Much later, when I was a student in London, I was subject to budget constraints and went for the cheapest flight whenever possible. Accordingly I found myself flying with an Irish airline, Ryanair, quite a lot. This enterprise is marked by its grisly yellow and dark blue colour scheme and continuous experimentation in lowered flight standards, comfort and safety, all for the sake of lower prices. For a 1-2 hour flight between England and Sweden it was fully acceptable.

Recently I have been flying between Japan and Sweden quite a bit. The intercontinental flight can last more than ten hours, and takes on quite a different character from short flights. Some of the essential absurdities of any flight journey become increasingly difficult to ignore during this time period.

Firstly, there is the fact that the airplane that more than a hundred passengers ride in is a sealed off, highly fragile, mobile cross-section of society and a habitat for human beings. Airplanes need continuous replacement, draining and replenishment of food, waste, excrement, water, fuel and electricity. The air pressure and temperature inside the cabin are artificially maintained. The similarities with an imagined future biodome on the moon are not a few. What happens if an airplane has to land on a tiny island in the middle of the ocean and doesn’t have enough fuel to fly back, or there is some kind of technical problem? All of these buffered flows which the airplane must always replenish would be interrupted, and our very lives are hooked up to those flows.

In addition, hundreds of people are placed very close to each other for an extended period of time with minimal lateral separation (although there is some longitudinal separation in the form of seat rows). A certain neuroticism is provoked. We become hyper-aware of our neighbours and what they do, what they talk about, how they dress and what habits they have. We try our best not to notice. And this lattice, this packing of people, is surveyed from above by the panoptic eyes of the flight stewards and hostesses. Observation not only from above but also from peers becomes essential in maintaining order in a closed-off society where governmental violence cannot reach and the usual norms might easily be violated. Security breaches are to the greatest possible extent preempted by the pre-flight security theatre, and what remains of risk is contained by observation and observability effects.

This pressurised air and pressurised micro-society is spiced up, or muddled, slightly by the increasingly confused roles of the stewards and hostesses. In the jet set era, the air hostess was an object of attraction, an apple of the eyes of businessmen, an icon of liberty who had authority but no doubt also a certain intoxicating effect which helped to pacify. Today she is more clearly authoritarian, but the old role has not quite been erased from people’s minds. Something oedipal threatens to take place. Is this person who serves me food a nurse, a security guard, a mother as well as a possible lover? The neuroticism of the family extended into international airspace. All authority figures merged into one. Male stewards only slightly less confusing.

Fortunately airlines are very happy to serve up small doses of wine and beer to take the edge off the situation. Flying is absurd, but for the moment we have no other way of getting around.

So I would like to, probabilistically, maximise my set of skills in order to best be able to achieve some kind of ambition I have set for myself. Cutting off my hand will probably not help me, but learning arabic might. Being in a car crash is unlikely to be helpful, but being a marathon runner could conceivably be useful. Both involve pain, but one causes irreversible damage, the other causes an increase of strength if done properly. What is the ideal form of schooling for children (If we take the unlikely view that the purpose of schools is teaching things)? That which increases their ability the fastest, which is to say, the most difficult knowledge, the fastest speed of teaching that they can possibly cope with. The maximum trajectory that they can sustain without losing the grip or their interest in the subject.

Should I do the same in life, then? Probably, but it gets tricky, because life experiences that promise to teach me a lot are often unfamiliar, or dangerous, or otherwise involve pain. As we have seen, it is not the case that pain equals learning, but pain can be strongly correlated with learning. To be more precise: if I become crippled in a car crash, or by cutting off my hand, it is because I received stimuli from directions and with intensities that I could not withstand. Provoke me at a slowly building rate, and I will learn to deal with the provocations and perhaps bite back. Provoke me really hard and really fast from the start, and I will die. And then there are provocation vectors to which individuals cannot adapt in a single generation, for instance, drowning. Species might adapt to this kind of threat over several generations. Is not life precisely that which adapts to changing circumstances, potentials and provocations, in particular potential threats or benefits? But intelligent animals, like humans, are a special form of life. We can select what experiences to undergo, and thus what training to receive. This is how we can consciously adapt in advance when we expect a difficult situation. (Young animals play in order to train themselves for adult behaviour, but this kind of training has been conditioned by evolution over many generations. Are there any animals that train selectively to face threats that they have identified during the same generation, like humans do?)

It is a fact that we cannot predict all the circumstances that we will find ourselves in throughout our lives. So we cannot predict what skills or strengths we will need either. Any one who has some kind of ambition in life has no way of establishing completely beyond doubt that their ambition will come true. They can only work towards reducing uncertainty.

At this point a number of different attitudes emerge. One could take the view that “Life is nothing but suffering. We must learn to cope with it.” Subsequently one could teach that suffering is a thing in the mind, and that training the mind to absorb suffering without feeling pain or becoming upset is our best hope. Either that, or reduce the ambitions so as to be frustrated less often. The goal of this ambition reduction is zero ambition, zero desires and zero expectations. With this mindset, you can never be let down. Nullified resistance, maximum fluidity.

Another view: life presents us with challenges, some of which we may overcome, some of which it is pointless to even try overcoming. A “pragmatist” view that tries to establish a middle ground. Some suffering is worth resisting, some is too much. People taking this view have some degree of resistance, but also a breaking point at which they would accept that “life is hard” and bend according to the circumstances of fate. Maybe they would also be opportunist and take their chances for easy gains when they can, to get revenge on life.

And finally, let’s look at the other extreme view. Nietzsche also said, perhaps slightly less famously, that “only to the extent that man has resisted, has he lived.” If I take this view, that I should resist adverse circumstances maximally and have my way in life, I must handle the problem mentioned at the beginning of this post — I cannot predict the circumstances that will befall me. No matter how strong I am, it is likely that there will be some set of circumstances that might destroy my aims completely, and me in the process. But let’s say that I take the view that some outcomes are less likely than others. I buy into some form of probability, for instance I think that five dice are less likely to all have the number four facing up than they are to not end up in this configuration. What choices should I make to maximise my ability to resist, given that some choices actually do make me stronger?

Last year I made some attempts at free association around formal languages and state machines. But at that time, not much was said about the idea of a state itself; an idea which I think holds a lot of interesting uncharted territory.

To begin with, what is state really? Intuitively the word distinguishes states of an object. The key here is the plurality. A single state in itself is uninteresting. Only as contrasted with another state does the first state acquire meaning. This leads us to an interpretation: states are a way of grouping all the possible forms-of-existence, for want of a better word, that an object has, which lets us make sense of such forms more easily.

To exemplify: the light switch in my apartment can be on or off. But in physical space, the plastic switch can occupy a very large number of positions between one and zero. However, the spring mechanism forces the switch into the first state or the second state as soon as I release my finger from it, giving rise to two distinct functional states. When I was a kid, I would sometimes play with the rather old light switches in my parents’ house by keeping the switch in the middle between on and off. A humming sound would be emitted, and the lights would flicker on and off. Surely not a very good thing for the fittings, and potentially dangerous, but interesting since this broke down the abstraction – the continuum behind the discrete was exposed.

So given a physical system, then, which remains the same system even as some parts move around, electrical currents flow, etc, we use states to partition all the forms of existence of that system into meaningful ideas. “The door is open/closed”, “The engine is turned on/off”, “The engine is turned on but there’s almost no fuel left”, and so on. States have probably been with us as long as we have been able to think of binary distinctions, which is to say throughout the history of mankind – opposites such as day/night and alive/dead must have been with the human mind from prelinguistic times.

Today, states are an essential way of turning the unmanageable analog realm into a finite, subjugated digital representation.

The easiest technologies to understand on an intuitive-emotional basis seem to be those that involve physical processes. Objects rotating, moving, being lifted and displaced, compressed, crushed. Gases and liquids being sent around in conduits, mediating force and energy. In short, the technology that has its foundation in classical mechanics.

If these are easy to get a feel for, it would probably be in part because an understanding of mechanical processes has been of use to us throughout history, and also before the advent of civilisation. An intuitive understanding of things such as momentum, acceleration, gravity has no doubt benefited mankind and its ancestors for a very long time.

It gets trickier when we get to the more recent technologies. Take electricity to be an arbitrary watershed. We have no intuitive idea of what electricity is, apart from the fact we might be afraid of thunder. Electricity has to be taught through the abstract idea of electrons flowing in conduits, a bit like water in pipes (to name one of many images being used).

And then there’s analog and digital electronics, integrated circuits, semiconductors and so on, where intuition has long ago been left behind. We are forced to approach these things in a purely abstract domain.

Yet, when our Mp3 players, game consoles, mobile phones and computers do things for us, we are left with a sense of wonder. Our minds, always looking for stories and explanations, want to associate the impressive effects produced by these devices with some stimuli. With a steam engine, it’s easy to associate the energy with pressure, heat and motion, all of which are well understood on a low level. With a mobile phone, not so much. A lot of very abstract stories have to be used in order to reach anything that resembles an explanation, and still it doesn’t reach the essence of the device, which might be in its interplay between radio transceivers, sound codec chips, a display with a user interface and software to drive it, a central CPU, and so on, together with, of course, the network of physical antennas and their connectivity with other such networks. Is it too much to suppose that the human mind often stops short of the true explanation here? That we associate the effects produced by the device with what we can touch, smell, see and hear?

This is of course the point where many computer geeks worldwide start to feel a certain affection for the materials that make up the machines. Suppose that we are in the 1980′s. Green text on a black terminal background. A particular kind of fixed width font. The clicking of the keyboard. The dull grey plastic used to make the case. All of these things can acquire a lot of meaning that they don’t really have, because the users lack a window (physical and emotional) into the essence of the machine. The ultimate “disconnected machine”, to relate to my field, is software.

This brings up questions such as: how far can we as a species proceed with technology that we cannot understand instinctively, how can we teach such technology meaningfully and include it in democratic debate, and how can we use people’s tendencies to associate sensory stimuli with meaning and effects in a more meaningful way? – for instance, when we design hardware and software interfaces.

It’s been just over a year since I started studying for my Ph.D. — formally, I entered the program in April 2009. With at least two years to go, how do things look with some hindsight? What do I think it means to obtain the Ph.D. degree, or, more specifically and usefully, to be a researcher in computer science?

Much of what I’m noticing are things that sound obvious and natural, like everyday truisms, when expressed with words, but the idea I have of it goes a little bit deeper than that. For instance, we all get told over and over throughout our lives, starting in high school, that we have to become good communicators. So it’s not going to be a surprise to anyone when I say that I think the process entails becoming a much better communicator than I’ve ever been before. Maybe what’s different is that I am trying to communicate things that haven’t been communicated before, things that I invented — or things that have hitherto been communicated only by a very small number of people. (Most of the communication I did prior to becoming a Ph.D. student may not have been terribly original.) Basically, reading and understanding a large amount of scientific papers, and understanding them with a particular use in mind, either having or getting a sense of how they fit into your own work. Then, writing your own papers, and communicating, somehow, what you thought, and what you were the first person to think, so that somebody else might read it like you read the works of others, and use it similarly. Then, presenting research, discussing it, and understanding what is being presented and discussed by others — similar challenges in speech instead of in writing.

I can’t speak for other fields, but in computer science ( I work with programming languages and software engineering), I find that a lot of this, for me, has been about building up a certain mental dexterity with formalisms. Understanding the implications of formalisms as you read about them and seek to apply them. Communicating formalisms to others. Some of this is still difficult, in particular the “communicating to others” part, but I think I am achieving things in this regard.

Communication, then, where does it take us? One of my mental images of academic knowledge is a big directed acyclic graph (a tree) where papers reference other papers. A surprisingly big part of writing a paper is ensuring that your work can get assimilated into this graph easily — placing it well, referencing the right things, making sure that you can be referenced easily. Also: defining the boundaries of your work extremely well — here’s where it begins, here’s where it ends. We assume precisely this and arrive at precisely that. It really seems that these things can never be made clear enough.

Which leads to another mental image of research: the paper/unit of work as a building block. The more solid it is, and the harder and sharper its surfaces and edges are, the better structures can be built from it (though I think there are other kinds of valuable works too). That’s one direction I think I need to be aiming for as an aspiring researcher.

Sometimes, though, the generalizers get it right. These are often moments of exceptional and lasting innovation. One example of such a system is the fabulously influential (but today, not that widely used) programming language Smalltalk. Invented by the former jazz guitarist and subsequent Turing award winner Alan Kay, Smalltalk was released as one of the first true object-oriented programming languages in 1980. It is probably still ahead of its time. It runs on a virtual machine, it has reflection, everything is an object, and the separation between applications is blurred in favour of a big object box. On running Squeak, a popular Smalltalk implementation, with its default system image today, users discover that all the objects on the screen, including the IDE to develop and debug objects, appear to follow the same rules. No objects seem to have special privileges.

Another such system is an application that used to be shipped on Mac computers in the distant past, Hypercard. Hypercard enabled ordinary users to create highly customized software using the idea of filing cards in a drawer as the underlying model, blurring the line between end users and developers through its accessibility. I haven’t had the privilege to use it myself, but it seems like this was as powerful as it was because it served up a homogenous and familiar model, where everything was a card, and yet the cards had considerable scope for modification and special features. Even though, in some ways, this system appears to be a database, the cards didn’t need to have the same format, for instance. (Are we seeing this particular idea being recycled in a more enterprisey form in CouchDB?)

There are more examples of successful highly general design: the Unix file system, TCP/IP sockets and so on. They all have in common that they are easy to think about as a mental model, since a universal set of rules apply to all objects, they scale well in different directions when used for different purposes, and they give the user a satisfying sense of empowerment, blurring the line between work and play to draw on the user’s natural creativity. Successful general systems are the ones that can be easily applied in quite varied situations without tearing in the seams.

While not widely used by industrial programmers today, Smalltalk was incredibly influential. In 1981 Objective-C was created by Brad Cox and Tom Love, directly inspired by what the Smalltalk designers had done. Objective-C was subsequently used as the language of choice for NeXTStep, and later for Apple’s MacOS X when Apple bought NeXT. Today it’s seeing a big surge in popularity thanks to devices like the iPhone, on which it is also used. In 1995 Java was introduced, owing a great deal of its design to Objective-C, but also introducing features such as a universal virtual machine and garbage collection, which Objective-C didn’t have at the time. In some sense, both Objective-C and Java are blends of the C-family languages and Smalltalk. Tongue in cheek, we might say that it seems evolution in industrial programming these days consists of finding blends that contain less of the C model and more of smalltalk or functional programming.

One way of making a name is stringing words together until the meaning is sufficiently specific. E.g. “morphism averse co-dependent functor substitutions in virtual machine transmigration systems”. Thus the abstruse academic research paper title is born.

Sciences sometimes give new meanings to existing words. This could be called overloading, following the example of object-oriented programming. E.g. a “group” in mathematics is something different from the everyday use of the term. A “buffer” in chemistry is something different from a software or hardware buffer, even though a fragment of similarity is there. And so on. This overloading of words gives newcomers to the field a handle on what is meant, but full understanding is still impossible without understanding the actual definitions being employed.

Sometimes new terms can be created using inventors’ names and everyday words. E.g. a “Lie group” or the “Maxwell equations”, or “Curry-Howard correspondence”. This is potentially useful, but perhaps not something you can do freely with your own research without seeming like you’re trying to inflate your ego excessively. (Even though researchers love inflating their egos, nobody wants to admit it.)

There’s a similar problem in software development. When we invent names of functions, classes and variables, the lack of words becomes very clear. Intuitively, what is an “adapter registry”? An “observer list”? Or an “observer list mediation adapter?” My feeling is that we often end up compounding abstract words because we have no better choice. And here lies a clue to some of the apparent impermeability of difficult source code. We need better ways of making names. We’re inventing ideas faster than our language can stretch.

The morning has turned into a game. It’s me against the city layout, me against my memory, me against entropy and the temporal degradation of my cognitive faculties. The ludic dimension has entered my life again. And soon enough, I find the place I was looking for.

When we have a sense of competition, that a victory against something or someone is possible, our awareness of life is heightened in every way. We pay more attention, we notice more, we become more here and now. The endless simmering chatter in our heads, nearly meaningless thoughts that usually refuse to yield anything meaningful, gives way to absolute focus.

It occurs to me that a society where everyday tasks can be carried out like they are games, victories to be won, might be a more moral society, with greater happiness and life awareness for everyone. In such a society, even if you lose a particular game, you win something else.

300. HOW FAR EVEN IN THE GOOD THE HALF MAY BE MORE THAN THE WHOLE. — In all things that are constructed to last and demand the service of many hands, much that is less good must be made the rule, although the organiser knows what is better and harder very well.He will calculate that there will never be a lack of persons  who can correspond to the rule, and he knows that the middling good is the rule. — The youth seldom sees this point, and as an innovator thinks how marvelously he is in the right and how strange is the blindness of others. (Helen Zimmern transl.)

Friedrich Nietzsche did not describe software making – I can only assume that he was describing authors and ideologists – but this seems to capture the difficulties of software development only too well. And it seems to give a recipe for how to overcome the communication difficulties (abandon exotic, over-refined solutions and focus on an easily understood middle ground, so that everybody can get together and comprehend the architecture). This was originally published in 1886.

With that, merry christmas!