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A. Feder Cooper @afedercooper.bsky.social · 13d

This is a really great community of researchers, and every accepted paper gets a generously long talk slot to present.

CFP: computersciencelaw.org/2026-2/2026-...

Main track deadline (archival and non-archival): September 30, AoE

2026-CFP - ACM Symposium on Computer Science & Law

2026 Call for Papers 5th ACM Symposium on Computer Science and Law March 3-5, 2026 Berkeley, California The 5th ACM…

computersciencelaw.org

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A. Feder Cooper @afedercooper.bsky.social · 13d

The NeurIPS position track didn't take a large number of extraordinary papers that surpassed the acceptance bar, limiting the acceptance rate to an unusually low 6%.

If you have a rejected paper at the intersection of ML and law, consider submitting to ACM CSLaw '26.

2026-CFP - ACM Symposium on Computer Science & Law

2026 Call for Papers 5th ACM Symposium on Computer Science and Law March 3-5, 2026 Berkeley, California The 5th ACM…

computersciencelaw.org

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Reposted by A. Feder Cooper

Mark Lemley @marklemley.bsky.social · 13d

Our paper "Machine Unlearning Doesn't Do What You Think" was accepted for presentation at NeurIPS

Congrats @afedercooper.bsky.social and @katherinelee.bsky.social, who led the effort

arxiv.org/abs/2412.06966

Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice

We articulate fundamental mismatches between technical methods for machine unlearning in Generative AI, and documented aspirations for broader impact that these methods could have for law and policy. ...

arxiv.org

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A. Feder Cooper @afedercooper.bsky.social · 15d

One more week to submit to CSLaw '26!!

A. Feder Cooper @afedercooper.bsky.social · 24d

15 days left to submit to the CSLaw '26 main track! (archival and non-archival)!

A. Feder Cooper @afedercooper.bsky.social · Aug 8

The CFP for ACM CSLaw '26 is up! Deadline for main-track papers (archival and non-archival) is September 30!

computersciencelaw.org/2026

A. Feder Cooper @afedercooper.bsky.social · 21d

at least 100k with all the appendices 🙃

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Reposted by A. Feder Cooper

Pamela Samuelson @pamelasamuelson.bsky.social · 23d

For an update on the state of play in the generative AI copyright cases, try this podcast: shows.acast.com/arbiters-of-...

AI Copyright Lawsuits with Pam Samuelson | Scaling Laws

shows.acast.com

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A. Feder Cooper @afedercooper.bsky.social · 24d

15 days left to submit to the CSLaw '26 main track! (archival and non-archival)!

A. Feder Cooper @afedercooper.bsky.social · Aug 8

The CFP for ACM CSLaw '26 is up! Deadline for main-track papers (archival and non-archival) is September 30!

computersciencelaw.org/2026

2026 - ACM Symposium on Computer Science & Law

CS&Law 2026 5th ACM Symposium on Computer Science and Law March 3–5, 2026 Berkeley, California Computing, software, and the Internet…

computersciencelaw.org

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Reposted by A. Feder Cooper

Elizabeth Lopatto @lopatto.bsky.social · 27d

did a little media criticism www.theverge.com/politics/777...

The WSJ carelessly spread anti-trans misinformation

The Wall Street Journal’s fuckup while covering Charlie Kirk’s killing needs more than an editor’s note.

www.theverge.com

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Reposted by A. Feder Cooper

mattie lubchansky @mattielubchansky.com · 27d

was just looking for @seantcollins.com’s “goofy at the crucification” post and google is so cool now

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A. Feder Cooper @afedercooper.bsky.social · 29d

Generative AI can be like a search engine, a website, a library, an author, or like any number of other things copyright has a well-developed framework for dealing with.

Prematurely accepting one of these analogies to the exclusion of the others would mean ignoring numerous relevant similarities

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A. Feder Cooper @afedercooper.bsky.social · 29d

5. Generative AI does not make the ordinary business of copyright law irrelevant:

Courts will still need to make plenty of old-fashioned, retail judgments about individual works.

6. Analogies can be misleading: Generative AI systems blur the boundaries between things that were formerly distinct.

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A. Feder Cooper @afedercooper.bsky.social · 29d

4. Fair use is not a silver bullet:

Generative AI scrambles past assumptions about ML and fair use. Some generations will infringe, and that could impact the fair use analysis at previous stages of the supply chain.

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A. Feder Cooper @afedercooper.bsky.social · 29d

3. Design choices matter:

Every actor in the generative-AI supply chain is in a position to make choices that affect their copyright exposure, and others'.

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A. Feder Cooper @afedercooper.bsky.social · 29d

2. Copyright concerns cannot be localized to a single link in the supply chain:

Decisions made by one actor can affect the copyright liability of another, potentially far away actor in the supply chain

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A. Feder Cooper @afedercooper.bsky.social · 29d

Part III provides broader lessons. They (and the piece in general) have held up really well, in spite of how fast this landscape is changing:

1. Copyright touches every part of the generative-AI supply chain:

Every stage from collecting training data to alignment can make use of copyrighted works

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A. Feder Cooper @afedercooper.bsky.social · 29d

Part I has the relevant background on ML, generative AI, and the complex, interconnected supply chain involved in the design, construction, deployment + use of generative-AI models & systems

Part II goes through the very many touch points between US copyright law and the generative-AI supply chain

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A. Feder Cooper @afedercooper.bsky.social · 29d

We worked really hard to make this piece accessible and useful to both copyright and ML experts, alike.

And we've been thrilled to hear over the last two years how our paper has helped teachers, journalists, and other interested readers better understand these issues.

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A. Feder Cooper @afedercooper.bsky.social · 29d

After 2 years in press, it's published!

"Talkin' 'Bout AI Generation: Copyright and the Generative-AI Supply Chain," is out in the 72nd volume of the Journal of the Copyright Society

copyrightsociety.org/journal-entr...

written with @katherinelee.bsky.social & @jtlg.bsky.social (2023)

TALKIN' 'BOUT AI GENERATION: COPYRIGHT AND THE GENERATIVE-AI SUPPLY CHAIN | The Copyright Society

We know copyright

copyrightsociety.org

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Reposted by A. Feder Cooper

James Grimmelmann @jtlg.bsky.social · Sep 5

The Bartz v. Anthropic settlement is the polar opposite of the Google Books settlement: a discrete one-time payment for past copying, on a discrete and closed-ended class, and making no attempt at all to deal with a larger forward-looking issues.

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A. Feder Cooper @afedercooper.bsky.social · Sep 2

not again…wrote a (really) long law review paper that started as a short response to some wildly inaccurate comments he made in a post about copyright and language models reproducing training data they’ve “memorized.” It’s 2 years later and that post still isn’t fully successfully debunked 🫠

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A. Feder Cooper @afedercooper.bsky.social · Aug 31

But it’s really expensive in others. E.g., NeurIPS ‘25 is slated to reject 300+ papers that ACs voted to accept bc of physical resource constraints. This is all bad for science, and will hit junior scholars the hardest.

(I also have no idea to responsibly recruit students in this ecosystem.)

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A. Feder Cooper @afedercooper.bsky.social · Aug 31

Also don’t think acceptance at these venues is a sign of quality anymore. Great, influential, unpublished arxiv paper seem to mean more. They’re dealing with the same slop + scale problems, without enough qualified reviewers. Drawing arbitrary lines is a “cheap” way to solve them in some sense.

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A. Feder Cooper @afedercooper.bsky.social · Aug 31

oh, not all of this evidence is ML experiments.

But I agree in general. I also don’t think I’d know how to solve this problem, but this particular line drawing seems like it could go not so great for some really good work (like @mariaa.bsky.social’s). It’ll be a wait and see.

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A. Feder Cooper @afedercooper.bsky.social · Aug 31

my current understanding @jacyanthis.bsky.social is this is targeting a new flavor of paper. A lot of good positions at ICML have supporting evidence. versions of these papers (even if not accepted) are arguably typical scientific papers (which often have positions), could go up as normal preprints?

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A. Feder Cooper @afedercooper.bsky.social · Aug 31

(Having done some work on this, I think this type of clean room practice isn’t actually super feasible in practice. Even if you get curation like this right—a huge if—I’m finding that these types of counterfactuals are really brittle in practice)

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