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<rss version="2.0"><channel><title>Sida Peng · AI Fault Line</title><link>https://aifaultline.com/authors/sida-peng/</link><description>New papers by Sida Peng in the AI Fault Line guide, and news naming them.</description>
<item><title>Paper: The Effects of Generative AI on High Skilled Work: Evidence from Three Field Experiments with Software Developers</title><link>https://aifaultline.com/research/p/doi-10-2139-ssrn-4945566/</link><guid>https://aifaultline.com/research/p/doi-10-2139-ssrn-4945566/</guid><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><description>Reports on three separate field experiments (at Microsoft, Accenture, and a Fortune 100 firm) measuring how GitHub Copilot access affects software developers&#x27; output, finding sizable increases in completed tasks per week that are largest for less-experienced programmers. As one of the largest employer-scale randomized trials of a generative AI coding tool to date, it adds enterprise-level evidence to the debate over whether AI narrows or widens skill gaps among workers.</description></item>
<item><title>Paper: The Impact of AI on Developer Productivity: Evidence from GitHub Copilot</title><link>https://aifaultline.com/research/p/doi-10-48550-arxiv-2302-06590/</link><guid>https://aifaultline.com/research/p/doi-10-48550-arxiv-2302-06590/</guid><pubDate>Mon, 13 Feb 2023 00:00:00 +0000</pubDate><description>A controlled experiment with recruited developers building a JavaScript HTTP server found that those with GitHub Copilot access finished the task 55.8% faster than a control group without it, with especially strong effects for less experienced programmers. It remains one of the most-cited direct measurements of an AI coding assistant&#x27;s productivity effect and is frequently used as a benchmark figure in broader estimates of AI-driven productivity growth.</description></item>
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