A sideways look at economics

Science fiction is not a genre that has ever done much for me. Space travel, however, regularly conjures similar enjoyable feelings of escapism to the psychedelic carpet ride of some Bowie songs. One of those waves of emotion was triggered during the past Christmas holidays as I was lying on a sofa, half comatose after washing down yet another food marathon with plenty of my mother’s home-brewed ‘Nocino’ liquor.

While heroically trying to both stay awake and flip channels on the remote, I landed on the movie First Man, narrating the background story to Neil Armstrong and his moon landing. Suffice it to say that not only did the film keep me awake; it also awoke a train of thought which I will share below.

My first reaction was a familiar one: they actually landed two men on the Moon in a washing machine! The sight of a lunar landing module has always made my jaw drop, since the first time I saw one on a trip to Cape Canaveral in my teens. To be clear, the emotions it conjures are sheer astonishment and awe at human ingenuity and bravery, rather than disappointment at not witnessing a fully-fledged Starship Enterprise (I was always more interested in the spandex body suits in that series, anyway).

As I grew older the idea of landing men on the moon in a washing machine also became an important life paradigm, at the crossroads of psychology and economics. (Bear with me.) As economics students, me and my friends embraced optimisations more as a way of life than simply an elegant mathematical approximation of human decision-making. However, I progressively identified two problems with pursuing an optimising way of life.

First, for it to work, optimisation should be applied to general and broad problems, rather than discrete and narrow ones. In other words, we typically enjoy spending hours on optimising many narrow tasks, such as reading reviews to find the best value-for-money restaurant or analysing the price per edible area of a 10-inch vs a 12-inch pizza, to cite a couple of not-so-random examples. There are countless optimisations like these that we perform daily, often unconsciously. Problems arise when we are carrying out so many narrow optimisations that we lose sight of optimising the most precious commodity of all: time. Instead, we should really try and optimise a few important things: like happiness, wealth, leisure and health. These broad optimisations, however, are very hard problems to solve, and we often resort to adding constraints to facilitate a more tractable outcome.

And therein lies the second problem: constrained optimisations are often cop-outs in disguise, elaborate rationalisation devices that stifle creativity and hinder personal growth. In my experience, many financial practitioners are still confused by the difference between a constraint and an objective. This confusion comes about because solutions to portfolio optimisations are often driven by too many constraints, making the original portfolio objective (e.g., to maximise return) almost redundant. Similarly, in life, we pretend to want to optimise happiness, but then set so many arbitrary constraints on our time, effort and resources that a feasible solution to our happiness exists only over an extremely narrow range of the status quo. Perhaps the movie prompted this first reflection, as I had recently caught up with a friend discussing life choices and trade-offs; how the impossibility of having everything translates into not being sure what it is that we actually want; even though deep down we know what will make us happy, but our rationalisation efforts invariably and passively anchor us onto the same, well-trodden path.

Next time we meet up I will mention the moon landing as one rare example of a real-life optimisation done right, where an incredible outcome materialised in spite of huge constraints on technology, resources, coordination and time, simply because they kept the ultimate goal (the moon) in mind.

There was a moment towards the end of the film that triggered another reflection. Neil Armstrong is guiding the lunar module down towards the moon surface. He is at the peak of his ice-coolness, laser-focused on the task in hand, when, suddenly, some red lights start flashing and beeping on the washing machine dashboard. You can barely see a flicker of worry on his face or in his voice, although he is in a situation where almost anyone else would have failed the mission due to soiling their space suit. Armstrong basically ignores the alarm, and the mission is a success.

I got curious and did some reading on what the alarm was about. Turns out that it was a false alarm, triggered by a small and thankfully inconsequential software error. The software and the equipment on board the washing machine were themselves a beauty of engineering and maths; landing the craft required a harmonious waltz between human skill, extremely scarce processing resources and vital data, partly radioed from earth and partly relayed by the on-board equipment, and all happening at the most crucial time of the mission. It was another example of constrained optimisation done right, albeit with an error. But also, I think, it provides a weird allegory for the defining moments of our own lives: moments that are seemingly random, but inextricably linked by the connections we form, the signals we catch, the processing we apply and the resilience that we build.

For me, at least, it was a reminder of a perhaps counter-cultural hunch that I hold about connections. What matters is not maximising their number, but rather the constant pursuit and identification of a handful that are worth fighting for, be it a relationship, a job or a cause. In fact, this is a bit more than a hunch. A research paper by Markus Neumann that applies agent-based modelling techniques is able to show that a social network made up of many small clusters is more resilient, altruistic and more prone to reciprocity than one big, more homogenous network dominated by one cluster with many connections.

Another agent-based experiment, less formal but very addictive, shows how, in a hypothetical zombie apocalypse, the experience accumulated from learning how to slay zombies is a key parameter giving humans the upper hand in their fight for survival. Interestingly, with only moderate levels of learning and initial skills, humans can win the fight even when they are outnumbered by zombies by a factor of 4 (see picture).

Optimisation

The final twist is that only a handful of people who are master zombie-slayers typically survive the game. The moral from the zombie apocalypse experiment is that what differentiates a human from a zombie, a life worth living from a passive existence, is the strength of our connections rather than the number of our connections. And it turns out that — for me at least — the connections that matter generate a self-reinforcing interest and curiosity that effortlessly make me want to revisit them over and over.

With that, I think it is time for me to conclude this space oddity of a blog and let you all go and revisit some of your own significant connections, preferably over a drink and a David Bowie song. And if Ashes to Ashes comes on, remember:

“My mother said, to get things done
You’d better not mess with Major Fathom.”

 

 

Read more from Fathom on space travel

Billionaires on a rocket

Dogecoin to the moon

Would you rather be the first person on Mars or starring on Love Island?