What color is this car?

No, it’s not a trick question. Go ahead and yell it. The car is maroon.

This help us grasp the concept of cognitive bias? Well, cognitive bias is a systematic error in thinking that affects the decisions and judgments that people make. Consider the quote from David McRaney,

“If you notice more about shark attacks on the news, you start to believe sharks are out of control and they are becoming dangerous when the only thing you know is the news is delivering more stories about sharks than normal. you think, ‘Damn, sharks are out of control.’ What you should think is ‘Damn, the news loves to cover shark attacks.”

It’s how our minds work, our brain makes assumption very well in small scale. Actually, when our world is small enough that news we hear from surrounding start or tend to represent the environment. If we hear more about that one swimming spot is being attacked by the shark, then we will never go for swimming there but If we take the wider context of beaches along the oceans then the risk of the shark attack will dramatically decrease after noticing the increase of shark attack and this assumption lead to an incorrect conclusion.

So, what’s the role of the picture of a car here? Considering the limited information given in the picture, the most accurate answer will be maroon or red by looking the side picture of the car. however, our brains processed this limited information to construct the bigger picture that color of the entire car is maroon. There is nothing wrong in making this decision. The chance of the car being maroon is very high but one cannot guarantee it. The noticeable thing is that we make this decision automatically until someone point it out, the fact that we are heavily inclined toward an answer that could be wrong is the bias.

This is the best part, we will still think that entire car is maroon despite understanding the assumption and seeing the bias, we may get the idea of the second half as blue or black but then also we will place a bet for maroon. My intention is not to warn you about “color” bias. The point is to provide an order for understanding how heuristics work and why they lead to biases.