While this question may seem logical at face value, anyone with coding experience would assert that coding knowledge will remain a valuable skill for years to come.
They might even retort, “Why bother teaching English if ChatGPT can write an essay?”
It’s true. Anyone can write a fairly decent essay on any subject using ChatGPT and be reasonably sure that the spelling, grammar, and subject matter will be mostly acceptable. However, if you’ve ever used ChatGPT to perform such a task, you probably recognized that it was just that… “mostly acceptable.” The essay still needed to be tweaked and fact-checked by a human who understood the full picture, and that human needed to understand the grammar they learned in English class.
Did they stop teaching multiplication when the calculator was invented?
Should we stop teaching Music now that AI can write and produce music in the style of any composer you feed it?
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These questions sound ridiculous to most people. Of COURSE, you still have to teach English, Math, and Music. However, some are of the opinion that it’s now useless to learn to code because AI (Which is itself written in code) can write code with a fair amount of competency. The only people you’ll never hear that opinion from are software engineers and web developers – coders.
AI – The Great Productivity Tool
Artificial intelligence is a wonderful productivity tool. But just as you have to understand English grammar to take a block of AI-generated text and edit it to suit your purposes most effectively, you would also need to understand code to have AI help you construct functional code.
Here’s a good example:
We recently used AI to help build a table in HTML to display a cost breakdown for what it takes to open a new iCode Franchise.
We described our desired functionality to the AI and provided it with the values we wanted to display. In return, we received about 380 lines of code that looked … just OK.
Now, without an understanding of HTML or CSS, we wouldn’t have known where to go from there. However, with an understanding of these languages, we could see how it laid out, what the problems were, and how to fix it. We took the foundation provided by AI and reduced it from 380 lines of code to 167 lines and added some CSS to the style sheets that defined a new type of table which allowed for a cleaner, more dynamic look with hover shading on the lines so that it felt more interactive.
Writing that table from scratch would have been an extremely time-consuming and soul-crushingly boring task, which is why we fed it to the AI in the first place. Polishing what the AI gave us allowed us to end up with a result we were happy with, and we wouldn’t have gotten there without understanding what the AI wrote.
Engineering Isn’t Just About Writing
Finally, let’s talk about engineering. Engineering involves applying principles from natural science, mathematics, and the engineering design process to tackle technical problems, enhance efficiency, increase productivity, and improve systems. This extends to software engineering, where the focus is on designing, developing, and maintaining software systems to achieve similar objectives in the digital realm.
There are hundreds of jobs that require knowledge of one or more types of coding, many of them in engineering. As AI continues to improve, it will continue to be an outstanding productivity tool for coders building repetitive code blocks. But people doing these jobs will always need to know what the code means, how it works, and how different puzzle pieces can work together to achieve the desired result.
The point of engineering isn’t just knowing how each part functions and what it does. It’s the ability to understand those pieces well enough to put them together to create something new.
Including new AI’s.
