Category Forecasting

Powers That Must Not Be

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Posted by on June 4, 2015

Death Note is a manga by Tsugumi Obha and Takeshi Obata, which centers around a magical book called a Death Note. This book confers a power: by following its instructions, the possessor of the Death Note can kill anyone by writing down their name, and choose the manner of death. The story centers on Light Yagami, who comes into possession of the Note and uses it to kill criminals.

While the story the Death Note is a supernatural artifact, there are things in real life that are somewhat analogous. Assassins have existed for at least as long as recorded history; in a sense, having a Death Note is like commanding a master assassin. What makes the Note different and scary, however, is its anonymity. Real-world assassination is inherently risky and difficult, and it’s risky and difficult every time. This is good; in a world with too many Death Notes, some would fall into the hands of villains, and be used to terrible effect. One reason the world today is a better, safer place than the world of a thousand years ago is because forensic science has made it virtually impossible to get away with murder.

A straightforward extrapolation of currently-existing technologies suggests that this power does exist, and is possessed by a small number of spymasters and heads of state. This is unfortunate, but it’s no worse than it was in humanity’s past.

But there are analogous powers, similar to the Death Note power but not quite the same, which humanity did not used to have, and which we would prefer it didn’t.

One such power is the power of atomic weapons. Rather than killing individuals, these kill regions. Their existence is a large and obvious threat to everyone, but fortunately, they are hard enough to make that only governments are able to acquire them, and their terribleness is imprecise enough that no government is willing to use them; the ensuing disaster would affect them as well.

There are other powers, which are worse, which technology hasn’t brought into the world yet, but might. Consider what happens in a world where internet-connected drones are common. Drones are dangerous; they can kill people by crashing into them. What happens if they’re hackable?

The combination of bad computer security, face recognition, and hazardous internet-connected devices could create a Reference Class Note: an artifact like Tsugumi’s Death Note which, instead of targeting a person, targets an arbitrary category of people. And the nature of computer software is unfortunately not like the nature of fissile elements; hazardous software can be constructed by skilled individuals.

There are other ways this could happen besides drones, which I will not name. What all of them have in common, though, is that they depend on the continued failure of computer security. In the 90s and early 2000s, cracking computer security was within easy reach for bored teenagers; they used this power for pranks, and were the first canary in the coal mine. Today, the bored teenagers mostly can’t manage it, but skilled individuals can; they use this power for theft, and are the second canary. We need to drive the bar up higher, to the point where defeating computer security is limited to large organized groups. We need to do this soon, before the “Internet of Things” takes hold.

If we can’t? Bam, sci-fi dystopia.

Technological Unemployment

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Posted by on June 3, 2015

Will automation displace workers and eliminate jobs? For many jobs, yes. Whether this will cause unemployment, however, is a controversial and open question. When technology automates away jobs, there are several possibilities for what happens to the people who would otherwise have been in those jobs. The total number of jobs worked might drop, or they might just shift to doing jobs that are hard to automate. If the number of jobs worked does go down, this could lead to people being unemployment and impoverished, or it could instead result in people entering the work force later, retiring earlier, working part time, and taking more long vacations.

Predicting what will happen is hard. Noticing what already happened, however, is more straightforward. Automation is not a new force in the world, and technology-driven unemployment has been a concern at least as far back as the Luddite movement in 1811. With the benefit of hindsight, nineteenth century Luddism was clearly incorrect; there was a massive amount of important work left undone for lack of people to do it. But what about more recent trends? Here from the Bureau of Labor Statistics is the United States unemployment rate, for everyone aged 16+.

Bureau of Labor Statistics Unemployment Rate, 1948-2014

This graph displays a pattern best described as “glaringly absent”. It’s basically noise. Why? It turns out that the definition of unemployment is fairly complicated. Unemployed refers to people who are jobless, available for work, and looking for work; it excludes people who have tried to find work recently but aren’t currently trying (marginally attached workers), people who have given up on finding work (discouraged workers), students not looking for work, and people unable to work because they are ill or disabled. The “discouraged workers” category is particularly unfortunate; it means that the unemployment rate is measuring a sort of residual, the people who can’t find work but haven’t realized it yet. A much more straightforward number is the employment-population ratio. This is simply the number of employed people divided by the population. So here, also from the Bureau of Labor Statistics, is the United States Employment-Population Ratio, for the civilian noninstutitional population, age 16+. (Excludes people on active duty in the armed services and prisons, nursing homes, and mental hospitals.)

Bureau of Labor Statistics graph of employment-population ratio, 16+, 1948-2014

This graph gyrates a little less wildly. If you squint hard enough, you might fool yourself into seeing a pattern. It turns out there is one more confounder to separate out.

Paul Samuelson famously criticized GDP by observing that, if a man married his maid, GDP would fall. In fact, it’s not just GDP that would fall; employment would fall, too. Employment only counts work that is done for wages; there is a separate category, “household activities”, for the rest. This includes things like cooking, laundry and child care. Unfortunately, this time the BLS doesn’t have a nice graph to give us, but we can get a few point estimates. The American Time Use Survey estimates that household take an average of 9.5 hours per week for men, 15.5 hours per week for women. By contrast, Valerie Ramie in the Journal of Economic History reviews twelve estimates from 1924-1953 and finds that in that time period, homemakers spent 47-63 hours per week on household production – a time expenditure comparable to or greater than that of full-time employment. This household labor fell primarily on women, and has now been substantially reduced by inventions such as laundry machines, microwaves, and robotic vacuum cleaners, as well as by declining fertility. This combined with changing social norms caused many more women to enter the labor force, as shown by the employment-population ratio for women:

Bureau of Labor Statistics graph of employment-population ratio for women 16+, 1948-2014

Here we see womens’ employment increases until some time around 1990-2000, then either stops changing or starts falling. This comes partially at the expense of mens’ employment, but I think it’s mostly at the expense of household activities. Meanwhile, the employment-population ratio for men looks like this:

Bureau of Labor Statistics graph of employment-population ratio for men 16+, 1948-2014

This is a steady decline of about 2.7% per decade. To see whether this trend extends past the time range covered by the BLS time series, I also checked the 1910 census and found that the employment-population ratio (male 16+) was 91% (Final Report Vol. 4 Ch. 1 Pg 69).

Based on this data, I expect both the US male and female employment-population ratios to decline at about this rate in the future. This will manifest as a mix of people entering the work force later, retiring earlier, working less, being declared legally disabled at a lower threshold, and sharing income within families. Depending on policy and social norms, we could have more leisure for everyone, or more poverty, or some mix of the two. It’s up to us to choose wisely.