Tuesday, March 3, 2015

Book Review - The Reputation Economy

A BloggingForBooks post.

The Reputation Economy, by Michael Fertik and David Thompson

In a few words, the book discusses how large scale data analysis will be able to correlate everything about you online, seriously impacting what jobs, dates and perks you get in real life. If you are a loyal customer, you may get attractive offers to switch but none once you are already a client. However, a disloyal customer will be identified as such and will either consistently get good offers (to hold him) or the company will just let him go to whoever wants to woo this hard client. The same thing will happen in all spheres of life, from finance (credit offers and interest) to dating websites. Everyone will be looking at huge data banks and specific scores (dependability, social, financial and whatever metric a company decides to create in order to identify the best clients for their strategy) so that the individual will not even be able to tell why they are treated the way they are.

Overall, I enjoyed the book more than I expected. I found the descriptions of how this kind of data analysis actually works fascinating and I developed a deeper understanding of how scoring works. However, I think the authors severely overstate their case. They rely on how one single action might have huge impact on your score, which could radically change your interest rate or job offer. That overlooks the fact that it isn't in the lender's best interest to radically change interest rates at the drop of a pin (the client won't be happy and that will affect the lender's reputation right back, since this works both way).

Also, it is important to remember that no one is perfect, no matter how perfect their "life curation" is. If we know everything about everyone, we will have to come to terms with the fact that everyone rants sometimes, everyone farts, everyone does somethings they shouldn't. It is already possible to see this: things that would be absolutely shocking 30 years ago (when it was much easier to keep some things quiet) are now more of a "they shouldn't have done it." My own prediction is that it will soon be easy to identify (using the same methods and processing power the authors describe) over curated profiles, which will raise the "what are they hiding?" flag. Anyone who has conducted a job interview has seen the too slick, too good candidate which sets off the hinky meter, even if we can't place our finger on the problem.

It is pretty obvious why the authors take such a radical stance on this: Fetik is the CEO of a company that does online reputation management - each reader that gets shocked into fear is a potential client. So I decided to take the worst case scenario with a grain of salt.

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