Curl et al, “Judges Shouldn’t Rely on AI for the Ordinary Meaning of Text” | Lawfare lawfaremedia.org/article/judges…

Justin Curl, Peter Henderson, Kart Kandula, and Faiz Surani warn that transfering influence to unaccountable private interests through the use of AI or large language models by judges to determine ordinary meaning represents a structural incompatibility with the judicial role.

Tempted to use AI to help interpret statutes or draft opinions? 📜🤖 Take pause. As we explained in Lawfare, closed models can smuggle in the hidden value judgments of everyone who touched the deployment/creation pipeline. To see why, look at the recent modification of Grok’s

America’s view of AI is often abstract and hyperbolic. Rather than the Western concept of a superhuman or self-improving system, China is betting on a more everyday approach econ.st/44UqSd0

We ourselves are enthusiastic users of AI in our scientific workflows. On a day-to-day basis, it all feels very exciting. But the impact of AI on science as an institution, rather than individual scientists, is a different question that demands a different kind of analysis.

The mainstream view of AI for science says AI will rapidly accelerate science, and that we're on track to cure cancer, double the human lifespan, colonize space, and achieve a century of progress in the next decade. In a new AI Snake Oil essay, Arvind Narayanan and I argue that

As of today, submissions for Harvard JOLT's spring issue are open! We're looking for law review articles related to law and technology (defined very broadly). Articles can be doctrinal, empirical, historical, philosophical, etc. Scholastica link is in the thread :)

How does GPT-5 compare against Claude Opus 4.1 on agentic tasks? Since their release, we have been evaluating these models on challenging science, web, service, and code tasks. Headline result: While cost-effective, so far GPT-5 never tops agentic leaderboards. More evals 🧵

If the goal is dependency and revenue from China's AI market, why sell? Cloud/remote access delivers both without giving away the hardware. Keep the revenue, keep some control. Selling chips is just giving away leverage for nothing.

AI as Normal Technology is often contrasted with AI 2027. Many readers have asked if AI evaluations could help settle the debate. Unfortunately, this is not straightforward. That's because the debate is not about differences in AI capability, which evaluations typically measure.

We’ve raised a $20M Series A from Index Ventures, Bain Capital Ventures, and Elad Gil, with participation from Sequoia Capital, Cooley LLP, and Patrick Collison It took us 173 days to review our first 1,000 contracts. Now, we do this every three weeks. Even as we’ve scaled, we’ve kept our signature