the plane after nobody volunteered to give up their seat. In light of the ensuing publicity disaster, it would have been cheaper and better for United to buy four Porsches and let the crew members drive to their destination.
Courts will sort out who owes what to whom—however, I have a different angle....

Complex Machinery

An airline is an incredibly complicated machine with a zillion moving parts: planes, passengers, crew, luggage—and all of it must be in certain places at certain times, or the whole thing will fall apart. It’s remarkable when you think about it.
Modern airlines operate at the scale and speed they do by automating all those little details. Computer algorithms make many of the decisions; people just execute them.
The computer knows the rules, but it’s not perfect. One of those one-in-a-million scenarios will arrive eventually—or worse, several consecutive ones.
I suspect that’s what happened with United.
Several different processes converged. Computers issued instructions and people responded. No one wanted violence, but a series of flawed decisions produced it.
Things like that happen when you don’t build an adequate error margin into a complex system.  Occasionally, conditions will combine to create results no one wants or expects.
Here’s the scary part.
Airlines aren’t the only industry to depend on complex algorithms. So do banks, brokerages, utility companies, hospitals, pharmacies, health insurers, governments, and more.
All these organizations let their algorithms make complex decisions in rapidly changing conditions. They work fine… until they don’t.
Yet we all constantly agree to contracts we don’t understand, then submit ourselves to algorithms that follow them to ludicrous extremes.
See the problem?

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