The human race began a path towards illiteracy when moving pictures and sound began to dominate our mode of communication. Grammar checking word processors and the Internet catalyzed an acceleration of the process. Smartphones, 3-D printing, social media and algorithmic finance tipped us towards near total illiteracy.
The complexity of the machines have escaped our ability to understand them – to read them and interpret them – and now, more importantly, to author them. The machines author themselves. We inadvertently author them without our knowledge. And, in cruel turn, they author us.
This is not a clarion call to arms to stop the machines. The machines cannot be stopped for we will never want to stop them so intertwined with our survival (the race to stop climate change and or escape the planet will not be done without the machines). It is a call for the return to literacy. We must learn to read machines and maintain our authorship if we at all wish to avoid unwanted atrocities and a painful decline to possible evolutionary irrelevance. If we wish to mediate the relations between each other we must remain the others of those mediations.
It does not take artificial intelligence for our illiteracy to become irreversible. It is not the machines that will do us in and subjugate us and everything else. Intelligence is not the culprit. It is ourselves and the facets of ourselves that make it too easy to avoid learning what can be learned. We plunged into a dark ages before. We can do it again.
We are in this situation, perhaps, unavoidably. We created computers and symbolics that are good enough to do all sorts of amazing things. So amazing that we just went and found ways to unleash things without all the seeming slowness of evolutionary and behavioral consequences we’ve observed played out on geological time scales. We have unleashed an endless computational kingdom of such variety rivaling that of the entire history of Earth. Here we have spawned billions of devices with billions and billions of algorithms and trillions and trillions and trillions of data points about billions of people and trillions of animals and a near infinite hyperlinkage between them all. The benefits have outweighed the downsides in terms of pure survival consequences.
Or perhaps the downside hasn’t caught us yet.
I spend a lot of my days researching, analyzing and using programming languages. I do this informally, for work, for fun, for pure research, for science. It is my obsession. I studied mathematics as an undergraduate – it too is a language most of us are illiterate in and yet our lives our dominated by it. A decade ago I thought the answer was simply this:
Everyone should learn to program. That is, everyone should learn one of our existing programming languages.
It has more recently occurred to me this is not only realistic it is actually a terrible idea. Programming languages aren’t like English or Spanish or Chinese or any human language. They are much less universal. They force constraints we don’t understand and yet don’t allow for any wiggle room. We can only speak them by typing them incredibly specific commands on a keyboard connected to a computer architecture we thought up 50 years ago – which isn’t even close to the dominate form of computer interaction most people use (phones, tablets, tvs, game consoles with games, maps and txt messages and mostly consumptive apps). Yes, it’s a little more nuanced than that in that we have user interfaces that try to allow us all sorts of flexbility in interaction and they will handle the translation to specific commands for us.
Unfortunately it largely doesn’t work. Programming languages are not at all like how humans program. They aren’t at all how birds or dogs or dolphins communicate. They start as an incredibly small set of rules that must be obeyed or something definitely will breakdown (a bug! A crash!). Sure, we can write an infinite number of programs. Sure most languages and the computers we use to run the programs written with language are universal computers – but that doesn’t make them at all as flexible and useful as natural language (words, sounds, body language).
As it stands now we must rely on about 30 million people on the entire planet to effectively author and repair the billions and billions of machines (computer programs) out there (http://www.infoq.com/news/2014/01/IDC-software-developers)
Only 30 million people speak computer languages effectively enough to program them. That is a very far cry from a universal or even natural language. Most humans can understand any other human, regardless of the language, on a fairly sophisticated level – we can easily tell each others basic state of being (fear, happiness, anger, surprise, etc) and begin to scratch out sophisticate relationships between ideas. We cannot do this at all with any regularity or reliability with computers. Certainly we can communicate with some highly specific programs some highly specific ideas/words/behaviors – but we cannot converse even remotely close with a program/machine in any general way. We can only rely on some of the 30 million programmers to improve the situation slowly.
If we’re going to be literate in the age of computation our language interfaces with computers must beome much better. And I don’t believe that’s going to happen by billions of people learning Java or C or Python. No it’s going to happen by the evolution of computers and their languages becoming far more human author-able. And it’s not clear the computers survival depends on it. I’m growing in my belief that humanity’s survival depends on it though.
I’ve spent a fair amount of time thinking about what my own children should learn in regards to computers. And I have not at all shaped them into learning some specific language of todays computers. Instead, I’ve focused on them asking questions and not being afraid of the confusing probable nature of the world. It is my educated hunch that the computer languages of the future will account for improbabilities and actually rely on them, much as our own natural languages do. I would rather have my children be able to understand our current human languages in all their oddities and all their glorious ability to express ideas and questions and forever be open to new and different interpretations.
The irony is… teaching children to be literate into todays computer programs as opposed to human languages and expresses, I think, likely to leave them more illiterate in the future when the machines or our human authors have developed a much richer way to interact. And yet, the catch-22 is that someone has to develop these new languages. Who will do it if not myself and my children? Indeed.
This is why my own obsession is to continue to push forward a more natural and messier idea of human computer interaction. It will not look like our engineering efforts today with a focus on speed and efficiency and accuracy. Instead it will will focus on richness and interpretative variety and serendipity and survivability over many contexts.
Literacy is not a complete efficiency. It is a much deeper phenomena. One that we need to explore further and in that exploration not settle for the computational world as it is today.
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