Computer Revolution

I just came across Chris Granger's essay "Coding is not the new literacy" and although I strongly agree with his overall notion, I disagree with his premise "Being literate isn't simply a matter of being able to put words on the page, it's solidifying our thoughts such that they can be written." and since this is an important topic for me I didn't want to restrict my thoughts to 140 characters.

Coding is Literacy

As far I understood it, Chris' main point is that "Coding is not the fundamental skill", modelling is. He compares coding to writing by stating that "Being literate isn't simply a matter of being able to put words on the page". And that's where I disagree. Being literate means exactly that: "being able to put words [from your head] on the page". It also means doing the reverse and the meaning has somewhat expanded during the last century but it also means exactly that.

In fact I would like to use the expanded definition of literacy:

The ability to [...] understand and use the dominant symbol systems of a culture.

So it's really all about decoding (understanding) and encoding (using) thoughts with symbols. Hence coding is a form of literacy. It's just not well suited for most kinds of thoughts and I think that's where Chris' pain is coming from. But maybe I'm projecting since this is also my pain. But more on that later.

Literacy and Thinking

The second part of his premise is that "Being literate [means] solidifying our thoughts such that they can be written." But writing is not necessary here since everything that can be written, can be spoken. The thought itself doesn't gain anything from being written down. It's the putting it in words (written or spoken) that makes a difference.

Writing down my thoughts is a strategy I use myself quite often to clarify them. This is actually a main reasons why I'm writing this article. But I could also just tell them to my rubber duck instead. I just feel slightly less ridiculous writing them.

I don't think, writing makes me better at thinking though. Having to put my thought in words probably does. But not much. If there is one thing that really challenges and improves my thinking skills it's good discussions with people I respect. There is no immediate need for literacy to do that though. Two comfortable chairs in a quite room is more than enough.

But still I'm not having this particular discussion over a cup of green tea in my favourite coffee house - although I would love to. Because I am literate and fortunate enough to own a computer with internet access, I was able to read Chris' essay and respond to it by writing this here. This is the value of literacy. Being able to have discussions without the limits of time and space. This way I can acquire the thoughts of Chris just as I can acquire the thoughts of Aristotiles. And while it's highly improbable that I ever share a tea with the former, it's impossible with the latter. But despite the millennia in between, the old Greeks still influences the way we think about the world today. Because we an still read their thoughts.

And it's reading new ideas that challenges own ideas and make me think about them and ultimately write them down. So it's the dispute, not the writing that (hopefully) improves my thinking skills. If I had to choose between being able to read or write, I'd choose reading without hesitating.

Modelling is Key

Where I completely and utterly agree with Chris (and it turns out, my good friend and colleague Robert Jenke as well) is that modelling is the fundamental skill. To build a model is necessary in order to put it in software. Just like formalising a thought is necessary before you can write it down. But I have to disagree with "Modelling is the new literacy". It's not. Being able to externalizing your mental models using software, that's literacy.

It's not an coincidence that Chris mentions Alan Kay, the guy who got me excited about modelling in the first place. (At this point I would like to urge every programmer and teacher to absorb as much of Alan's thoughts as possible.) Like him and Chris, I strongly believe that being able to play around (aka experiment) with models is probably the best way of discovering and learning complex ideas and this is exactly what Alan and others tried to do with computers in the 70s and 80s.

That was decades ago. But still, "the computer revolution hasn't happened yet." Why? Because we are still using computers only as a replacement for existing technologies. Better paper and pen. A lot more powerful and interconnected paper and pen that has changed the way we access and distribute information but not what kind of information. The single most distinguishing thing that computers can do that paper can't is to execute dynamic models of our thoughts. But yet only a tiny part of humanity use the capabilities or even know how to use them.

I really want to make this clear: being able to write down the way you think as dynamic, living software is fundamentally different and exponentially more powerful than writing down your thoughts with static words. It's not only recording thoughts, but thinking itself. Or in Chris' words:

To put it simply, the next great advance in human ability comes from being able to externalize the mental models we spend our entire lives creating.

The analogy between coding and writing is quite compelling. Just like writing down thoughts forces you to put them into words and thus clarify them, encoding a dynamic model forces you to think about it on a whole different level. A big part of my job as a software engineer is picking the brains of so-called domain experts. People who usually know very well how something works, but most times this knowledge is implicit. My job is then to make it explicit enough to be able to encode it in the programming language of my choice.

This means my ultimate goal is to put a part of the mind of this person into a machine. If done well, the machine can then do the thinking for the person. Only a lot faster. This might sound scary to some but it's what software engineers have been doing ever since the first machine instruction was executed.

The Problem with Programming Languages

Chris seems to ignore that humanity is already "able to externalize the mental models" - through coding. There are hundreds and thousands of programming languages out there. They are just not very approachable, or easy to learn. It's like if the only "language" we would have to write down our thoughts was mathematical notation. It's a great notation for a whole category of thoughts but it's just a little too complex to be adopted by the majority of people. Sure you can describe a circle as (x-a)² + (y-b)² = r² but usually it's a lot easier to write "circle" or even draw a circle. It might not be an exact circle, but usually that's not a problem.

And most programming languages is to dynamic models what mathematical notation is to thoughts. They are powerful tools but just way too complex for everyday stuff. I regularly attend the local CoderDojo meet-up where me and other "mentors" are trying to teach young people aged 5-15 how to program. Now it's really when you're sitting down with a ten year old that you realize how incredibly complex these languages really are. And the sad thing is that this complexity is incidental. It's a side product. It's not necessary. But it keeps us from learning and using them.

The answer to "How do I make a rectangle with text in it and when you click on it, it becomes red?" should not be "This bunch of HTML + CSS + JS". Just like you should not need to know about Pythagoras' theorem to be able to draw a circle. All you should need is a pen and a surface and your personal idea of a circle. We are still using languages that make it easy for the computer, instead we need to focus on making it easy for the human.

Of course a lot of people are doing exactly that. Trying to make programming easier for humans. That's why Excel is so widely used to build simple models. Because it's (relatively) easy and you can "touch" it and play around with it. And it's what Chris Granger and his associates are working on as well with Light Table and the recently announced eve project which sounds like Excel on steroids. But I'm afraid that like Excel, it will be somewhat limited and only work well for a certain class of models. Although I'm looking forward to be proven wrong.

So what Now?

It's always easier to criticise existing solutions than to come up with a better one. So I take my hat in front of everybody who is trying and doing something about it. I hope that some day I will join that group as well. Until then let me describe what my ideal programming environment would look like.

There is actually one piece of software that comes remarkably close: Etoys. And again it's no coincidence that it's designed for children and by Alan Kay. In Etoys, you can create objects by drawing them and you can give them behaviour by using tile-based programming. So it's almost trivial to "remote" control a virtual car or make the same car follow a track automatically. But you can also do complex things like the Etoys environment itself since the underlying platform, Smalltalk, can be reached from anywhere.

So my ideal programming environment would use a user interface similar to Etoys (maybe without tile-based programming or at least not the default option) but completely based on distributed, concurrent, composable and abstractable entities. I call them zells and wrote about them in my Diploma Thesis. The whole system would consist of nothing but these zells in a single, global address space (for easy sharing and publishing) and the only instruction would be "send zell to zell as message".

Re-usage is an important principle in software engineering but I agree with Chris that "the idea that we can reuse components without having to change them [...] has caused us more harm than good." Components need to be malleable so we can use them as a starting point but adjust them to our specific needs. We can not expect the creator of a software to account for all possible usages of his product. So if a peace of software is not exactly doing what you want it to do, you should be able to change it. But that requires literacy. We need to be able to read and write software.

It almost stroke me as odd that when it comes to text, there has always been a lot more reading than writing. But in the software world it seems to be the opposite. True literacy means that we can exchange dynamic models of our thinking with software the way we exchange our thoughts with text now. My ideal programming environment would allow us to have discussions using these models. Somebody could implement a model of how he thinks a part of the society works and I could change his model to incorporate my own view of the world or argue against it with a completely different model. The difference is that we wouldn't have to explain our thoughts to each other and hope that the other one understands our mental model and builds a similar one in his brain. Instead we could send each other our mental models directly and experiment with the thinking of other people. We could make predictions and verify the correctness of the models. Build upon them and improve them. We could do real science and thus step by step understand the world a bit better. We could record and make our thinking available without the limit of space and time.

This would be a computer revolution.