The Most Precise Word in the Dictionary
One of the ideas behind my writing course is that for every classic writing form—the sentence, the citation, the argument, the resume—there is a counterpart on the Web that holds the same qualities yet is more dynamic and advanced simply because it is online and accessible to the collective minds of the world.
A Tweet is an improved sentence because it has set limits—it can’t run on and forces clarity. It’s published—it’s not hidden away in a diary. It’s categorized—search engines and hashtags help readers find the sentences they want to read. And it’s critiqued—each compact thought either inspires a conversation or not.
I’ve found interactive complements to each aspect of the writing process, which is really the thinking process. My most controversial one, at least among my students, is my comparison of longform writing, and specifically the logical essay, with the algorithm.
Oxford defines an algorithm as “a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer.” An algorithm is a special case among word definitions because it has a formal definition among scientists who want to make it even more formal.
The precision of the definition is the goal.
During the Industrial Revolution, humans began their quest to replicate manual labor with machines. In 1936, mathematician Alan Turing made a tremendous leap in applying machines to mental labor or thought. He described a machine that could reproduce any decision-making process by breaking it down into a series of symbols and instructions.
What we first called hypothetical “Turing Machines,” we now call computers. We now have instructions or “software applications” that guide us through all kinds of decisions and behaviors.
Turing was also famous for describing the hypothetical “Turing Test.” If a machine could pass the Turing Test, then its software could replicate human thought and consciousness. It would mean humanity had successfully turned a robot into a real boy.
Our ability to do this, to replicate consciousness, is an active scientific question and challenge. It’s more active than it’s ever been before. Different brilliant people will tell you we are on the cusp or that it will never, ever happen. Thus, we don’t know if we can break down human decision and human awareness into 1s and 0s, math, or biology. Human consciousness is still a mystery.
Whether or not scientists can define an algorithm precisely is the source of a whole lot of problems.
Which is why the algorithm is such a wonderful and inspiring metaphor for the textbook word problem, the nonfiction essay, and even the novel. A word problem can reduce words to math. A nonfiction essay hopes to tell a logical, objective story or make a logical, objective argument. A novel just tries to grasp the human condition and all its variables in a limited number of pages.
The gap between our complicated, tragicomic lives and better decisions is what all art, science, and study are about.
In language itself, there are two ways of understanding grammar. Prescriptive linguists believe in firm definitions and that grammar is a set of rules—or an algorithm—to follow. Descriptive linguists believe grammar and definitions are more fluid and evolve in daily conversation.
I’m certainly more descriptive in philosophy. I love how the Web creates neologisms and new word uses and mashed up portmanteaus and metaphors around the clock. The Web reinforces the descriptive because it allows us to observe how words and phrases change in real time, but it also produces new prescriptive communication platforms and applications whose rules we must learn at a faster rate.
By using the algorithm as a metaphor for any effective method, set of instructions, or logical argument in my class, I have muddied the waters a bit. Yet scientists use algorithm informally to mean procedure or recipe too, while the culture has stretched the term to mean anything from medical diagnosis to the dating game.
I apologize to all the mathematicians, IT departments, and Turing fans, but as long as they insist they can teach a machine to write like Shakespeare, I will use their precise word to remind everyone how much of our world is still unquantifiable and incomputable.