Licence to be Bad summary

You’ve probably heard of game theory. This is the famous way of thinking that predicts people’s behavior based on rational decision-making. Game theory rose to prominence in the post-war years, when mathematician John von Neumann used it to advise the US government to bomb the Soviet Union as soon as they could. Thankfully, President Eisenhower disagreed.

Fellow American John Nash pushed game theory further by emphasizing the role of self-interest. Nash believed that people always acted selfishly. If people looked like they were cooperating, it was only because it suited their own interests at that moment.

How should governments reduce unemployment? Here’s one idea – bribe employers.

This actually happened in Illinois in 1983. Almost 4,000 unemployed people were invited to take part in an experiment, where if they found and kept a job, their employer could claim a $500 reward.

“Democracy is impossible.” Catchy one, right? This slogan gained huge popularity thanks to the work of economist Ken Arrow. But it’s debatable at best.

Arrow’s Impossibility Theorem is a mathematical proof that shows that, under a strict set of conditions, no system of collective decision-making can produce a result that’s consistent with what everybody collectively wants. That would mean, for example, that it’s impossible to elect anyone in a truly democratic way.

Here’s a scenario. Two criminals are pointing their guns at someone, intending to fire. But only one of them actually does. Who is the murderer? The one who fires, right?

Had that criminal not fired, the other criminal would have done so instead. But that doesn’t make the killer less guilty, and every legal system would agree that the criminal who fired the gun is the murderer. Speaking more generally, individual responsibility isn’t lessened, just because other people might do the same thing.

You wouldn’t call most of the examples we’ve seen so far traditional economics. Issues like voting and the climate catastrophe, after all, aren’t quite the same as graphs of supply and demand.

But since the 1980s, there’s been a movement toward understanding the world more broadly in economic terms. The ultimate aim is to be making decisions based on efficient, economically optimal thinking.

In the 1990s, several day care centers in Haifa, Israel, had a problem with parents arriving late to collect their children. So they started issuing fines. And the number of late collections rose.

Here’s a different example. In 2011, the UK government wanted to discourage people from using single-use plastic bags, so they started making people pay for each bag – effectively, a small fine. Usage fell by 80 percent.

August 2007 was a hair-raising time for David Viniar, then CFO of Goldman Sachs. In a Financial Times interview, he describes events in the market as “25-standard deviation moves,” happening “several days in a row.”

A 25-standard deviation move is like winning the British lottery 21 times in a row – we’re talking less than once in the history of the universe. Yet during the crash, these events were happening not just once, but over and over. That leaves two possibilities. Either we all just got really, really unlucky, or the statistical modeling was badly wrong.

It’s well known that there’s a high level of inequality in the world today. But intriguingly, there’s just as much inequality among the rich as there is overall.

Inequality follows a fractal distribution – just like the stock market and snowflakes in the previous blink. So it’s also scale-invariant. Say you look at a whole nation’s income and see that the richest 1 percent gain around 20 percent of all the income. Scale-invariance means that if you zoom in, you’ll see that within the richest 1 percent, the top 1 percent receive 20 percent of all that income.