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Learn To Code, Learn To Think


Is learning to code software a valuable skill? Is it one that prepares people to join the workforce of the future?

On the one hand, the popularity of computer science as a college major and the proliferation of coding bootcamps suggest the answer is decidedly "yes." Code.org, a non-profit that encourages education and diversity in computer science, currently invites visitors to its homepage to join over a million others in agreeing with the following statement:

"Every student in every school should have the opportunity to learn computer science"

On the other hand, some endorse the headline on Kevin Maney's May 29th article at Newsweek: "Computer Programming Is A Dying Art," one that will soon be taken over by smarter, more "brain-like" computers. So, perhaps the answer as to whether you should learn to code is "don't bother." In fact, Kevin Maney ends his article with the following prediction:

" ... in 2030, when today's 10-year-olds are in the job market, they'll need to be creative, problem-solving design thinkers who can teach a machine how to do things. Most of them will find that coding skills are about as valuable as cursive handwriting."

Maney's timeline may be optimistic but the prospect isn't crazy. Gary Marcus and Ernest Davis, cognitive and computer scientists blogging for The New Yorker, identify what they see as "fundamental obstacles" (but not insurmountable obstacles) to self-coding computers. These include the fact that computers are still far from achieving human levels of language comprehension or of general real-world knowledge — both longstanding and deeply challenging problems in AI.

But there's another reason to learn to code, whether or not self-coding computers are on the horizon. And it's this: learning to code is a good way to learn to think.

Some of the very properties of computer languages that can be cumbersome and difficult to master — such as the need to specify everything explicitly, to consider exceptions, to understand recursion and to think through downstream consequences — are among the most valuable for thinking. It's precisely because human thinking is so often underspecified, and human language so often ambiguous, that designing computers that can code from human instruction is such a hard problem for AI. But it's also why learning a formal, expressive language is so valuable for human minds.

In his article, Maney writes:

"In the end, far more people will be able to program without knowing code. They'll just need good higher-level design thinking so they can clearly, logically explain the computer's task."

It may be that learning to code is the best way to develop those very thinking skills.

Programming languages come and go. And it doesn't much matter whether most people master the subtleties of semicolon use in Python versus C. But the basic abilities to think a problem through carefully, clearly and thoroughly are essential for just about all people in just about all fields.

The analogy to cursive handwriting turns out to be an instructive one, though perhaps not for the reasons intended. New research, summarized in a June 2nd article by Maria Konnikova at The New York Times, suggests that the process of learning to write cursive may itself be important for learning to read, to write and, perhaps, even to generate ideas — no matter that the resulting ability is often replaced by a keyboard and decent typing proficiency.

Similarly, it may be that programming is a skill that makes us the kinds of thinkers that we need to be, even if we ultimately have the option of outsourcing our coding to clever machines.

You can keep up with more of what Tania Lombrozo is thinking on Twitter: @TaniaLombrozo

Copyright 2021 NPR. To see more, visit https://www.npr.org.

Tania Lombrozo is a contributor to the NPR blog 13.7: Cosmos & Culture. She is a professor of psychology at the University of California, Berkeley, as well as an affiliate of the Department of Philosophy and a member of the Institute for Cognitive and Brain Sciences. Lombrozo directs the Concepts and Cognition Lab, where she and her students study aspects of human cognition at the intersection of philosophy and psychology, including the drive to explain and its relationship to understanding, various aspects of causal and moral reasoning and all kinds of learning.

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