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liarsandoutliers

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Cybercrime as a Tax on the Internet Economy

I was reading this 2014 McAfee report on the economic impact of cybercrime, and came across this interesting quote on how security is a tax on the Internet economy:

Another way to look at the opportunity cost of cybercrime is to see it as a share of the Internet economy. Studies estimate that the Internet economy annually generates between $2 trillion and $3 trillion,1 a share of the global economy that is expected to grow rapidly. If our estimates are right, cybercrime extracts between 15% and 20% of the value created by the Internet, a heavy tax on the potential for economic growth and job creation and a share of revenue that is significantly larger than any other transnational criminal activity.

Of course you can argue with the numbers, and there’s good reason to believe that the actual costs of cybercrime are much lower. And, of course, those costs are largely indirect costs. It’s not that cybercriminals are getting away with all that value; it’s largely spent on security products and services from companies like McAfee (and my own IBM Security).

In Liars and Outliers I talk about security as a tax on the honest.

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Prisoner's Dilemma Experiment Illustrates Four Basic Phenotypes

If you’ve read my book Liars and Outliers, you know I like the prisoner’s dilemma as a way to think about trust and security. There is an enormous amount of research — both theoretical and experimental — about the dilemma, which is why I found this new research so interesting. Here’s a decent summary:

The question is not just how people play these games­ — there are hundreds of research papers on that­ — but instead whether people fall into behavioral types that explain their behavior across different games. Using standard statistical methods, the researchers identified four such player types: optimists (20 percent), who always go for the highest payoff, hoping the other player will coordinate to achieve that goal; pessimists (30 percent), who act according to the opposite assumption; the envious (21 percent), who try to score more points than their partners; and the trustful (17 percent), who always cooperate. The remaining 12 percent appeared to make their choices completely at random.

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How Altruism Might Have Evolved

I spend a lot of time in my book Liars and Outliers on cooperating versus defecting. Cooperating is good for the group at the expense of the individual. Defecting is good for the individual at the expense of the group. Given that evolution concerns individuals, there has been a lot of controversy over how altruism might have evolved.

Here’s one possible answer: it’s favored by chance:

The key insight is that the total size of population that can be supported depends on the proportion of cooperators: more cooperation means more food for all and a larger population. If, due to chance, there is a random increase in the number of cheats then there is not enough food to go around and total population size will decrease. Conversely, a random decrease in the number of cheats will allow the population to grow to a larger size, disproportionally benefitting the cooperators. In this way, the cooperators are favoured by chance, and are more likely to win in the long term.

Dr George Constable, soon to join the University of Bath from Princeton, uses the analogy of flipping a coin, where heads wins £20 but tails loses £10:

“Although the odds [of] winning or losing are the same, winning is more good than losing is bad. Random fluctuations in cheat numbers are exploited by the cooperators, who benefit more than they lose out.”

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