A new form of decision analysis is helping executive reevaluate risk
management. In a nice PDF, Tim Laseter and Matthias Hild wrote a good introduction on what might be a post-bayesian statistics applied to business decision making.
Despite the mathematical proof defending the logic of expected value, in
real world, we, human, aren’t much rational when it comes to making
decision. We all know (do we?) current right wing ideology pretend that
the market is made of rational users. If this was true how can we
explain why we are so poor at picking the rational decision.
Let’s face it. If in a coin toss, I offer you $100,000 on heads but
you’ll pay me $50,000 on tails, few of you will rush to take the wager.
Although the expected value of this bet is a positive one, i.e. ((50% x
$100,000) minus (50% x $50,000)) yield effectively $25,000. At least a
logical machine would bet right away. For us, mere mortals, the
potential downside – loosing $50,000 – is simply too great.
That is because we do use our instinct : « how much can I lose? » « What’s
the likelihood of a bad resulting occuring? ». Logic isn’t in the radar.
What I like of Plausibility Theory is that it recognizes that we people
choose knowable over unknowable risk rather than a simple examination of
(logical) expected value.
This explains why we do weight more risk over expected value. And
sometime backing up when something new is coming. Open Source Software
evangelists should take note.
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