Educators sometimes hold up an ideal of knowledge as having the kind of coherence defined by formal logic. But these ideals bear little resemblance to the way in which most people experience themselves. The subjective experience of knowledge is more similar to the chaos and controversy of competing agents than to the certitude and orderliness of p’s implying q’s. The discrepancy between our experience of ourselves and our idealizations of knowledge has an effect: It intimidates us, it lessens the sense of our own competence, and it leads us into counterproductive strategies for learning and thinking.¹
– Seymour Papert
People are sentient and we know that we are sentient. We are also social creatures. The human mind is aware of ‘agency’, in both itself and others. Since the beginning of recorded history, and probably long before, we have even ascribed agency to objects and events in the natural world. Once we attain consciousness, it becomes powerful and efficient to reuse this mind machinery to understand the world around us in familiar terms. Mirror neurons in the human brain enable us to read or infer intention in others. They do not merely form patterns of thought – they reflect them.
Syntonic is a word sometimes found in music theory, but in psychology, syntonicity means having a strong emotional connection with the environment. It is understanding something through identification with it. It is achieved by putting oneself “in another’s shoes”, and it is key to human learning. One form of this is imitation, and children do this all the time, with everything from trees and animals to teapots and airplanes. Another form is metaphor, where an established understanding is substituted for a new and unfamiliar thing. See Ancient Metaphors for examples from the IT world.
When we mature, many of us discover computer programming and would like to use the same built-in learning method that allowed us to develop ‘common sense’. However, most programming languages and their text books are so abstract, formal, and doctrinal, that it’s nigh-on impossible to get very far this way. As a result, computational thinking recedes off into the ivory tower, and the world is much worse off because of it.
This type of learning is well suited to therapeutic applications due to its natural, informal flow. Starting with the ‘hard wired’ facilities we all have, ‘bootstrapping’ (discussed below) is a very individual and non-doctrinal process.
An interesting and more in-depth exploration of syntonicity in programming languages was written by Stuart Watt.²
I have found Forth to be a very syntonic language.
Syntax and structure are the first face that we see of a new language. Some are fairly natural (e.g. BASIC), most are verbose and intricate, and some are at the extreme end of mathematical formality (e.g. Haskell). Forth is positively Spartan by comparison, with the majority of keywords being three letters or less, and the ‘: … ;’ pair providing most of the structure and context. Some long time users of Forth do not even like its syntax and quickly override keywords (a trivial task in Forth), inventing their own to craft the language to be more in tune with their way of thinking. Ironically, this makes them love Forth more, not less. It is an extremely simple language. At its core, Forth is just a mechanism to reduce the cost of calling a subroutine to merely referring to it by name. But this is not what makes Forth syntonic.
“syntonicity is not directly a property of the syntax, or even the semantics or pragmatics of a language, but a property of the stories that we tell about it” (Watt p.5)
Forth is a stack-based, threaded, concatenative language with a tightly coupled interpreter and compiler. To explain these terms, and thus ‘tell a story of Forth’, we’ll use a metaphor:
Forth – a hiker (named ‘Arkady’ for convenience)
Stack – her backpack
Thread – the trail
Interpreter – her mind (neurology)
Compiler – her logbook
Notice that there is no clear distinction between traveler (Forth) and journey (program). Arkady’s journey is of more interest to her than is her destination. She is open to distraction, side-trips, and unexpected eventualities. Even mistakes are sometimes learning opportunities. This is the way of Forth – less focus on design and protocol, more on exploration, discovery, and emergence. While most languages are applicative (functions are applied to data), Forth is concatenative, which is a much more natural and emergent process. There are also few safeguards in Forth; the entire environment (machine) is wide open. This freedom is anathema to authorities of language design, which might partly explain why Forth-like languages are not more widespread. It’s much safer to clone an application from an existing template and/or framework than to invent a new one. Of course, the result is a copy, not an original. Incidentally, in much research funding, the outcome must almost be predicted along with careful metrics and timetables (ask anyone who has prepared a grant application). This squelches creativity and serendipity. It also puts a premium on positive results over negative (and perhaps greatly informative) ones. In fairness, just so we don’t make the mistake of assuming that everyone agrees that doctrine is a bad thing, there has been a large and successful effort to come up with a more standardized, ANS Forth.
Her backpack (the stack) is a readily available, last in, first out (LIFO) pile of items that she adds or removes as required. As a good hiker, Arkady is always aware of what’s in her backpack. She keeps often-used items (tools, map, compass) near the top. Longer term necessities (food, tent) are towards the bottom.
She walks along the trail (thread), step-over-step. Some steps are short and obvious, like avoiding big rocks and snakes. Some are more complex and subtle, such as crossing streams and staying downwind of bears. Many are actually composites of smaller steps. Some require more items from the backpack than others. At each step, she has the same backpack, although the exact contents may vary. She may sometimes just take the top few items, drop the pack, and head off down an interesting side trail. This is how a Forth program is built up. New ‘words’ are written to accomplish tasks. These words are then threaded together as higher level words invoke a series of them. Eventually, a single, highest level word is the starting point for the whole program, which is just a chain of subroutine calls.
Using all of her neurology, from senses to brain to common sense, logic, and rationality, she ‘interprets’ her world. She learns new facts and skills as she walks, gradually ‘bootstrapping’ a deeper understanding of her environment and more powerful and efficient use of resources (food, energy, time). To learn if and how something works, she prods it and observes the results. If she finds an unfamiliar mineral, she could bring whatever tools she is carrying to bear. Or, she could invent an entirely new tool. She could craft a crude microscope from the magnifying lenses and rolled up map in her backpack. If she has time, a mass spectrometer may be suitable. In Forth, quick tests and trials are inexpensive and easy. There is no odious edit-compile loop to get in the way. For example, to find what OVER does, put a few numbers on the stack, type OVER, and examine the stack to see the result. Stumbling around with her nose in manuals and books would perhaps cause Arkady to miss a fossil or patch of berries. It is also a good way for her to become lunch for a mountain lion.
A word about bootstrapping. Sometimes, when a skill is applied to produce a result, new knowledge (or a new tool) is gained in the process. This new knowledge opens the door to skill-set improvement or refinement, which enables hitherto impractical or unseen possibilities. In turn, even more new knowledge is obtainable, and the process repeats. The result is flint knife to bow and arrow to alchemy to chemistry to electronics to spaceflight. Bootstrapping is the essence of Forth. Sadly, multitasking, object-orientation, dissociation and data-hiding, and that ultimate chestnut, ‘leveraging’ are all much more in vogue today. Multitasking in human thinking is greatly overrated. Deeper, syntonic thinking enables more creativity and innovation. If Forth was more widely used and understood, you might well be reading this on Mars right now. If it had been invented earlier, you might be reading this on Triton.
From time to time, Arkady considers new observations, knowledge, thoughts, and ‘steps’ to be well-established and important enough to jot down in her logbook. This log serves as a permanent record of all she has learned on her journey. It is in fact, a purified, corrected, ‘frozen concentrate’ of her trail.
Arkady eventually arrives at the end of her journey. It may have been cut short for various reasons or maybe her destination is different (maybe even better) than she originally intended. This is a function of her curiosity as much as weather or circumstance. In any case, she still has her logbook, for her or others to use as a future guide (be they human or machine).
Some would say that it’s wrong to argue for Forth going forward. After all, it’s an old language, and was originally created for control of machinery in an era of sparse computational resources. As programs and systems grow ever-more complex, capable, and intelligent, such a language has outlived its usefulness. However, I must disagree. The future is not just about frameworks, big data, and augmented reality. It will be at least as important to build new, ad hoc, ‘micro’ systems rapidly and locally in a time of dizzying acceleration of technology. Creating, testing, and problem solving starting from first principles will always be valuable.
Understanding the world requires thinking in new languages. Forth is to computer science what math is to physics. Computational thinking, syntonicity, learning-by-doing*, and good old human common sense are not headed for the dust bin of history any time soon. Here are some further thoughts on learning.
* I am, however, perhaps not a very good constructionist, try as I might.
I once tried (unsuccessfully) to acquire a minor Logo implementation.
I believe in learning-by-doing something else ! A wide, diverse search is
often the most efficient (just ask the ants).
(1) Papert, S. (1980). Mindstorms: Children, Computers, and Powerful Ideas. New York: Basic Books
(2) Watt, S. (1998). Syntonicity and the psychology of programming – Psychology of Programming Interest Group 10th Annual Workshop.