So once again I’ve taken myself off Twitter and Facebook. After a three-month sabbatical which ended a month back, I was back on these two social networks in a “limited basis” – I had not installed the apps on my phone and would use them exclusively from my computer. But as days went by, I realised I was getting addicted once again, and losing plenty of time just checking if someone had replied to any of the wisecracks I had put on some of those. So I’ve taken myself off once again, this time for at least one month.
This post is about the last of my wisecracks on facebook before I left it. A facebook friend had put an update that said “good things do happen to those who wait”. I was in a particularly snarky mood, and decided to call out the fallacy and left the comment below.
In hindsight I’m not sure if it was a great decision – perhaps something good had happened to the poor guy after a really long time, and he had decided to celebrate it by means of putting this cryptic message. And I, in my finite wisdom, had decided to prick his balloon by spouting gyaan. Just before I logged out of facebook this morning, though, I checked and found that he had liked my comment, though I don’t know what to make of it.
Earlier this year I had met an old friend for dinner, and as we finished and were walking back to the mall parking lot, he asked for my views on religion. I took a while to answer, for I hadn’t given thought to the topic for a while. And then it hit me, and I told him, “once I started appreciating that correlation doesn’t imply causation, it’s very hard for me to believe in religion”. Thinking about it now, a lot of other common practices, which go beyond religion, are tied to mistaking correlation for causation.
Take, for example, the subject of the post. “Good things happen to those who wait”, they say. It is basically intended as encouragement for people who don’t succeed in the first few attempts. What it doesn’t take care of it that the failures in the first few attempts might be “random”, or that even success when it does happen is the result of a random process.
Say, for example, you are trying to get a head upon the toss of a coin. You expect half a chance of a head the first time. It disappoints. You assume the second time the chances should be better, since it didn’t work out the first time (you don’t realise the events are independent), and are disappointed again. A few more tails and disappointment turns to disillusionment, and you start wondering if the coin is fair at all. Finally, when you get a head, you think it is divine retribution for having waited, and say that “good things happen to those who wait”.
In your happiness that you finally got a head, what you assume is that repeated failure on the first few counts actually push up your chance of getting your head, and that led to your success on the Nth attempt. What you fail to take into account is that there was an equal chance (assuming a fair coin) of getting a tail on the Nth attempt also (which you would have brushed off, since you were used to it).
In my comment above I’ve said “selection bias” but I’m not sure if that’s the right terminology – essentially when things go the way you want them to, you take notice and ascribe credit, but when things don’t go the way you want you don’t notice.
How many times have you heard people going through a happy experience saying they’re going through it “by God’s grace?”. How many times have you heard people curse God for not listening to their prayers when they’re going through a bad patch? Hardly? Instead, how many times have you heard people tell you that God is “testing them” when they’re going through a bad patch?
It’s the same concept of letting your priors (you see God as a good guy who will never harm you) affect the way you see a certain event. So in my friend’s case above, after a few “tails” he had convinced himself that “good things do happen to those who wait” and was waiting for a few more coin tosses until he finally sprang a head and announced it to the world!
Now I remember: I think it’s called confirmation bias.