Co-Director Vanderbilt AI Law Lab
Nashville, TN
Joined July 2009
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mark williams retweeted
[read about what’s happening with AI]
ME: Wow we’re actually legit fucked this is so bad.
[go outside]
ME: Wait those people are all acting like nothing unusual is happening. Maybe I was just in a paranoid bubble? Yeah it must be that. Phew.
[read more about what’s happening with AI]
ME: Wait no we ARE fucked. Shit. It’s all those people outside who are in a delusional bubble.
[go outside]
ME: Wait...
mark williams retweeted
Working with AI requires perpetually operating at the edge of sanity. You have to recalibrate your mental model of AI capabilities and your own job description every few months, without getting delusional about seemingly infinite productivity gains, or feeling threatened by losing what you thought was the uniquely human part of your job, or obsessing over the perfect setup, or losing your mind over the clumsiness and jaggedness of agents, or ...
Maybe AI literacy needs to be less about prompting and more about improving emotional regulation.
mark williams retweeted
At a conference on AI & legal profession. I'm sorry folks, but you are over-indexed on hallucinations. You aren't calibrated on the magnitude of the problem and it's possible that one reason is psychological. It's comforting to think that the robots will never be as accurate & diligent as we are.
*I am NOT saying that AI doesn't hallucinate or never makes mistakes; indeed, I believe that it does.
mark williams retweeted
From city councils to Congress, there’s a growing desire to tax AI, but policymakers don’t always know their options. My new paper outlines 34 ways to tax AI across data centers, chips, data, AI cos. & products, automation & general tax reforms. vanderbiltpolicyaccelerator.…
mark williams retweeted
New from @asad09, a menu of how to think about taxing AI -- a must read!
From city councils to Congress, there’s a growing desire to tax AI, but policymakers don’t always know their options. My new paper outlines 34 ways to tax AI across data centers, chips, data, AI cos. & products, automation & general tax reforms. vanderbiltpolicyaccelerator.…
mark williams retweeted
VAILL has announced several important updates for the school year, including the well-deserved promotion of Lecturer Emily Pavuluri to Associate Director.
Learn more about the GenAI bootcamps, industry partnerships, and student-facing initiatives here: ow.ly/13Ae50ZSmsI
mark williams retweeted
.@polynoamial on @dwarkesh_sp: I don't know what will happen in 3 months.
Legal academics: my article should be out by the end of 2027.
We've got to seriously reexamine how academics share their research...
mark williams retweeted
If lawyers don't define what the "practice of law" means as AI takes on more legal work, insurers will define it for them through underwriting requirements.
Professors @markjwill and @inspiredcat make the case via @BLaw
Read more: ow.ly/YERP50ZLCY5
mark williams retweeted
i've tried and failed to make this point as clearly as i want to, but:
AI is weird, in that ppl who are optimistic about the technology's growth are often doomy about its implications; while ppl who are extremely skeptical about AI's capabilities are by default optimistic about it being a "normal" technology that won't change much in the world.
so you have this weird situation where a lot of AI skeptics who haven't been following AI news for the last few years (bc they wrote the whole thing off as NFTs 2.0) have no idea that there exists an enormous contingent of AI ppl who have for 10+ years said that very fast AI progress could be really bad for the world, and therefore they suspect that a conspiracy was concocted in the last two weeks to invent the case for AI safety
mark williams retweeted
Teams during rivalry week:
- Ohio State: We don’t give a damn for the whole state of Michigan
- Alabama: Go East until you smell it, go South until you step in it
- Kansas: John Brown did nothing wrong. 260,000 dead confederates was not enough.
mark williams retweeted
I can't believe they were saying the law firm of Wachtell, Lipton, Rosen & Katz was washed
mark williams retweeted
A thing to remember about AI-generated LinkedIn slop is many of those people (marketing people, corporate division chiefs, comms and PR professionals) are objectively among the most educated and literate people to have ever walked the face of the earth.
mark williams retweeted
New paper: every law in America is technically public. But not really, until now!
With @DenisPeskoff at UC Berkeley, we built a corpus of ~every publicly accessibly city and county law, and released a huge chunk of it!
2.2 million laws, you're (probably) covered in it!
🧵
mark williams retweeted
Make no mistake: post-Mythos, the United States has a licensing regime for AI. It’s just informal, with no consistent rules or firm boundaries on state power or public transparency. Cobalt mining in the Congo is vastly more institutionalized than frontier AI licensing in the US.
mark williams retweeted
There is a lot of justified anger at Anthropic for sandbagging Fable 5 for AI development tasks. But an unanticipated side effect is that third-party evaluators can no longer credibly use the model for evaluations.
Case in point: we are in the middle of running *really hard* AI R&D evaluations. Fable 5 would be a perfect test candidate. But because of Anthropic's guardrails, we can't know if the model failed or if their classifiers blocked the capability.
By the way, this is not just true for AI R&D. Since Anthropic doesn't make it clear when they are sandbagging, this could seep into any number of technical tasks, and the evaluators wouldn't have any way to know. So they can't credibly claim to evaluate state-of-the-art accuracy using the model.
mark williams retweeted
Are Berkeley Law faculty prohibited from using AI-detection tools, or merely warned that AI-detection tools may be inaccurate and biased? I'm curious what schools are doing about this, as I've only seen warnings.
It's news to me that it was obvious in the 2000s that ML is biased. If that were accurate, a number of groundbreaking studies published starting around 2016 wouldn't have been such a big deal.
Prohibiting AI detection tools does not solve the bias problem. As @olawaleidowu_ pointed out, the concern is AI Police who overconfident in their ability to identify AI-generated content. xitter.gq/olawaleidowu_/status/2…
mark williams retweeted
Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.
mark williams retweeted
we’ve developed proprietary benchmarks for legal reasoning maintained by attorneys at Norm.
because Norm Law attorneys, while serving as outside counsel to hedge funds, PE firms, etc. deploy AI agents in their day-to-day work, we can uniquely build real legal AI benchmarking.
we've been tracking frontier models across generations, and the trend is clear: models are improving substantially in their legal reasoning capabilities.
the latest generation of models are nearly indistinguishable from each other in accurately answering legal questions.
most models are increasingly consistent, with the most recent generation of frontier models reaching the same conclusion ~90% of the time.
but for high-stakes legal work, even the best models on this benchmark reach a different answer often enough that, at scale, users receive contradictory answers to the same question every week.
to integrate ai agents into high-stales legal workflows, you need both (1) purpose-built systems that can constrain, verify, and govern AI reasoning automatically, and (2) the human overlay of expertise for live workflows fully intertwined/integrated w/ ai agents in a deliberate process.
mark williams retweeted
If you think clients buy documents and hours from law firms, this is bad news for lawyers. But if you believe that clients seek discernment, counseling, risk management, and advice from law firms, and documents are just artifacts, this is terrific news for lawyers and clients.
New essay on the economics of structural change and the post-commodity future of work.
1. Almost any question about the impact of advanced AI on the economy needs to start at the same place: what is still scarce? Answer that, and the analysis becomes pretty straightforward. This essay explores what becomes scarce if AI really can replicate most of what humans do in production, and what this mean for the future of jobs.
2. My conjecture, working through the economics: labor reallocates across sectors, and the sector it reallocates to has properties that keep labor a meaningful share of the economy. Ultimately this is about the structure of demand itself. For this, we have to go back to Girard, Augustine and Rousseau: once people's base needs are met, their preferences shift to comparative motives (e.g., status, exclusivity, social desirability). This motive is inherently non-satiated.
4. The key paper is Comin, Lashkari, and Mestieri (Econometrica 2021). As people get richer, they don't buy proportionally more of everything. They shift spending toward sectors with higher income elasticity. They estimate income effects account for 75%+ of observed structural change.
5. The ironic consequence: the sector that gets automated becomes a smaller share of the economy, not a larger one. Agriculture got massively more productive and its share of employment collapsed. Manufacturing too. The "stagnant" sectors absorb the spending and the jobs.
6. So the question is: which sectors have high income elasticity in a post-AGI world? I argue it's what I call the relational sector. Categories where the human isn't just an input into production, it is part of the value.
7. Why does the relational sector have high income elasticity? Because human desire has a mimetic, relational dimension. We don't just want things for their intrinsic properties. We want what others want, and we want it more when others can't have it. Girard, Rousseau, Augustine, and Hobbes all saw this.
8. In work with Kristóf Madarász, we showed this experimentally: WTP roughly doubles when a random subset of others is excluded from the good. And in new work with Graelin Mandel, AI involvement kills the premium. Human-made art gains 44% from exclusivity; AI-made art only 21%.
9. This all comes together for the core argument. The sector that absorbs spending as AI makes commodity production cheap is one where human provenance is part of the value, and demand for it grows faster than income. Exactly the profile that keeps labor meaningful.
10. To be clear about the claim: I'm NOT saying aggregate labor share must rise. It may fall. The claim is about sectoral composition, i.e., where expenditure and employment go once commodities get cheap, and the fact that the sector that will absorb reallocated labor maps to a substantial component of human preferences and desire.
11. If you're interested in the formal model, a linked companion technical note works out all the economics.
Read the essay here: aleximas.substack.com/p/what…
