The Payoff For Language Learning.

An Economist piece had the following to say about the ROI for learning a foreign language:

“First, instead of $30,000, assume a university graduate, who in America is likelier to use a foreign language than someone without university. The average starting salary is almost $45,000. Imagine that our graduate saves her “language bonus”. Compound interest is the most powerful force in the universe (a statement dubiously attributed to Einstein, but nonetheless worth committing to memory). Assuming just a 1% real salary increase per year and a 2% average real return over 40 years, a 2% language bonus turns into an extra $67,000 (at 2014 value) in your retirement account. Not bad for a few years of “où est la plume de ma tante?

Second, Albert Saiz, the MIT economist who calculated the 2% premium, found quite different premiums for different languages: just 1.5% for Spanish, 2.3% for French and 3.8% for German. This translates into big differences in the language account: your Spanish is worth $51,000, but French, $77,000, and German, $128,000. Humans are famously bad at weighting the future against the present, but if you dangled even a post-dated $128,000 cheque in front of the average 14-year-old, Goethe and Schiller would be hotter than Facebook”

As an aspiring polyglot with a passion for language learning, this is great news! I’ve got some groundwork laid in French, Spanish, German, and my Korean is pretty good, which I imagine will only become more valuable as time goes on.

It’d also be interesting to see the effects on earning potential of people who know languages which the modern economy has juxtaposed. For example, how competitive would a native English speaker be if they knew French and Mandarin to fluency? China has been investing heavily in Africa (I don’t know how much of it is in French-speaking countries, but it’s a reasonably safe assumption that some of it is), and a person could probably leverage those language skills for some pretty lucrative work with, say, hedge funds or multinationals doing work in that part of the world.

Peripatesis: Superintelligent Strategic Advantages, The Aftermath of Cannae, ‘Utility’ In Game Theory.

‘Peripatesis’ is a made-up word related to the word ‘peripatetic’, which is an adjective that means ‘roaming’ or ‘meandering’. I’ve always liked to think of knowledge as a huge structure through which a person could walk, sprint, dive, climb, or fly in as straightforward or peripatetic a fashion as they like.

Here’s are my recent wanderings and wonderings:

Bostrom, N., Superintelligence, p. 78-104

I made it through two chapters this week, in which Bostrom addressed the questions of what sort of strategic advantage superintelligence-development projects could expect to have and how this would impact the future.

The question of strategic advantage is closely related to the question of take-off speed, because if we can expect a fast takeoff then it’s likely that the first project which creates an AI capable of recursive self-improvement will also give rise to the first superintelligence. If, on the other hand, the takeoff is slow then there might be many different AIs improving themselves on the path to superintelligence.

As Bostrom believes that a takeoff will probably be fast, he also believes that first superintelligence will probably be the only superintelligence. Any such agent will be capable of utilizing various superpowers, or abilities far beyond those possessed by competing agents, to disproportionately affect the future.

Using conservative estimates for the computational ability required to simulate human minds and how much of the available matter in the universe can be converted to computational substrate, Bostrom makes the case that the future is a truly vast place inhabited by a near-uncountable number of minds.

Given this, a strong argument can be made that the development of the first superintelligence is the most important project a group of humans will ever undertake.

Goldsworthy, A., The Fall of Carthage, p. 214-221

Following his astonishing victory in the battle of Cannae, Hannibal faced the question of whether to march on Rome or to spend some time resting his troops and planning his next move.

Hannibal chose the latter, giving rise to one of the great ‘what-if’s’ of world history. It is far from clear that Rome would’ve been able to repel a full assault on the city itself, and equally unclear that Hannibal could’ve taken Rome.

In any case Rome ignored the delegation Hannibal sent to negotiate, choosing instead to begin the process of rebuilding their army.

For his part, Hannibal gained many new allies in Southern Italy, and with them a means of drawing supplies to feed his army, meaning he no longer needed to constantly be on the move.

From this point on it was to be a markedly different war between these two titanic enemies.

Luce, R., Raiffa, H., Games and Decisions, p. 12-38

As the concept of utility is essential in gaining an understanding of game theory, the entirety of Chapter 2 is devoted to it.

The following conceptual distinctions are made: an individual can be thought of as any entity or entities with a unitary goal, and a group is one comprised of members with competing goals. Decisions can be made under conditions of certainty, risk, or uncertainty.

A situation is certain when each action leads invariably to a known outcome, risky when each action leads to a set of possible outcomes which have known probabilities, and uncertain when it isn’t clear what the outcome of an action will be.

The authors then turn to analyzing decision making under certainty and under risk before laying out a number of axioms central to game theory.

Peripatesis: Intelligence Explosion Dynamics, The Battle Of Cannae.

‘Peripatesis’ is a made-up word related to the word ‘peripatetic’, which is an adjective that means ‘roaming’ or ‘meandering’. I’ve always liked to think of knowledge as a huge structure through which a person could walk, sprint, dive, climb, or fly in as straightforward or peripatetic a fashion as they like.

Here’s are my recent wanderings and wonderings:

Bostrom, N., Superintelligence, p. 62-78

In Chapter 5 Bostrom examines several different shapes an ‘intelligence explosion’ or ‘takeoff’ could have. The two most important factors governing this shape are the optimization power of the system and its recalcitrance, or resistance to improvement; in conjunction, optimization power and recalcitrance can give rise to slow, moderate, or fast takeoffs.

Different sorts of potentially superintelligent systems have different recalcitrance profiles. For example, the recalcitrance of developing nootropics would initially be low as little in the way of nootropic research has been done, but would likely to start to rise rapidly after most of the low-hanging fruit had been picked. An emulated mind on the other hand might have low-to-moderate recalcitrance for quite a while if it were able to absorb increasing amounts of hardware to run copies of itself on.

AI could play a role in the development of several different kinds of superintelligent systems, for example a network of knowledge workers whose output is vastly improved in terms of quality and quantity by the aid of an AI research assistant. As such, it makes sense to analyze the dynamics of an AI takeoff in some depth.

The recalcitrance of AI systems is hard to judge, because it may turn out that the key to making an AI smart enough to begin self-improving may be many little insights, each of which requires more and more effort to uncover, or it may be a single insight that eludes everyone for a long time. In the latter case, there may not be much improvement in the system at all until the last piece of the puzzle drops into place, and then change may start happening very quickly.

Bostrom believes that AI recalcitrance will not prove to be very high. Earth spends a lot of time developing new and more powerful computers, so once a human-level AI system is developed it will probably be able to make use of extra computing power laying around to run itself more quickly. It could also avail itself of the truly vast quantities of information available via the internet to fashion an knowledge base far in excess of anything possessed by a human being.

With respect to the other part of the equation, optimization power, it seems most likely that it will increase during the takeoff because people will begin investing huge amounts of effort in any AI system that shows promise. At a certain point the system will become capable enough that most optimization pressure is coming from the system itself. This might result in an improvement cascade, wherein each improvement makes further improvements easier, and the takeoff could be very fast indeed.


Goldsworthy, A., The Fall of Carthage, p. 198-214

In this section of Goldsworthy’s history of the Punic wars I learned about one of the most epic defeats ever dealt to the Roman empire: the battle of Cannae.

After a string of humiliating defeats the Roman senate had decided to put the two incoming consuls, Caius Tarentius Varro and Lucius Aemilius Paullus in charge of the largest army Rome had ever fielded. Each consul was to have four larger-than-normal legions, instead of the usual two, and the consuls were to face Hannibal together.

Hannibal waited until crops had ripened before heading south, eventually setting camp in the former stronghold Cannae. The Romans followed, taking great care to avoid spots where they could be ambushed.

The roman plan was to punch through the center of Hannibal’s army, scattering his infantry. Roman cavalry, notably inferior to their Punic counterparts, were only supposed to prevent flanking maneuvers for long enough to allow victory in the center.

Hannibal anticipated this and strengthened his center, bulging it outward towards his enemy.

After hours of intense fighting the Romans had managed to push the Carthaginian center backwards, eventually routing them. In the process their originally neat formations began to lose shape until the Roman soldiers were in one great mass hacking away at retreating Gauls. At this point the Libyan infantry on either side turned inward to face the Romans, and the real butchery started.

Disorganized and surrounded, the Romans were unable to make much use of their superior numbers. Though they inflicted ghastly casualties on the Carthaginians, Hannibal emerged victorious over the greatest fighting force Rome could muster.

For centuries thereafter the defeat at Cannae would be a Roman yardstick for measuring other losses.

Peripatesis: Forms of Superintelligence, Game Theory.

‘Peripatesis’ is a made-up word related to the word ‘peripatetic’, which is an adjective that means ‘roaming’ or ‘meandering’. I’ve always liked to think of knowledge as a huge structure through which a person could walk, sprint, dive, climb, or fly in as straightforward or peripatetic a fashion as they like.

Here’s are my recent wanderings and wonderings:

Bostrom, N. Superintelligence, p. 52-61

In chapter 3 Bostrom outlines three distinct forms a superintelligence could take:

speed superintelligence is one which functions in a similar fashion to a human mind but which does so much more quickly, like a whole-brain emulation. A collective superintelligence is a superintelligence comprised of a network of lesser intelligences, like an extremely well-run conglomeration of knowledge workers. And a quality superintelligence is one which functions at the same speed as a human mind but which, for architectural or other reasons, does so much better.

He also lists many advantages that a digital intelligence would have over a biological one: for example, electrical circuitry has much lower latencies than neural circuitry, and thus communication among the elements from which a computer-based mind is built would be much faster.

Luce, R., Raiffa, H. Games and Decisions, p. 1-12

This introductory volume to game theory begins by pointing out that ‘conflicts of interest’, situations in which several agents are trying to influence the outcome of a situation while not having full control of all the variables, is both very interesting to most people and at the heart of the discipline.

Game theory gets off the ground by making certain assumptions about the players involved, such as that they have consistent preferences and know the preferences of the other players. In real life of course this is almost never the case, but simplifying assumptions of this sort are often required in developing mathematical tools.

If such assumptions simplify too much, though, the insights gleaned won’t be of much use. Is this the case for game theory?

The authors promise to address this in later chapters, but point out that, at a minimum, game theory could be used to design experiments which could then be used to modify the assumptions of game theory.


Intrapersonal Comparisons: You Might Be Doing It Wrong.

I recently noticed a failure mode in myself which other people might plausibly suffer from so I thought I’d share it.

Basically, I realized that sometimes when I discovered a more effective way of doing something — say, going from conventional flashcards to Anki — I found myself getting discouraged.

Upon reflection it occurred to me that this was because each time I found such a technique, I automatically compared my current self to a version of me that had had access to the technique the whole time. Realizing that I wasn’t as far along as I could’ve been resulted in a net loss of motivation.

Now, I deliberately compare two future versions of myself, one armed with the technique I just discovered and one without. Seeing how much farther along I will be results in a net gain of motivation.

A variant of this exercise is taking any handicap you might have and wildly exaggerating it. I suffer from mild Carpal Tunnel (or something masquerading as CT) which makes progress in programming slow. When I feel down about this fact I imagine how hard programming would be without hands.

Sometimes I go as far as to plan out what I might do if I woke up tomorrow with a burning desire to program and nothing past my wrists. Well, I’d probably figure out a way to code by voice and then practice mnemonics because I wouldn’t be able to write anything down. Since these solutions exist I can implement one or both of them if and when my carpal tunnel gets bad enough.

With this realization comes a boost in motivation knowing I can go a different direction if required.

Peripatesis: Paths To Superintelligence.

‘Peripatesis’ is a made-up word related to the word ‘peripatetic’, which is an adjective that means ‘roaming’ or ‘meandering’. I’ve always liked to think of knowledge as a huge structure through which a person could walk, sprint, dive, climb, or fly in as straightforward or peripatetic a fashion as they like.

Here’s are my recent wanderings and wonderings:

This week has been especially busy, and so little in the way of reading got done.

Bostrom, N. Superintelligence, p. 22-51

Beginning in the second chapter Bostrom discusses a number of paths to superintelligence, including evolving one, programming a seed AI which bootstraps itself to superintelligence, emulating a human brain in a computer, improving human cognition, improving brain-computer interfaces, and designing smarter organizations.

The most direct path to superintelligence is more likely to involve programming a seed AI than it is augmenting human brains or organizations, so it makes more sense to focus on that route.