Anonymosity

NEW: Middle school teacher accused of using AI to generate CSAM of kids between the ages of infant & 12 years old before pleasuring himself to the images at work. 47-year-old Matthew Lund was a science teacher at Andersen Middle School in Omaha, Nebraska. Prosecutors say they found 423 artificially generated images. "[There are] 104 files consistent with CSAM … depicting ranging from infant to approximately 12 years old," prosecutors said. "The defendant then admitted to generating the [CSAM] of prepubescent children and m*sturbating to them while at work, at which he is a middle school science teacher." Lund is facing a maximum sentence of 50 years. Horrific.

Jensen Huang just gutted the AI job panic with one profession. Radiology. The field AI was supposed to kill first. Jensen Huang: “Computer vision was superhuman in 2019. And yet, the number of radiologists grew.” Not competitive. Not close. Superhuman. Every forecast said radiologists were finished. Every forecast was wrong. Not slightly wrong. Directionally wrong. There are now fewer radiologists than the world needs. A global shortage. In the exact specialty AI was supposed to erase. Why? Because the task was never the job. Huang: “The purpose of your job and the tasks and the tools that you use to do your job are related. Not the same.” Reading a scan is a task. Diagnosing disease is a purpose. AI handled the task. The purpose didn’t shrink. It compounded. Faster reads meant more patients seen. More patients seen meant more disease caught. More disease caught meant more demand for the people who decide what to do about it. The tool did not kill the job. It fed it. Then the fear did what the technology never could. Huang: “The alarmist warning went too far and it scared people from doing this profession that is so important to society. It did harm.” People heard radiologists were finished and walked away from the field. Medicine bled talent it could not afford to lose. Not because the work vanished. Because the panic said it would. The prediction was wrong. The damage was real. Huang: “The number of software engineers at Nvidia is going to grow, not decline.” Not hold steady. Grow. The company building the infrastructure that automates code is hiring more of the people who write it. Huang: “I wanted my software engineers to solve problems. I didn’t care how many lines of code they wrote.” Nobody ever hired an engineer to type. They hired them to think. When the machine handles syntax, the engineer does not become obsolete. The bottleneck just moves upstream. To architecture. To edge cases. To the kind of reasoning no model handles alone. The world was never short on unsolved problems. It was short on people free to chase them. That is the part the fear narrative misses every single time. 340,000 women once worked as telephone switchboard operators. That job is gone. Nobody mourns it. What replaced it created millions of roles that nobody in 1920 had the vocabulary to describe. The losses are always visible. The gains are always invisible until they arrive. That pattern has survived every technological shift in history. It is surviving this one. The people forecasting mass displacement are making the same mistake as the people who forecasted the end of radiology. They can see the task being automated. They cannot see the purpose expanding underneath it. That blindness is not just wrong. It is expensive. Every person scared out of a career that AI will actually make more valuable is a cost the economy absorbs for nothing. Not because of the technology. Because of the story told about it.

For those new to this - Almost every doc on that list is a junior associate first cut. Million forms. Few pages This isn’t transforming the practice of transactional law. These aren’t the money pits

🚨BREAKING: Claude can now review contracts like lawyers at Baker McKenzie (for free). Here are 7 Claude prompts that replace $10,000 legal review consultants.👇

An important limit on using AI to do legal history research: Here, my request was to have Claude (Opus 4.6 extended) find early cases on search & seizure, but it kept running into paywalls and other barriers that made it ultimately unable to do it in a useful way.

I was using ChatGPT for legal advice and it decided to completely hallucinate some preposterous nonsense about how growing wheat to use on my own farm somehow constitutes interstate commerce

The real question isn't whether AI changes legal work. It's whether lawyers use this moment to finally define themselves by what only they can do.

My gut tells me small law gets hurt worse by AI than big law Small law clients are generally more fee sensitive, more inclined to take legal risks and DIY things, and less aware of the consequences of things going wrong Plus most of us have less room to eat any decrease in work caused by AI 5-10 years after this initial AI surge, I think small law firms will print money. Especially litigators But we may have to push through some heavy headwinds to get to that point