Life isn't about getting predictions "right"; it is about knowing how to navigate the environment and controlling it.How?

 False causality

Consider the following surprising headline:” The employee motivation leads to higher corporate profits.” What about maybe people are only motivated because the company is doing well or what about highly motivated workers working in business doing poorly?

     Another one. What about female advertising cosmetic and thus many female consumers believe firmly that these products make you beautiful. Well what about those who do not use cosmetic and crown beauty queens? All what I am saying is – it is not these products that make you beautiful. Quite, simple models are born attractive and only for this reason – they are candidate fo         r cosmetic advertising. Hence beauty is a factor for selection and not result. This is a second example of false causality.

  By the way without this illusion, half of advertising campaigns would not work

  Among many traits that multimillionaires have in common such great appetite to risk, they work hard. Well take look at the cemetery of bankruptcy – you will realise that the bankrupt people share certain extend the same attributes-namely they have great appetite to risk and they work hard. This in nutshell another example of false causality.

  Finally, when I ask people about the secret of their happiness, I often hear this surprising answer. “You have to see the glass half full rather half empty”. See the glass half full I ask myself

Ask my viewers to watch the cemetery episode, the confirmation bias

   The kernel point of my thoughts is we have to be careful on things we can make inference and things on which we can’t. We tend to make the mistake of overestimating our ability to find cause and effect -which has the direct consequence that cognitively we like to have causes which give us the illusion of understanding the world. By way the today, we simultaneously inhabit two – systems- namely the predictable which is linear and the unpredictable which is nonlinear if you want complex. The problem lies in the fact of conflate one environment for another. If you haven’t listen the episode about, If someone tries to trick you with "Evidence-based analysis", show him this story of the turkey

Are You Victim of the Bed of Procrustes as Your Bedrock, Via Negativa, f someone tries to trick you with "Evidence-based analysis", show him this story of the turkey

Here are the 3 big ideas from to retain from this episode.

 --First and foremost, always do counterfactual which allows you not to fall victim of the confirmation bias and even debunk it

--Second always simulate, not to see what will happen- but what may happen

--Finally switch from predictive methods to non-predictive methods, stop trying to understand the world and focus on robustness by avoiding fragility