Humble Pi: When Math Goes Wrong in the Real World

Humble Pi is a fun book about math gone bad. Or perhaps smore accurately, it is about humans' poor understanding of numbers. There are big disasters and little flubs described. Bridges collapsed because minor changes greatly increased loads. McDonald's went to court because they seemingly exaggerated the number of meal combinations. Other companies understated the number of combinations. People have been given lethal doses of medications due to misunderstandings of the unit of measurements. The Gimli Glider was a 767 airplane that ran out of fuel midflight. Luckily, the pilot was able to glide it down to a landing. A number of things together created the issue. However, a key issue was the use of wrong units for fuel calculations.

People can sometimes have very bad logic when confronted with big numbers. One meme mistakenly assumed dividing a large number in the millions by another in the millions would have an answer in the millions. There have been internet flame wars over whether a week has 7 or 8 days. (Having something 0-based or 1-based does make a big difference.) 

The intersection of computers and people also create all sorts of problems. In one hilarious case, the upgrade of a an operating system (and downgrade of mail software) resulted in emails only being able to reach recipients within 500 miles. (Thank you speed of light!) Strange results often appear due to the binary representation of numbers. Results that exceed the maximum capacity can be very unpredictable. (When the 8-bit level number in pac-man rolled over, things went bezerk.) However, a similar overrun has also lead to a rocket to crash. (Legacy code also contributed to this. The part that caused the self-destruct did not even need to be run at the time.)

People's inability to behave like "math" can also help finding frauds. A professor can distinguish between those that really did record a large number of coin flips and those that made things up. Those that really did it are more likely to have some longer "runs" than a faker would appear. Forensic accounting can also be used to identify fraud due to bad distributions of numbers, indicating more likely "fakes".

What do we learn from all this? People can make bad mistakes with numbers. However, there are also many cases of bad number usage that we are still living with. There are also plenty of others that have been identified by the perpetrators, but have been "swept under the rug" as trade secrets.