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3.72 AVERAGE
3.72 AVERAGE
Made me remember why I studied math instead of philosophy.
Eclectic. Rich. Fun. Non technical-friendly. Nassim is a proper BS detector and is also a diva and we’re all here for it.
My quick takeaway is that people are terrible at risk assessment and predicting, including the "experts". That doesn't sound so crazy but there's no way you can read Taleb without changing your perspective on the way the world works and how people interpret what's going on.
Love the theory and concepts, but didn't care for the writing.
challenging
informative
reflective
slow-paced
I really didn't like the fact he's so full of himself in the book. He ignores other's opinion out right and sure maybe they're partially wrong, but the author speaks as if he's completely right and other's are absolutely wrong.
I almost gave up at least four times. This book makes good points, but the meandering prose, mixed with the author’s (mostly) unfounded disdain for several disciplines and the Nobel prize, while not missing a single opportunity to remind the reader how amazing and smart he is made this feel like a diary written as a stream of consciousness.
Take the same points, condense them down without the self aggrandizement and the snark and you have a great 100-page book!
Take the same points, condense them down without the self aggrandizement and the snark and you have a great 100-page book!
Challenged my thoughts with a pinch of humour + realism.
Black Swan event;
• an outlier/rarity
• extreme impact
• retrospective
Black Swan logic: what you do not know is far more relevant than what you do know.
Key points from Black Swan:
• The normal bell-curve distribution predict approximation of results that does not necesserily accounts for Black Swan outliers —shift the distribution significantly. Contributed by pure chance and the tendency for obvious outliers which leads to significant impact due to specific circumstances.
* Gaussian bell curve —few data sets can be effectively analysed using the normal bell distribution in reality.
• Platonifying: The human mind tends to create an illusion of understanding things that are too complex for it to grasp, making chaotic events seem orderly and predictable in retrospect, and overvaluing neat classifications.
• Complex systems are viewed as random due to the lack of available or comprehensible information —predictability is relative to knowledge.
• Predictive models are distorted as a result of generating simplified narratives of the causes of Black Swans and demonstrating their probability after the fact prevents people from taking into account the many complex factors that actually caused the event caused the event, which then distorts predictive models.
• Bad predictions are mostly rooted in extrapolating from the past, which does not always take into account actual, current threats faced.
• Almost evryone of us, especially experts in rapidly changing fields, have tendency to be overconfident in their knowledge —additional information of a topic leads to blind confidence in uninformed determination and unwillingness to revise conclusions and predictions.
Strategy for withstanding Black Swan:
• Be true to ourselves especially on our ignorance/things we do not know
• consider decisions based on available information instead of long-term assumptions
• contemplate on possible risk and adopt methods to minimise risk
I have a lot of comments on it as well but honestly a good read
I'd read this once before a while back and decided to read it again. It is a thought provoking book and Taleb spares no punches for government officials, bankers, economist and statisticians. It comes across that he is anti prediction and anti building any sort of models but that is not the case. What he is against is having an overconfidence because you have a model and blindly applying a model for prediction that doesn't work. I guess as a statistician, I could be offended and dismiss the book as a bunch of rubbish, but there is some truth in what he says and I'm not a particular strong fan of models. I am a big fan of the data and making good decisions based on the data, which doesn't necessarily require one to build a model, particularly where there is a lot of data. Fun book to read, quite different than most that you will read.
challenging
funny
informative
lighthearted
reflective
medium-paced
In summary, we can say that Taleb teaches us areas of prediction that we did not have foreseen, the data that remains outside the percentages are the most problematic, since we believe that by seeing 97% in a graph, we will automatically be there, why? Why don't we think about what would happen if we were in the remaining 3%? Isn't enough to avoid the problems that come from quantifying in our favor, from searching our minds for the narrative that fits our future with a fictitious convenience, because then we are not different from Catholics, trusting blindly in God or numbers , Aronofsky presents a similar thesis in his first feature Pi¸ Are the numbers of God really different? The logic of faith? Eventually the two come out of the mind following their own logic.
I repeat once again based on Taleb's learning, it is useless in the graphics to come, having read one more book, because it will open a quantitative area that will spread branches of new knowledge that we will not know, it will always be as Mark Twain suggests, more dangerous what we don't know.
I repeat once again based on Taleb's learning, it is useless in the graphics to come, having read one more book, because it will open a quantitative area that will spread branches of new knowledge that we will not know, it will always be as Mark Twain suggests, more dangerous what we don't know.