Beth Plale

join me at @bplale.bsky.social

Year 3 Site Visit successfully completed !! Excellent presentations, demo & posters by ICICLE NextGens showcasing Software/CyberInfrastructure components icicle.osu.edu/cyberinfrastru… Year 3, the year to “Innovate, Integrate, and Generalize on the path to Global scale!”

After trying to explain research to new grad students yesterday, this brief article rings true

A leading light of the information-library community guides a bit longer .

Great setting at the #BeilstrinBozen2024 Symposium with many exciting talks, engaged discussions and more perspectives on AI in Chemistry and Biology: Evolution or Revolution? @dipizio_lab @ferruz_noelia @bplale @restrepog @CDDLeiden @csteinbeck @G_Cuniberti

Can't do it anymore. X is for someone else. See me on 🧵🧵🧵@bethplale.

@ednewtonrex Thank you for taking a stand. AI companies' claim to fair use is highly unfair to creators

I’ve resigned from my role leading the Audio team at Stability AI, because I don’t agree with the company’s opinion that training generative AI models on copyrighted works is ‘fair use’. First off, I want to say that there are lots of people at Stability who are deeply thoughtful about these issues. I’m proud that we were able to launch a state-of-the-art AI music generation product trained on licensed training data, sharing the revenue from the model with rights-holders. I’m grateful to my many colleagues who worked on this with me and who supported our team, and particularly to Emad for giving us the opportunity to build and ship it. I’m thankful for my time at Stability, and in many ways I think they take a more nuanced view on this topic than some of their competitors. But, despite this, I wasn’t able to change the prevailing opinion on fair use at the company. This was made clear when the US Copyright Office recently invited public comments on generative AI and copyright, and Stability was one of many AI companies to respond. Stability’s 23-page submission included this on its opening page: “We believe that Al development is an acceptable, transformative, and socially-beneficial use of existing content that is protected by fair use”. For those unfamiliar with ‘fair use’, this claims that training an AI model on copyrighted works doesn’t infringe the copyright in those works, so it can be done without permission, and without payment. This is a position that is fairly standard across many of the large generative AI companies, and other big tech companies building these models — it’s far from a view that is unique to Stability. But it’s a position I disagree with. I disagree because one of the factors affecting whether the act of copying is fair use, according to Congress, is “the effect of the use upon the potential market for or value of the copyrighted work”. Today’s generative AI models can clearly be used to create works that compete with the copyrighted works they are trained on. So I don’t see how using copyrighted works to train generative AI models of this nature can be considered fair use. But setting aside the fair use argument for a moment — since ‘fair use’ wasn’t designed with generative AI in mind — training generative AI models in this way is, to me, wrong. Companies worth billions of dollars are, without permission, training generative AI models on creators’ works, which are then being used to create new content that in many cases can compete with the original works. I don’t see how this can be acceptable in a society that has set up the economics of the creative arts such that creators rely on copyright. To be clear, I’m a supporter of generative AI. It will have many benefits — that’s why I’ve worked on it for 13 years. But I can only support generative AI that doesn’t exploit creators by training models — which may replace them — on their work without permission. I’m sure I’m not the only person inside these generative AI companies who doesn’t think the claim of ‘fair use’ is fair to creators. I hope others will speak up, either internally or in public, so that companies realise that exploiting creators can’t be the long-term solution in generative AI.

This is intelligent systems engineering!

Arxiv plays a critical role in science dissemination. Glad to see this award to continue good work.

Why, of course.

The day rises on the CENTRA6 meeting. Thanks to all who have traveled into Indy for AI edge-cloud-hpc continuum discussions. #centra #iub #luddyai #icicle

📢 Researchers, Scientists, & Students at US Minority Serving Institutions! The @OpenResearchFG Seed Awards Program🌱is geared to stimulate & reward #OpenScience #OpenData #OpenScholarship at MSIs. Join our webinar 8/18 @ 1 pm ET to learn more! Register: shorturl.at/bhpyA

Dr. Beth Plale @IUBloomington talks about #Trustworthy #AI at the ConvoHPC workshop @PEARC_Conf

An opening for conversations on topics of anxiety and depression in science academia.

Brief history of #PID work within @resdatall. Great context as @RDA_US works with @OpenResearchFG and others on developing a PID strategy for the US. Learn more here: docs.google.com/document/d/1Ke…

Brilliant colleagues contribute to an energetic kickoff of @RDA_US 2.0!

Next phase for @RDA_US - positioning itself to direct support US open science efforts. @bplale

Congrats to IU alum and visionary @thoefler on yet another award. A duty to help data scientists succeed with their tools bs using HPC tools is a perspective that is on point.

People want to pursue #STEM possibilities where they live. Read my op-ed in @ScienceMagazine on how @NSF is trying to meet people where they are by building realistic paths locally for them to enter the STEM workforce: science.org/doi/10.1126/sc…