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pricing information for the products

The final, and perhaps the most interesting, way to understand decision-making in the face of uncertainty is to generalise the meaning of an event to let us handle cases that might cause different behaviour. To understand the value of an umbrella, for example, we could divide days into two classes: rainy days and rain-free days. We can then estimate the value of an umbrella as being its value on a rainy day weighted by the probability of rain plus its value on a rain-free day weighted by the probability that it does not rain. It turns out that we can use this idea to understand why seemingly valuable information often remains relatively unprotected.

Much like the value of an umbrella depends on the chances of rain, the value of information is highly dependent on context. If you pick two random laptop users and have them switch laptops, both will probably end up unhappy with the exchange because data that may be very valuable to one of these users will probably be virtually useless to the other. One user might be a sales executive for a software company whose laptop contains a list of important customer contacts and pricing information for the products that he sells. And although he and his employer may perceive the value of this information as being very high, to the average laptop user this information is useless.

The other laptop user might be a marketing manager at a plumbing fixtures company whose laptop contains information on the future plans of his company to change the composition of the bronze alloy that they use in certain pipes and their plans to outsource the production of these pipes to China. This information is similarly valuable to its owner, but is of little value to most of the world. If these two laptop users manage to switch laptops, they both will find the data that they end up with of essentially no value, even though it was extremely valuable to its original owner.