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TFS: Why you should think like a loser

Often, prejudicial thinking falls under the "Sin of Representativeness." We estimate the probability of success based on whether someone looks like a winner. How can you avoid prejudicial hiring? We are naturally drawn to likeable candidates that fit our expectations.Tq130520tl

Daniel Kahneman: Thinking, Fast and Slow:

You surely understand in principle that worthless information should not be treated differently from a complete lack of information, but WYSIATI [the biased belief that you see is all there is] makes it very difficult to apply that principle. Unless you decide immedidately to reject evidence for example, by determining that you recieved it from a liar), your System 1 will automatically process the information available as if it were true. There is one thing you can do when you have doubts about the quality of the evidence: let your judgments of probability stay close to the base rate.* Don't expect this exercise of discipline to be easy--it requires a significant effort of monitoring and self control.

The more confident you feel that you've found a winner, the more you should check that feeling and imagine that you've picked a loser. Don't indulge your confimation bias. Get your analytical System 2 to kick in by forcing yourself to thinking about the humiliation of losing. Pick up a resume you rejected and visualize the possibility that you're overlooking someone who will become a big success for your competition. 

*Wikipedia on "base rate":

In science, particularly medicine, the base rate is critical for comparison. It may at first seem impressive that 1000 people beat their winter cold while using 'Treatment X', until we look at the entire 'Treatment X' population and find that the base rate of success is actually only 1/100 (i.e. 100 000 people tried the treatment, but the other 99 000 people never really beat their winter cold). The treatment's effectiveness is clearer when such base rate information (i.e. "1000 people... out of how many?") is available. Note that controls may likewise offer further information for comparison; maybe the control groups, who were using no treatment at all, had their own base rate success of 5/100. Controls thus indicate that 'Treatment X' actually makes things worse, despite that initial proud claim about 1000 people.

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