Book Notes: Thinking in Bets

Thinking in Bets: Making Smarter Decisions When You Don’t Have All the Facts by Annie Duke
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People tend to equate the quality of a decision with the quality of the result. However in the real world it is not possible to make perfect decisions because some of the information is hidden – as such real world decisions are more like games of poker rather than chess.

As such we are very bad at separating luck and skill as bad decisions can still produce good outcomes. In poker the feedback loop is short, in the real world this is much longer making the evaluation of decisions even harder.

We suffer from Hindsight bias – believing we could have predicted something at the time. Alternative we attribute all of our successes to our skill and all our failures to bad luck – in reality neither are fully the case. There is a lot of space between being unequivocally “right” or “wrong” which we tend to vastly simplify. Offloading the losses to luck and onboarding the wins to skill means we persist our approach without learning. This is because our Ego need for a positive self image and losing feels twice as bad as winning.

How our beliefs are formed:

  1. We hear something we believe is plausible
  2. We then believe it as a true
  3. Sometimes at some point later, if we have the time and inclination, we think about it and vet it to determine whether it is, in fact, true or false

Instead of altering our beliefs to fit new information, we do the opposite, altering our interpretation of that information to fit our beliefs. This prevents us from learning.

There is a big difference between clocking up experience experience and becoming an expert.

In reviewing decisions the result does not matter as this is influenced by luck which is out of your control.

How can we overcome our deficiencies?

Putting a percentage on our statements – this helps us realise that things are not fully true or false and in calculating the percentage we evaluate our beliefs.

Instead of fixating on an outcome, think of a set of future outcomes.

Better evaluate decisions

  • Communism – data belonging to the group, data which we have an urge to leave out is exactly the data we must share
  • Universalism – universal standard no matter the source of data
  • Disinterestedness – vigilance against things which could influence a groups decision
  • Organised Skepticism – discussions to encourage engagement and dissent

Building a decision support group

Visualising our future self or how will I feel about the choice in 10 min, 10 months, 10 years

Run premortems to evaluate both sides of the problem

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