Anyone who’s ever substantially coded before knows just how painstaking and time-consuming a project can often be, thanks to thousands of lines of programming and hours of tedious trial-and-error. A new program is aiming to ease that pain.
Created by GitHub in collaboration with Microsoft and OpenAI, Copilot is a new, collaborative artificial intelligence software able to make predictive suggestions and edits for programmers based on billions of publicly available lines of coding. “GitHub Copilot draws context from the code you’re working on, suggesting whole lines or entire functions,” GitHub CEO, Nat Friedman, explained in a blog post yesterday. “It helps you quickly discover alternative ways to solve problems, write tests, and explore new APIs without having to tediously tailor a search for answers on the internet.”
Given that Copilot is constantly learning from users’ inputs, it's probably not a long stretch to see AI like this becoming increasingly helpful to even the most complex coding projects.
Far from perfect — Coders don’t need to worry about programs like Github’s Copilot coming for their jobs anytime soon, though. According to Copilot’s FAQ, a recent, blanked-out benchmark coding test against a set of “Python functions that have good test coverage in open source repos” saw the model getting 43 percent of the answers right the first time around, and increasing to 57 percent within 10 attempts. “It’s getting smarter all the time,” promises GitHub, but it sounds like there’s still a long way to go before we can hand the reins entirely over to Copilot.
Decoding the biases — As it stands, an AI is only as good as its designers, and designers are human, after all (for now — see bad robot overlord jokes above for reference). Machine learning and artificial intelligence programs like facial recognition still pose a whole host of ethical and privacy concerns. An increasing number of people are working to address these issues (GitHub included), but projects like Copilot will still need to be closely monitored and critiqued to ensure the most equitable and helpful assistance possible.