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4 months ago
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Back when I started programming, project teams were large. Organizations had dozens of programmers on sprawling projects. Reusing code was not trivial. Sharing code required real effort. Sometimes you had to hand over a disk or recopy code from a printout.
Better networking eased code reuse. Open source took over. We no longer have someone writing a red-black tree from scratch each time we need one.
What happened to those writing red-black trees when you could just download one from the internet?
They moved on to other work.
Generative AI (Copilot and friends) is basically just that: easier code reuse. If you’re trying to solve a problem that 20 engineers have solved and posted online, AI will solve it for you.
What happens to you? You move on to other, better things.
Software is supposed to be R&D. You’re supposed to solve problems no one has quite solved before.
But aren’t people predicting mass unemployment due to AI?
I suggest not making claims about the future without looking at hard data first The unemployment rate in Canada is relatively high right now, but historical data shows no ChatGPT discontinuity (before 2022, after 2022).
Maybe unemployment due to AI will hit computer science graduates hardest? Compared to what? Biology or business graduates? Where’s the data? Whether you should go to college at all is another question, but if you recommend opting out of computer science while still going to college, please provide the ChatGPT-safe alternative.
Can anyone become a programmer today? Let’s look at what happens on campus. Over 90% of students use AI for coursework. I estimate the percentage is higher in computer science. Let’s say all computer science students use AI.
A couple of years ago, I added a chatbot to my intro-to-programming class (now using RAG + GPT-4). With over 300 students a year, it’s a good test case.
I have grade data, and there’s no visible before/after ChatGPT effect. Last term, the failure rate was about the same as five years ago.
I don’t have data from other universities, but I haven’t heard anyone complain that students breeze through programming classes. This is despite AI being able to handle most assignments in an intro-to-computing course.
The challenge in an intro-to-programming class was never finding answers. Before ChatGPT, you could find solutions on Google or StackOverflow. Maybe it took longer, but it’s a quantitative difference, not a qualitative one, for elementary problems.
The skill you need to develop early on is reading code and instantly understanding it. If you’re a programmer, you might forget you have this skill. ChatGPT can give you code, but can your brain process it?
If you give Donald Trump ChatGPT, he still won’t code your web app. He’ll get code but won’t understand it.
More broadly, OECD economists predict worker productivity could grow by up to 0.9% per year thanks to AI over the next ten years. I’m not sure I trust economists to predict a decade ahead, but I trust they’ve studied recent trends carefully. And economist will tell you that a 0.9% rise in worker productivity per year is not at all a break from historical trends.
In fact, by historical standards, productivity growth is low. We are not at all in a technological surge like our grand-parents who lived through the electrification of their country. Going from no refrigerator to a refrigerator and a TV, that’s a drastic change. Going from Google to ChatGPT is nothing extraordinary.
Can generative AI bring about more drastic changes? Maybe. I hope so. But we don’t have hard evidence right now that it does.
