New paper alert: We (w/ @ichbinsnicht, @samjboysel, Sida Peng, Kevin Xu) just released the working paper version of our study “Generative AI and the Nature of Work” - https://t.co/wgFFbD8k1e. We seek to build upon research on #AI and productivity to better understand how #GenAI

Why do consumers go with closed models when open options are often more powerful and less expensive? @frank_nagle points out people often think they can't use "open" models because the world would know their data - which is exactly backwards as open models can be run entirely

$8.8 trillion. That’s the estimated economic value of open source software, according to a new report commissioned by the @linuxfoundation and presented at #OSSummit by @HarvardHBS’s @frank_nagle #OpenSource #WordPress

Tune into #OpenSourceSummit now! 🚨 #theCUBE’s @pnashawaty speaks with @frank_nagle about how @LinuxFoundation aims to understand and extract maximum value out of #opensourceAI. 📺 Stream NOW! https://t.co/2GCskq5iE8 #OpenSource #AI #BusinessValue #EnterpriseTechNews

@Mylovanov Congrats @ichbinsnicht @frank_nagle and coauthors on an interesting work!

looking forward to @frank_nagle and his impact at the LF :)

We're thrilled to welcome Frank Nagle to the Linux Foundation as Advising Chief Economist! His invaluable expertise and leadership will help quantify the economic and societal impact of open source in the AI era and support sustainable growth across the open source ecosystem.

Here’s a Google notebooklm podcast of the @HarvardHBS paper “The Value of Open Source” by @ichbinsnicht @frank_nagle & Yanuo Zhou

AI is often framed as a force that will replace jobs. But a recent report from @HarvardHBS professor @frank_nagle and coauthors suggests it could be a tool that enables employees to craft more meaningful careers—if they know how to harness it. Combining these findings with the

You can find an interview about our working paper "Generative AI and the Nature of Work" on the GitHub blog. Thanks, Kevin for the great interview! Working paper: https://t.co/fzuXZD77o8 GitHub blog post:

1/ Open source AI is crucial for driving healthy competition, ensuring real transparency and accountability, expanding access, and—ultimately—keeping us all safe. 🤖

Hey #EconTwitter, I'm on the job market with a paper about open source software. OSS is a global public good, widely used and provided by the private sector, but the target of recent industrial policy. Paper: https://t.co/m7O3ul9DRj 1/

At a recent lab meeting, Frank Nagle (@frank_nagle) presented his paper 'Generative AI and the Nature of Work': "We seek to build upon research on #AI and productivity to better understand how #GenAI changes how people do work. We look at how the release of a GenAI coding tool

Found this SUPER cool study on the effect of CoPilot over millions of uses from @frank_nagle @ichbinsnicht team. Findings show people are exploring more thanks to CoPilot, like using diff programming languages😀 Exciting to see impact of AI increasing human exploration!!

Today's #1 read. @frank_nagle, look at you, a scholar of task performance now? Anyway, this looks fascinating. Will dig in shortly.

Fascinating and important work by @frank_nagle @samjboysel and coauthors

(this would likely diminish in the long run). Though our empirical setting is open source software #OSS, we argue, and find evidence, that the results generalize to private work settings as well. Many thanks to @github , @Microsoft , and @D3Harvard for their support of this work!

Further we find the effects are greater for workers with lower ability. Finally, we do a back-of-the-envelope calculation and show that using GenAI allows developers to start coding in languages that have higher wages, leading to a labor market value impact of nearly $500 million

tasks. We show two mechanisms drive this effect - workers with GenAI allocate more of their work efforts to things they can do by themselves (and less to collaborative work) and also do more exploration (new projects, new languages, etc) and less exploitation (existing projects).

changes how people do work. We look at how the release of a GenAI coding tool (@github Copilot) changed how developers allocate their efforts to different types of tasks. We find that GenAI leads workers to spend more time on core work activities and less time on managerial