Associate Professor of Law @GeorgetownLaw, thinking, writing, and teaching about artificial intelligence, consumer protection, and procedure.
Joined July 2009
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Danny Wilf-Townsend retweeted
Jun 13
Second, the lack of predictability here — evident from Anthropic's blog post — speaks to the total lack of AI policy capacity within the admin. I don't know if this is someone misunderstanding jailbreaking, or someone not trusting Anthropic, but in a functioning administration nobody would have ever been blindsided by an action like this; the government simply would've just requested that Anthropic do additional testing or add more safeguards before release.
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Jun 13
This seems very plausible to me—it has the potential makings of a case you could find in casebooks. But one big question will be: will this work its way through the courts slowly enough to actually yield some precedent, or will events overtake / moot the litigation?
Jun 13
This may become the first big First Amendment AI case.
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Jun 13
Something interesting to note is that, at least as of now, the New York Times’ coverage of this is 3/4 of the way down the page, far below, eg, the latest developments in Trump’s name on the Kennedy Center. Serious underrating.
Jun 13
Wow.... This is the most serious national security control of software I can recall. I cover some of the possible national security authorities in my paper The National Security Internet, just out from @GeorgetownLJ. law.georgetown.edu/georgetow…
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Danny Wilf-Townsend retweeted
Jun 12
Amazing opportunity for aspiring law professors. I wish this had existed when I was preparing for the academic job market.
We are pleased to announce the inaugural Law & AI Academic Fellowship.
The Law & AI Academic Fellowship is intended as an alternative to university-sponsored Visiting Assistant Professor or law fellow positions for legal scholars wishing to pursue a career in US legal academia.
Our goal is to prepare fellows for the US legal academic job market by providing them with the time and resources to produce high-quality, impactful academic research as part of a larger academic application package. Fellows should expect to spend the majority of the fellowship researching and writing articles for publication in law journals.
This is a full-time, two-year role. The salary for the position is $130,000 per year.
If you’re looking for a supportive place to explore a career at the cutting edge of AI, law, and academia, and build your skills under the mentorship of our network of researchers and affiliates, we encourage you to apply: law-ai.org/career/academic-f…
Applications close on July 31, 2026.
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Danny Wilf-Townsend retweeted
Jun 6
I look forward to reading the following risk factor in Anthropic's S-1:
"Our business depends on our ability to develop and deploy increasingly powerful AI models. In June 2026, we began studying how an international effort may be undertaken to pause further development of AI. There is a risk that we will be successful."
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Perhaps unsurprisingly, in my many conversations with law professors about AI over the last few months, this study is the one that I have found most consistently helps people update their worldview about AI capabilities.
Jun 2
Law professors wrote questions they were asked during office hours. Gemini 2.5 & humans answered them then other law professors blindly judged the results:
-Gemini had a 75% win rate vs. professors
-Gemini's answers were rated LESS harmful than humans
-Newer models do even better
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Finally -- I've been waiting for this paper to be made more broadly available. Answers blind-graded by experts is, I think, the most useful form of AI quality assessment, and this study really makes it clear how capable these tools are at answering legal questions.
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May 29
This news from Kirkland along with the Harvey legal agent benchmark this week raises a big question: will the next major improvements in legally useful AI come from law-specific model building, or from improvements in general-purpose foundation models? 🧵
Kirkland & Ellis, the world's highest-grossing law firm, is setting aside $500M to build its own AI platform rather than rely on tools available to its rivals (Financial Times)
(Visit Techmeme dot com for the link and full context!)
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May 29
But at this point my default bet would be that ChatGPT 6 or 7 (or whatever) will be better than Kirkland 1, just as o3, GPT 5 Pro, etc., are so much better than Lexis or Westlaw's AI products, both in terms of raw power and workflows.
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May 29
Obviously people at Kirkland will have thought about this all, too, and have their own reasons and evidence. I'll be curious to see how it plays out.
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May 28
It’s very interesting to me that they view this as a good idea
Kirkland & Ellis, the world's highest-grossing law firm, is setting aside $500M to build its own AI platform rather than rely on tools available to its rivals (Financial Times)
(Visit Techmeme dot com for the link and full context!)
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May 28
I definitely take this anonymous post with a grain of salt, but it’s a good reminder that a lot of what’s going on in courts with AI may not be very legible…
May 27
talked to a sitting state court clerk in NJ. here’s what he said.
I asked about AI hallucinations in briefs. he said judges are seeing them from reputable firms and mostly aren’t sanctioning unless the whole brief is BS. here’s the reason: NJ judges are nominated by the governor and can only get tenure after 7 years if they’re confirmed again by the governor and senate. that confirmation is informed by reviews of the judges written by lawyers who appeared before them. so judges don’t want to be known as hard asses.
on AI use in the courts: “AI is used by every clerk and judge in the NJ courts. NJ’s courts spent millions developing a proprietary internal AI which does nearly everything a judicial clerk does — it scans documents, finds caselaw, and can draft decisions.” not Harvey, not Legora. built in-house. they also give the judges access to LexisAI.
on his own workflow: “I don’t have any physical documents I just look up the docket number. I can download the PDFs and put them into the AI to tell me what’s relevant and then I’ll have AI do a first draft of an analysis and check the cases.”
I asked him if he’s just chilling compared to old school clerks. his quote: “I swear the only reason they still have judicial clerks is the deep clerking culture in Jersey.”
on the inflow of AI-drafted briefs from pro se litigants: “Pro se briefs are now like 10-20 pages of actual meritorious arguments. It’s wild.” historically pro se filings were thin and easily dismissed. now they’re being drafted with Claude and the clerks have to take the arguments seriously.
on the skill being built: he used to think his clerkship was about the intense writing experience. now he thinks the real skill is reading through AI-drafted work and finding the core arguments underneath — and every clerk is developing that skill in real time because of the volume.
I asked if AI is going to speed up the court process. his answer: “Jersey already has a relatively quick motion cycle (it’s literally every two weeks) so I think this will just let clerks get more work done in that two weeks so less stuff will get adjourned.”
makes me wonder if the courts are further along than law firms.
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Danny Wilf-Townsend retweeted
May 27
talked to a sitting state court clerk in NJ. here’s what he said.
I asked about AI hallucinations in briefs. he said judges are seeing them from reputable firms and mostly aren’t sanctioning unless the whole brief is BS. here’s the reason: NJ judges are nominated by the governor and can only get tenure after 7 years if they’re confirmed again by the governor and senate. that confirmation is informed by reviews of the judges written by lawyers who appeared before them. so judges don’t want to be known as hard asses.
on AI use in the courts: “AI is used by every clerk and judge in the NJ courts. NJ’s courts spent millions developing a proprietary internal AI which does nearly everything a judicial clerk does — it scans documents, finds caselaw, and can draft decisions.” not Harvey, not Legora. built in-house. they also give the judges access to LexisAI.
on his own workflow: “I don’t have any physical documents I just look up the docket number. I can download the PDFs and put them into the AI to tell me what’s relevant and then I’ll have AI do a first draft of an analysis and check the cases.”
I asked him if he’s just chilling compared to old school clerks. his quote: “I swear the only reason they still have judicial clerks is the deep clerking culture in Jersey.”
on the inflow of AI-drafted briefs from pro se litigants: “Pro se briefs are now like 10-20 pages of actual meritorious arguments. It’s wild.” historically pro se filings were thin and easily dismissed. now they’re being drafted with Claude and the clerks have to take the arguments seriously.
on the skill being built: he used to think his clerkship was about the intense writing experience. now he thinks the real skill is reading through AI-drafted work and finding the core arguments underneath — and every clerk is developing that skill in real time because of the volume.
I asked if AI is going to speed up the court process. his answer: “Jersey already has a relatively quick motion cycle (it’s literally every two weeks) so I think this will just let clerks get more work done in that two weeks so less stuff will get adjourned.”
makes me wonder if the courts are further along than law firms.
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May 27
I'm very much in favor of more and different legal benchmarks. But from what I can tell, this benchmark is graded by AI models as well. That has advantages of course, but without validating that kind of grading, that is a meaningful asterisk, and could limit hill climbing.
May 26
Don't read this as suggesting law poses any particular challenges to AI. Rather, the existence of a benchmark in which AI already scores in the mid-single digits suggests that rapid improvement and saturation are imminent. If you can measure, you can hill climb.
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May 27
I say "could" genuinely here—maybe an AI-graded benchmark will help. But there's also a risk that it's the cheap/easy way out in a domain where getting a good signal for model training is notoriously difficult.
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May 26
My working theory is that human writing has more information density, more perplexity, and more emotional range than AI writing, and people who are used to reading both recognize that intuitively, which leads to being turned off by the latter.
Why is it so repulsive/cringe when someone uses obvious AI writing? I feel this, but can't decide if it's a feeling I want to defend. 1/
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May 26
I think it also leads to feeling a bit cheated when you thought you were reading a human product and then realize it's AI. You were just expecting, reasonably, to get more for your time. (Note that all this might change with changing capabilities!).
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May 26
I should also caveat—not *all* human writing is better along those lines, of course. But a lot of it! Even just your everyday twitter back-and-forth has more of those features than your everyday AI output. And I say this as someone who uses AI often and finds it very valuable.
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