The Huge Power and Potential Danger of AI-Generated Code

Will Knight - WIRED Magazine
GitHub's report on AI coding assistant Copilot reveals that users accepted the AI's suggestions about 30% of the time, indicating its ability to predict useful code. AI-enhanced coders saw productivity increase over time, with the greatest gains observed among less experienced developers. However, a study by Stanford University found that programmers using code-generating AI assistants tended to include more bugs in their final code, leading to concerns about overreliance on automation and potential issues in AI-generated code. Regulators and lawmakers should consider the subtler impacts of AI deployments on software quality.

Summary: GitHub’s report on AI coding assistant Copilot reveals that users accepted the AI’s suggestions about 30% of the time, indicating its ability to predict useful code. AI-enhanced coders saw productivity increase over time, with the greatest gains observed among less experienced developers. However, a study by Stanford University found that programmers using code-generating AI assistants tended to include more bugs in their final code, leading to concerns about overreliance on automation and potential issues in AI-generated code. Regulators and lawmakers should consider the subtler impacts of AI deployments on software quality.

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