Dear fellow programmer,
I used to think humans wrote software the way they did because they knew what they were doing. Then I realized that they didn’t really know, but adopted ways that seemed to work better than others. Or maybe rather humans were adopted by the ways that best knew how to survive, whether they actually “worked” or not. In any case, I trusted “evolution”, that is, ultimately, other people, to have figured out the best way that software could and should be written. But everything I knew about computing changed when one day I met a Houyhnhnm (pronounced “Hunam”), who told me how things were done in her faraway land. She made me think in terms of computing systems rather than computer systems; and from my newly found understanding, I could see clearly how computing systems could and should be, that today’s (mainstream) Human computer systems aren’t. But mostly, she taught me how to think, by myself, about computing. And so let me take you through my story of computing enlightenment.
Beyond the Sea of Potentiality
This adventurous Houyhnhnm, whose name was Ngnghm (but I call her “Ann”) had heard of a stranger who long ago visited her home country. So the legend said, the traveler, called Gulliver, was a “Human”: a paradoxical creature that looked just like a Yahoo, yet who like a Houyhnhnm (at least to a point) possessed the ability to reason and speak. There were fantastic tales of a planet full of such Humans, as attributed to this Gulliver; and the stories went that in the land of Humans, there were animals known as “Horses” that looked just like Houyhnhnms, yet who like Yahoos couldn’t speak any language and were likely not fully sentient. Ann, immensely curious, had embarked on a journey of discovery to find and visit this fantasy land of Humans and Horses, if it existed at all. But while sailing the Sea of Potentiality, her transdimensional ship collided with débris caused by Human (or was it Yahoo?) pollution — and she was shipwrecked. Now she was stranded onto our plane of existence (actually a sphere). Not being able to communicate in Human language, she was initially mistaken for a wild and dangerous mare; and she had but narrowly escaped being sent to the knacker — or worse, to a government research facility.
By the time I met her through a friend, though, Ann had already learned to read and write our language, albeit imperfectly. She was desperately looking for parts to build a new ship, so that she may some day sail back home. Since I know nothing of transdimensional travel, I instead showed her how to use the Internet to find all the support that mankind could offer her. She was stupefied by how similar yet how different our Human computer systems were from those of the Houyhnhnms; in some way, ours were so much more advanced, yet in other ways they were so desperately primitive. And as she was telling me of how Computing was done amongst Houyhnhnms, I was suddenly reminded of how I had always felt that there had to be better ways to engage in computing, but couldn’t pin point exactly what was wrong. Now I had found a clearer vision of a world I was yearning for — a world I felt like I had lost, though I never had it — and a world that was within reach if only I could build a suitable ship, to sail the Sea of Potentiality and reach the mysterious and enticing land of Houyhnhnm computing.
Some people have accused me of having imagined all this encounter. But my hope is that, after reading my story, you’ll see that it is not only real but necessary, and soon you will start telling other people what you’re now imagining; and eventually, you and I will build the ship with which we will sail together to the land of Houyhnhnm computing.
A Different Point of View
The fundamental difference between Human computer systems and Houyhnhnm computing systems is one of point of view. Houyhnhnms do not possess a different kind of logic, nor mathematics, nor physics; though they have discovered how to travel across dimensions to other potential universes, they do not have quantum computers, logical oracles, or any magic means of computation beyond our own capabilities. However they approach computing in a way that is foreign to us Humans, and that leads to very different results.
Whereas Humans view computers as tools below them to which they give orders and that do their bidding, Houyhnhnms view computing as an interaction within a system around them that extends their consciousness. Humans articulate their plans primarily in terms of things: the logical and physical devices they build (sometimes including tools to make more tools), in the lower realms of software and hardware. Houyhnhnms weave their conversations foremost in terms of processes: the interactions they partake in, that they attempt to automate (including these conversations themselves), which always involves wetware first. In short, Humans have computer systems, Houyhnhnms have computing systems.
You may dismiss all this as dreamy philosophy, empty words without any consequences — I certainly did so at first. Yet the difference in point of view that I am now attempting to distill leads to systems that are organized in very different ways, that are optimized for very different metrics, and that engage users in very different processes, with role delineations according to very different criteria, resulting in a very different variety of artifacts of very different sizes, but most importantly, connected in very different ways. It may all be but just so stories, but stories have consequences.
What made me most aware of this difference was when Ann discovered that, like she was in her own world, I was trained in writing software, and then asked me to demonstrate the working of some Human computing systems, starting with the simplest I could find. So I showed her simple programs I was writing in C; C is a relatively simple programming language with a somewhat familiar syntax; its formal semantics is simple and well defined in theory, and in practice it is a universal programming language capable of doing everything; indeed it is used almost everywhere that Humans have computers. Yet, after she painfully assimilated enough of what I showed her, struggling all the way, her conclusion was that, no, I was obviously not programming in C, and that I couldn’t possibly be programming in C, because C was not a universal programming system at all, but could do next to nothing, and only very inefficiently so. Instead, what I was programming in was not just C, but a C compilation toolchain plus an IDE and an Operating System plus plenty of libraries and utilities, that all together constituted a very large computing system with incredibly complex formal semantics; what more, a large part of the interaction between these components depended on a large number of completely informal semi-conventions about how the filesystem was or wasn’t used by which process, and how these system and user processes themselves were managed. What to Humans looked simple because our point of view focuses on some aspects and neglects others, to the Houyhnhnms was an unmanaged and unmanageable mess because they see things from a different angle.
What Houyhnhnms considered to be a simple system was one that has a short description when you take into account the entire software system, including the compiler, interactive editor, formal verification tools, libraries, operating system, drivers, hardware blueprints, etc., and including the informal conventions used by isolated or cooperating users, or the chaotic lack thereof. C, because its underlying development environment necessitated huge and largely informal support structures, constituted a very complex computing system, even though it looked small and simple once the support system was assumed. Functional programming languages like ML or Haskell yield much simpler systems if you take into account the verification tools and the development process; yet they still neglected entire swaths of what makes a complete computing system, such as IDE, Operating System, persistent storage usage conventions, schema upgrade, etc., and so they ended up being overall still pretty complex.
By Houyhnhnm standards, the simplest Human computing systems, though far from ideal, would be more something like Smalltalk or the other systems built by Alan Kay’s ViewPoints Research Institute, where the description for the entire system, including compiler, IDE, libraries, operating system, drivers, interactive graphical environment, font rendering, etc., all fit in a few tens of thousands of lines of code. Note that FORTH has been used to build complete systems of even smaller overall software size; but being low-level, FORTH relies more on informal design patterns and manually enforced limitations, which according to Houyhnhnm criteria make the resulting system overall more complex, especially so if multiple people are supposed to work on the same system. Still, such simplistic systems make sense for isolated resource-starved programmers.
Why Simplicity Matters
Houyhnhnms certainly don’t restrict themselves to using systems that are simple (according to their metric). But these simple systems do play an essential role in the Houyhnhnm computing ecology: first, they are an essential part of computing curricula, so programmers can get a grasp of all the parts that make a complete system; second, the ways to factor and evolve such systems is also studied by designers and managers so they may think in terms of overall system architecture (including the Houyhnhnm factor, of course); last but not least, they are also instrumental in the bootstrapping process by which more complex systems are built in a way that is auditably secure.
In any case, a change in point of view led to a completely different metric to assess the simplicity of computing systems. It would also change how to judge other qualities of computing systems in general — and thus change the approach to how computing is done and what artifacts it yields. Alan Kay said that A change of perspective is worth 80 IQ points. The way we humans build and use computing devices may have a lot to gain from considering the Houyhnhnm perspective. And next quality of computing systems that Ann made me reconsidered was something as basic as Persistence…
How do you pronounce “Ngnghm” or “Houyhnhnm”, my friends ask? Mostly, I don’t. You must realize that these are attempted transcriptions of sounds that Houyhnhnms make with their equine mouths. So if you’ve never met a Houyhnhnm, just imagine one of them whinnying in a way that you’d transcribe like that if you had to. Or don’t. Personally, I have stopped trying to mimic the way Ngnghm neighs, and if I have to pronounce one of these two names when talking to a friend, I just call my friend “Ann”, and pronounce “Houyhnhnm” as “Hunam” — like “Human”, but exchanging the “n” and the “m”. Importantly, though, I am careful to avoid the H-o-r-s-e word when talking about Ann and her kin: she deeply dislikes and vehemently objects to being assimilated to these stupid creatures, Horses — just like you probably wouldn’t want to be taken for (and treated as) a Yahoo.