The Impact of AI on New Programmers

Introduction

Imagine starting to learn programming today. You’ve just installed your first development environment, maybe you’ve read a tutorial or two, but when you hit that first coding roadblock, you feel lost. Then, an AI assistant like GitHub Copilot or ChatGPT comes to your rescue, ready to suggest a solution. Sounds like a dream, right? In fact, AI is revolutionizing the way we learn to code. But like any new tool, it has its pros and cons. In this essay, we’ll explore how AI can help beginners with coding, the risks it presents, and the ethical implications that come with this new type of assistance. We’ll figure out whether AI is truly the ideal tutor, or if it hides some traps that we may not notice right away.

Benefits: A Tutor Always Available

For someone learning to program, AI is like having a tutor who never sleeps. GitHub Copilot, for example, is an assistant that integrates into your development environment and suggests code as you type. Does it sound too good to be true? It’s actually a great way to save time and reduce errors. Not sure how to declare a variable in JavaScript or which library to use for a function? Copilot will immediately give you a practical example. This lets you focus on the concepts, not on the small syntax details. It’s like having a guide on hand, always ready to help when you hit a problem. Plus, it helps you see alternative solutions to a problem you might not have considered.

Another advantage we can’t ignore is debugging. For a beginner, reading error messages can be frustrating. But with an AI assistant, you can simply ask, “What’s going wrong?” and get an immediate explanation. Instead of spending hours trying to figure out why your code doesn’t work, AI helps you pinpoint the problem, sometimes even before you realize it. That way, you not only save time but also learn how to approach errors more efficiently.

Also, AI helps you get into the flow more quickly. When you’re first learning programming, it can be hard to focus on complex concepts like loops or functions. But tools like ChatGPT can explain these concepts in a simple way, using analogies that make you instantly understand what’s going on. Imagine asking “What’s a for loop?” and getting an answer with a practical example in a language you understand, without having to scroll through page after page of documentation.

Risks: Too Much Help Isn’t Always Good

On the flip side, there’s the risk of becoming overly dependent on AI. It’s easy to rely on and accept every suggestion AI gives you, but this can slow down your learning process. If every time you run into a problem, you turn to the AI without trying to solve it yourself, you’ll miss out on truly understanding what you’re doing. It’s like having a friend do your homework for you all the time—eventually, you never learn how to do the work on your own.

Imagine learning to program without knowing all the fundamentals yet. AI gives you a suggestion to complete a function, but you don’t fully understand why that solution is correct. You end up copying it without asking why, and the next time you face a similar problem, you won’t know how to tackle it on your own. This is the risk of not developing real skills: AI provides the answer, but it doesn’t teach you to think like a programmer.

Another risk is that too frequent use of AI tools might lead you to write incorrect or inefficient code without realizing it. AI, like any tool, isn’t flawless. Sometimes it might suggest a solution that looks correct but isn’t optimal. If you don’t have the knowledge to verify or improve it, you’ll end up adopting it without realizing that better methods exist.

Ethical Implications: What Happens to Merit?

Then there’s the question of merit. If a beginner relies too much on AI to complete their code, how can we measure their actual progress? In an academic setting, using AI too often could raise doubts about how much someone really understands. It’s like a student copying homework from the internet without putting in the effort to learn. So there’s an issue of authenticity: who’s writing the code—the AI or the programmer? And how do we distinguish between code written entirely by a person and code written with the help of artificial intelligence?

These questions are particularly relevant in the workplace, where programmers are evaluated based on their skills. If a developer uses AI tools to quickly complete a task, how do we assess the quality of their work? If someone writes code quickly thanks to AI, but doesn’t know how to solve problems without it, they might end up being evaluated for skills they haven’t actually developed. And this brings up another ethical issue: is it fair for beginners to use AI tools without proper evaluation of their actual skills?

AI-Powered Tools: Which Ones to Use?

Let’s take a look at some of the most popular tools that assist programmers. GitHub Copilot, as mentioned, is one of the most well-known. It easily integrates into code editors like VS Code and suggests completions, functions, and solutions to problems in real time. While not perfect, it’s a great tool to speed up coding and learn new solutions faster. Another useful tool is ChatGPT, which can explain complex concepts, help you understand syntax errors, and even suggest changes to your code. It’s more like a “tutor” who’s ready to answer any question about programming, breaking things down step by step.

Another interesting tool is Tabnine, which offers an autocomplete feature similar to Copilot, but with a special focus on privacy. It allows you to run the AI engine locally, meaning your code is never sent to external servers, which can be important for those working on sensitive projects.

So, choosing a tool depends a lot on personal needs. Each AI assistant has its strengths and might be more suited to specific languages or types of projects. If you’re a beginner, I’d recommend trying out different tools and seeing which one helps you the most, but never losing sight of the importance of continuing to think like a programmer.

Conclusion

AI is changing the way we learn programming, offering numerous benefits—from helping with immediate difficulties, to speeding up code completion. But, like every tool, it should be used with care. It’s important not to let AI do all the thinking for you, but rather to continue learning through hands-on experience. AI can accelerate the process, but it shouldn’t replace the reasoning that’s fundamental to becoming a good programmer.

Over time, we’ll likely see more discussions about the ethics of using AI, especially in academic and professional settings. But for now, if used properly, AI can really make a difference, helping those just starting out navigate a journey that would otherwise seem overwhelming. The key is in the balance: use AI as a support, but not as a substitute for your effort and creativity. The future of programming might be more collaborative than ever, with AI as a co-pilot while the programmer stays in the driver’s seat.

Written by Ismail Nasry