How AI Tools Like GitHub Copilot are Transforming the Way Coders Think

Will Knight

Many people—like, say, journalists—are understandably antsy about what generative artificial intelligence might mean for the future of their profession. It doesn’t help that expert prognostications on the matter offer a confusing cocktail of wide-eyed excitement, trenchant skepticism, and dystopian despair.

Some workers are already living in one potential version of the generative AI future, though: computer programmers.

“Developers have arrived in the age of AI,” says Thomas Dohmke, CEO of GitHub. “The only question is, how fast do you get on board? Or are you going to be stuck in the past, on the wrong side of the ‘productivity polarity’?”

In June 2021, GitHub introduced a preview version of a programming tool known as Copilot. This AI-driven tool assists users by suggesting extensive sections of code as they begin to type. Currently, Copilot is a paid tool and has gained significant popularity. Microsoft, the owner of GitHub, announced in their recent quarterly earnings report that the tool now boasts 1.3 million paid accounts, marking a 30% increase from the previous quarter. They also shared that the software is utilized by 50,000 different companies.

According to Dohmke, recent data reveals that nearly half of the code produced by users is generated by AI. However, he also points out that there is limited evidence to suggest that these AI programs can function without human involvement. He states, “There’s clear consensus from the developer community after using these tools that it needs to be a pair-programmer copilot.”

Dohmke articulates Copilot’s effectiveness in simplifying complexities for programmers working on a problem. He likens this ability to modern programming languages that conceal the intricate details that previous languages insisted coders to handle. Dohmke adds that younger programmers are particularly embracing Copilot, and it appears to be exceptionally beneficial in resolving beginner coding issues. He says, “We’re seeing the evolution of software development.”

However, this does not imply that the need for developers’ labor won’t be influenced by AI. GitHub’s research in collaboration with MIT demonstrates that Copilot enabled coders dealing with relatively straightforward tasks to complete their work roughly 55% faster on average. This productivity boost suggests that firms can accomplish the same work with fewer programmers. Nevertheless, the savings could be allocated to labor costs on other projects.

Even for non-coders, these findings—and the rapid uptake of Copilot—are potentially instructive. Microsoft is developing AI Copilots, as it calls them, designed to help write emails, craft spreadsheets, or analyze documents for its Office software. It even introduced a Copilot key to the latest Windows PCs, its first major keyboard button change in decades. Competitors like Google are building similar tools. GitHub’s success might be helping to drive this push to give everyone an AI workplace assistant.

“There’s good empirical evidence and data around the GitHub Copilot and the productivity stats around it,” Microsoft’s CEO, Satya Nadella, said on the company’s most recent earnings call. He added that he expects similar gains to be felt among users of Microsoft’s other Copilots. Microsoft has created a site where you can try its Copilot for Windows. I confess it isn’t clear to me how similar the tasks you might want to do on Windows are to the ones you do in GitHub Copilot, where you use code to achieve clear objectives.

There are other potential side effects of tools like GitHub Copilot besides job displacement. For example, increased reliance on automation might lead to more errors creeping into code. One recent study claimed to find evidence of such a trend—although Dohmke says that it reported only a general increase in mistakes since Copilot was introduced, not direct evidence that the AI helper was causing an increase in errors. While this is true, it seems fair to worry that less experienced coders might miss errors when relying on AI help, or that the overall quality of code might decrease thanks to autocomplete.

Given Copilot’s popularity, it won’t be long before we have more data on that question. Those of us who work in other jobs may soon find out whether we’re in for the same productivity gains as coders—and the corporate upheavals that come with them.

William Turton

Matt Burgess

Makena Kelly

Lauren Goode

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