If computing were a natural science, what might it look like?

One of the hardest-won results from the natural sciences, uncovered over the last half-milennium, is simple, but hard to keep in mind: the real world is not accessible to our cognition. 

When we realize this, it makes the world a mystery, but this, in turn, makes the world interesting and exciting to explore. That's science. And since the machinery of our brain is part of this mysterious world, it too is a mystery, and we have almost no idea how it's interfering with, and relating to, our perception of the world.

Our intuition fooled us into believing that we 'understood the world'. It felt like we understood it. But then Galileo pointed out that, by our intuition, a heavy body will fall faster than a light one. But, in reality, it doesn't. And, when we thought hard about things we already knew, things that we forgot because parts of our intuition acted as obstacles, we realized that it was rational for them to fall at the same rate.

And there are always more internal obstacles.

 Another intuitive part of our rationality makes use of the concept of a "clockwork universe", recruiting it as a criterium for understanding. But as every first-year physics student learns, and as Newton demonstrated in the 17th-Century, there is no clockwork, contact-mechanical explanation for gravity, or any other force. No system of invisible pulleys or rods can 'explain' these forces. They are simply 'qualities' of the universe, and we were forced to adjust our idea of explanatory adequacy accordingly.

In general, we can say that the goal of the natural sciences is to find out what is going on outside our perceptions -- 'outside our skins', 'out there' -- to use just a few suggestive phrases to convey a difficult idea. 

But here's the problem: we're still in the mix. We can only try to get out of our skins. And we need to keep trying. Each time we discover another way that our minds are interfering with the accuracy of our scientific theories, it allows us to work positively for a while. But there's always another horizon. And we always come across further mental interference, further stipulations that need removal, later on. Our own cognition is, ironically, the most serious obstacle in the sciences.

Another problem arises because many of our scientific interests revolve around ourselves, and our minds. It's almost impossible to find any work on the mind which isn't rife with mental interference -- but many researchers are aware of the problem, and try to sort the results from the stipulations, the external from the internal.

Here's a problem that's peculiar to the cognitive sciences: we look at ourselves from the outside, appropriately, as animals. But externally measurable behavior is superficial. So we need a human to interpret the behavior. And we need to recognize complex phenomena, the internal ones, as we experience them, so that we can experiment on ourselves, using ourselves as gauges or meters of the complex phenomena under investigation. 

So, in the classic example, even though we understand almost nothing from external measurement about the biological organ that provides us with language (the Language Faculty), we can use ourselves to test the boundaries of language phenomena, from the inside. For example, we can ask if the sentence "I'm going to the store" is experienced as grammatical, where we use a complex internal organ to make a judgement on external stimuli -- and if we ask if "I go store to" is grammatical, the different answer leads us to interesting research questions. Without this internal meter, we wouldn't know how to even approach this as a question in the natural sciences.

Clearly the human activity of computing is not something that has even begun to broach these difficulties. As a practical matter, though, computer people, and computer users, are impacted by these issues everyday. The craft of computing has developed, to at least cope with the issues in a limited way, and get work done. But, in my view, no computer scientists or programmers have any awareness of what is going on in the real world of computer-human interaction, no more than a pianist knows what is happening to our brains when we hear music. We have a craft, but we have not even the beginnings of a natural science of computing.

What would a natural science of computing look like? What might programming look like, as a result?

I want to provide a taste of the kind of research needed.

There are many tools available for web programming. Generally, some engineers have found themselves doing the same thing many times, and recognizing this they attempt to create a layer, something that allows them to do the same thing they've done before, but with less effort. As a result, the higher-level view of this layer becomes a kind of notation of its own, backed by its own ideas, which can be combined and parameterized so they become a kind of general platform on which to build applications.

As a result, application development becomes rather path-dependent, making many programs effectively the same. Developers begin by imaging these elements and combining tools, and then making a stab at using them to take steps forward, towards products they have in mind.

It's important to understand that all this 'bridging' happens in the brain, and is completely dependent on mental faculties that as yet have no name or research program. 

The tools are something external, and too complex to know completely, but the programmer needs to understand them better in some way, in order to move forward in some direction. The 'direction', or 'product definition', is an exercise of the imagination, with some notes on paper, and the programmer picks some aspect of this fantasy to approach with tools that he knows, or believes he can discover something about.

To address this 'bridging problem', the programmer needs an increasing understanding of (1) the emerging 'product', from a user's perspective, (2) the emerging program, from an engineer's perspective, and (3) the frameworks, libraries, ideas, and communities that these are built upon.

So, we've begun to characterize what the programmer is doing as a human activity, one that needs to be investigated from a biological perspective: we need to pick elemental examples of these bridging moments, and study what makes it easier or harder for the mind to organize a solution.

But the state of the art is rather different. There's a kind of struggle to create support systems. Helping with (3) are the myriad websites that have emerged to let programmers share technical tricks and ideas, and endless 'branded movements' that attempt to justify and codify sets of ideas that provide various kinds of inspiration.

The focus is on technology and borrowed ideas. But none of this addresses (1) and (2). That's because it's hoped that the programmer will be inventive, and bridge the gaps. But that means the critical human dimension of software development, the study of the user's issues, and the programmer as user, suffer from lack of serious investigation.

These are questions that could be investigated from a natural science perspective.  In regards to (2), what unknown mental faculties enter into the simplest internally-experienced phenomenon of 'discovery' while looking within a program? When the programmer needs to create some new infrastructure to deal with some 'type' or 'aspect' or 'property' of the problem as they perceive it, how does their programming environment make this hard or difficult? 

As an example, say I'm writing a completely different kind of web application. Say that the most important thing, to me, is typography. Nothing I see in my program should be more important than the new issues before me, because the whole point of the program is to study 'typographical effectiveness' for human users. 

Unfortunately, nothing in a framework or programming environment will facilitate the creation of a fresh, new, special-purpose theory, or framework, with which to study the creation of programs that support the as-yet-unknown world of the typographer. There is general-purpose functionality, and in pre-trod areas there are special-purpose frameworks, but there is nothing to help me create the special-purpose ones, and to help me find my way around these new special-purpose theories once I've created them. All this despite the fact that most of life is quite mysterious, and hence certainly unexplored by software.

The lack of support for developing and exploring 'the new' and 'the special', is coupled with a prejudice towards 'the general', at least a particular, extremely limited interpretation of the notion of 'general'. The combined effect is the lack of imagination and sensitivity in almost all computer products and applications. Motivated people, who are exploring new territory, can still muddle through and get some limited new things to happen, but they are almost entirely on their own. Because no one is studying the problem of technical support for innovation, or bridging, we rely instead totally on the innovation of the worker in overcoming the poverty of the available tools. 

All of this derives from the total lack of a perspective within computing that falls within the natural sciences. Imagine if we observed a very mysterious behavior among spiders in the wild, and we just said "well, I don't know what's going on, but the spiders keep making webs, so it doesn't really matter!" Science doesn't do that. We want to know what's happening. But if it's us, we might care more, but we don't investigate what's actually going on. If we did, we could help. And help ourselves, because we could really use good tools for investigating new ideas. In the future, the computer, in whatever form it takes, might actually fulfill its potential, and normal people, who have better things to do than keep up with another trivial new programming environment, or another trivial programming 'paradigm', will be able to use computers to explore the endless mysteries around and within us.