Have you ever noticed how anyone going slower than you is a moron and anyone faster than you is a maniac? You of course, are always travelling at exactly the right speed.
What about that last time you messed up at work? Remember that?
Of course that wasn't entirely your fault, in fact it was due to the incompetence of others. That bloody Jane in accounts didn't give you that report on time, and your day was messed up early because of that train delay. Plus of course you had that stinking head cold.
Then there was the time that the new kid messed up, complete incompetence! His task was so simple a bloody five year old child could have completed it in half the time and with much more skill and competence than John managed.
Wait a minute, I'm beginning to see a pattern here; how about you?
Asymmetric Standards
The pattern that we are starting to uncover is one of asymmetry. That is to say it is not a balanced arrangement. To look into this further, think about the last time you did something really good, that you yourself consider noteworthy.
Perhaps you got a promotion at work, or maybe you invested in a crypto that later went through the roof. Or perhaps you won a competition. Whatever the winning situation, we can safely assume that the positive outcome occurred because of your actions. Right?
Now let's take a look at the last time something bad happened to you. Maybe you lost a job or your boss shouted at you. Perhaps a crypto crashed through the floor just after you bought it, or someone you met romantically stopped calling you. Well it was clear at the time, and still is, that external circumstances caused those bad things to happen and they were things that were quite frankly, beyond your control.
A Biased History
What we have been looking at here is the actor-observer bias, sometimes called actor-observer asymmetry. This is a cognitive bias that was discovered by psychologists Edward Jones and Richard Nisbett in 1971.
Jones & Nisbett did various studies on college students to find out if people held themselves to different standards to others that they did not know well.
In 2006 another psychologist Bertram Malle performed a meta analysis of Jones & Nisbett's initial experiments along with over one hundred other studies on the matter.
Malle discovered that the initial findings weren't quite as accurate as people at first thought. However he did find that there was indeed an interesting asymmetry. His findings have since been backed up by nine more empirical studies.
Observing The Actors Of Hardfork 20
Recently we had what is known as a hardfork on the Steem blockchain. That is a situation whereby the code that allows the chain to function, is changed at a fundamental level. The reasons for doing such a thing was to allow the framework for a new user experience on the Steem platform.
Thousands of lines of code were written, observed, and tested for over a year before finally being implemented on the 25th of September, 2018.
However it did not go smoothly, the change happened and a large number (some say 99%) of accounts were effectively frozen. This was because we moved from the old Steem Power/bandwidth system, to a new Resource Credits/Mana system.
Afterwards few people could post, vote or transfer funds, which obviously led to plenty of wailing and gnashing of teeth.
I myself did plenty of wailing and gnashing, using words such as unacceptable and making lots of assumptive phrases such as; they obviously didn't test this . . . and why didn't they do this another way?
Then I stopped and started to listen to the chatter that was flying around the various Discord channels and Steemit Chat.
That was when it became clear that there was not very much forgiving language being offered towards the Steemit developing team. Almost everyone automatically assumed that the reason HF20 had gone wrong was because they hadn't tested it properly beforehand. Along with that plenty of people were throwing around terms such as incompetent.
Very few people allowed for the fact that code is very complex. Also for the fact that there is no way of knowing if your code will work in a live environment until, well, until you deploy it in a live environment.
No matter how much testing you do, there will always be situations whereby things spring up that you did not test for. We call these things; unforeseen circumstances.
Those very same circumstances are what you would have brought up had you been working on the dev team. However because you were not, the actor-observer bias causes you to blame the people involved rather than external events.
Walk 5 Seconds In Their Shoes
Seeing things from other people's point of view is hard for the simple reason, that you are not other people, you are you!
It gets slightly easier when it is a family member or friend. Oh Jane's husband left her because he is a cheating bastard! Or, Tom lost his job because his boss is an ass.
However for strangers it is much harder, why? Well it is mainly because we are shielded from the potential reason for failure by the mere fact that we are not involved in the process. All we are affected by is the outcome.
If a car speeds by you almost knocking you down, you don't immediately think; 'Wow, I hope that guy is ok, maybe he is driving like that because he is rushing to the hospital to see a sick relative!
No, you think, what an arsehole! Slow down you maniac!
Sometimes if we just pause to consider what the other person's motivations might be, even if it is just for 5 short seconds. We can possibly avoid being caught up in the actor-observer asymmetry.
For instance with Steem and HF20 you might not be happy about the outcome, but at least ponder for a few seconds that neither are they. The devs weren't trying to deliberately sabotage you. They take as much pride in their work as you do. Plus of course, they had it fixed pretty quickly after launch, within 24 hours most people's accounts had returned to normal.
Just remember, mistakes happen to everyone, and just like your own errors, other people's also sometimes happen for reasons beyond their control.
Sources
Actor–observer asymmetry - Wiki
The Actor–Observer Asymmetry in Attribution: A (Surprising) Meta Analysis - Bertram F. Malle - .pdf
A Brilliant Explanation of the Actor-observer Bias in Psychology - psychologenie
WHAT SITUATIONS ARE YOU MOST SUSCEPTIBLE TO THE ACTOR-OBSERVER BIAS? ARE YOU QUICK TO JUMP TO CONCLUSION WHERE OTHERS ARE INVOLVED? OR PERHAPS YOU ARE ALWAYS MEASURED AND SEEING THINGS FROM OTHER'S POINT OF VIEW?
AS EVER, LET ME KNOW BELOW!
Title image: Ryan Christodoulou on Unsplash