Danny Wilf-Townsend

@dannywt.bsky.social

Associate Professor of Law at Georgetown Law, currently visiting at Yale Law. Working on civil procedure, consumer protection, and AI. Blog: https://www.wilftownsend.net/ Academic papers: https://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=2491047

Very happy to see this study finally made available publicly. 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.

Ethan Mollick@emollick.bsky.social · 4mo ago

Apparently superhuman performance from the AI in answering questions about contract law in this paper, as judged by law professors compared to the answers of their peers -Gemini 2.5 had a 75% win rate vs. professors -Gemini's answers were rated LESS harmful than humans -Newer models do even better

This is tangential, but I wonder how the idea / expression distinction will hold up over time with generated AI. Expressing an idea used to be costly, typically taking effort and often some creativity. What happens when ideas serve as prompts and expression is cheap or free, and easily iterated?

404 Media@404media.co · 6mo ago

Malus, which is a piece of satire but also fully functional, performs a "clean room" clone of open source software, meaning users could then sell software without crediting the original developers.

New post up about what I think is an under-discussed problem: the low visibility that we collectively have into responsible AI use by legal professionals. We have lots of data points about hallucinations, but many fewer public discussions of responsible uses, even though ...

A periodic update about the frequency and intensity of AI use in legal practice: Thomson Reuters reports that 55% of generative AI users at law firms use it at least daily, with 30% multiple times a day:

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I have a new post out in @lawfaremedia.org today about continual learning, the goal of many AI developers to build tools that can learn from their users. That technology could have many uses, but also will challenge existing ways we are trying to regulate AI. www.lawfaremedia.org/article/when...

When AI Models Can Continually Learn, Will Our Regulations Be Able to Keep Up?

Regulation has already been hard enough for static AI models.

lawfaremedia.org

I have a new post out in @lawfaremedia.org today about continual learning, the goal of many AI developers to build tools that can learn from their users. That technology could have many uses, but also will challenge existing ways we are trying to regulate AI. www.lawfaremedia.org/article/when...

When AI Models Can Continually Learn, Will Our Regulations Be Able to Keep Up?

Regulation has already been hard enough for static AI models.

lawfaremedia.org

A thoughtful thread on the Netflix / Warner Bros merger. I think the points about consumer preferences are particularly important — it’s sometimes hard, but often important, to tease apart when law and policy arguments are inflected by different preferences about product features

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An update for Sonnet 4.5, released last week: it scored 60.2% on my final exam (with extended thinking on, 54.4% without it). That's a big step up (~20 percentage points) from Opus 4.1's scores, and puts Sonnet 4.5 close to, if slightly behind, other lead models. On a human curve, that's ~ an A-/B+

Danny Wilf-Townsend@dannywt.bsky.social · last yr.

For my latest round of informal tests of large language models, I looked at how good different models are at taking a law school exam—and also whether they are capable of grading exam answers in a consistent and reasonably accurate way. 🧵 www.wilftownsend.net/p/chatgpt-ta...

One other note: across the five exam answers and dozens of answer evaluations generated here, I did not notice a single hallucination. This test wasn't designed to measure hallucination rates, but it's consistent with the general sense that they have dropped significantly

Danny Wilf-Townsend@dannywt.bsky.social · last yr.

For my latest round of informal tests of large language models, I looked at how good different models are at taking a law school exam—and also whether they are capable of grading exam answers in a consistent and reasonably accurate way. 🧵 www.wilftownsend.net/p/chatgpt-ta...

A nice quick read from my colleague @JonahPerlin about an issue that I see a lot of people oversimplifying: whether an attorney's use of a generative AI tool waives privilege. This is an area where I'm very interested to see how the law develops. news.bloomberglaw.com/us-law-week/...

No, Generative AI Didn’t Just Kill the Attorney-Client Privilege

Opinion: Georgetown Law professor Jonah Perlin says using third-party technology doesn't categorically waive the attorney-client privilege.

news.bloomberglaw.com

A very pleasant surprise to listen to one of my favorite podcasts and hear my own work being discussed. And it's an excellent episode and overview for anyone thinking of AI's effects on the legal profession. Some thoughts / suggestions below for anyone who wants further reading:

Joe Weisenthal@weisenthal.bsky.social · last yr.

NEW ODD LOTS: We talked to the legend @wertwhile.bsky.social about how AI is already reshaping the practice of law. A must listen, with out friend Joel podcasts.apple.com/us/podcast/w...

Judge Alsup has the first true opinion on fair use for generative AI in Bartz v. Anthropic. He holds that AI training is fair use, and so is buying books to scan them, but that downloading pirated copies of books for an internal training-data database is not fair use. 🧵

Eriq Gardner@eriqgardner.bsky.social · last yr.

🚨BREAKING: Federal judge concludes that using copyrighted works to train generative A.I. is transformative and ultimately a fair use. (Nevertheless, Anthropic can’t beat the lawsuit because it pirated books for another purpose too.) First of kind ruling. www.documentcloud.org/documents/25...