Me Right, You Wrong!

I do health research, and I spend a lot of time thinking about conditions like infallibilitis. It's an adult-onset (or at least teen-onset) disease where a person can't admit they're wrong. I'm working on a study where a couple of survey items just didn't appear on a web-based survey altogether. Obvious and weirdly understandable botch (you've hopefully made it to my website, so I can let you in on the dirty secret that it took a buckload of time to make sure the site presents nicely on different browsers and handheld devices). The vendor refuses to admit that they screwed up, though, and more heinously, didn't do anything about the problem when it was first identified. The issue has probably reduced my quality of life, although it is hard to demonstrate that empirically because the QOL items are the ones that got omitted from the survey.

I first noticed how common infallibilitis (henceforth, "IF") is during my first job out of college at a company called MBI. I would inherit spreadsheets where numbers were hardcoded into cells that should have auto-calculated, and it wasn't hard to realize that the explanation for doing that of "well, there were some shipping delays that cause blah blah blah" was IF-speak for "I don't know, but it made everything balance out." It wasn't long before I started seeing it everywhere, from budgeting errors to payment problems, and it started to feel like a game where you'd subtly try to get someone with IF to tell you the truth. I spent a good two years trying to get some programmers to admit that the "months of coding work" they did to change the frequency of some shipments was actually nothing more than writing a few dates on a calendar (note: I never did get them to admit anything).

Doctors often suffer from IF.

Academia has been way more frustrating on this front, mainly because IF is more common and the problems are harder to fix. In business, screw-ups equal lost money, so whatever problem the IF guy causes gets fixed, often by someone further up the food chain. In academia, though, the consequences are more intangible; and the loss of prestige from admitting a mistake is hard to balance against the (ethical?) obligation to do the highest-quality work. I have never seen an important research-related problem go unresolved, but it almost always feels like pulling teeth to reach a resolution. I once spent a week trying to convince someone that 3179/5915 = 54%, not 47%. I'm glad I finally won that debate.

I've reached the conclusion that the only solution to IF is to ascend the food chain and yell at people. The original survey problem I discussed above was identified a year ago by someone who recently received her BA, which explains why the programmers essentially ignored her complaint. Sadly, her boss (who is very, very respected) barely got better treatment from the programmers; so my suggested solution one is an imperfect one, at best. As I close this post, I'll list what I've observed as risk factors for IF, and I invite you to add more.

• Increased education
• Male gender
• Computer programming training
• Desire to be President of US