Generative coding tools promise big productivity gains, but uneven uptake could widen skill and income gaps. We train a neural classifier to spot AI-generated Python functions in over 30 million GitHub commits by 170,000 developers, tracking how fast -- and where -- these tools take hold. Today, AI writes an estimated 29% of Python functions in the US, a modest and shrinking lead over other countries. We estimate that quarterly output, measured in online code contributions, has increased by 3.6% because of this. Our evidence suggests that programmers using AI may also more readily expand into new domains of software development. However, experienced programmers capture nearly all of these productivity and exploration gains, widening rather than closing the skill gap.

翻译：生成式编程工具有望带来巨大的生产力提升，但采用不均可能加剧技能与收入差距。我们训练了一个神经分类器，用于识别来自17万名开发者在GitHub上超过3000万次提交中由AI生成的Python函数，追踪这些工具的普及速度与地域分布。目前，美国约有29%的Python函数由AI编写，这一领先优势相对有限且正在缩小。我们估计，由于AI的应用，以在线代码贡献衡量的季度产出增长了3.6%。证据表明，使用AI的程序员可能更易于拓展至软件开发的新领域。然而，经验丰富的程序员几乎独占了这些生产力和探索性收益，反而扩大了而非弥合了技能差距。