Chris Hoofnagle ✓
@hoofnagle
si irascare, adgnita videntur. I teach technology law at Berkeley and focus on intel/defensetech
7 004Followers
264Following
1 834Posts total
1.1MViews on collected posts
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Two more ideas on AI:
- You'd be surprised to see how earnest 1L students are and how many of them are committed to developing their skills---becoming a better reader, writer, thinker. And so yes, there are the dishonest out there, but they are not the modal student.
- Maybe I
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@hoofnagle ludicrous, unenforceable sabotage. pure virtue signalling from deeply unserious people
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And just to be clear, I am an AI-fanboy. I use https://t.co/DO9p0pLjE6 for my 1l Torts course. But to be clear, this is a RAG-based tutor that I can monitor to see where students want more info. It is not an approach that offloads thought.
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Students are still free to use AI to prepare for class, to self-tutor, and so on.
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Here's a key idea: In the classroom, we don't want students to write the best possible paper, but rather the best possible paper that the student is capable of.
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Don't lawyers need to learn AI? Of course. And we have AI-specific courses focused on those skills. But when it comes to the basics, particularly in 1L, we need students to do the work, lest they never develop the ability to judge for themselves.
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Our original policy was based on the concept of plagiarism. But the rapid increase in capabilities in Claude particularly caused us to shift focus: the new policy seeks to protect the cognitive skills constitutive of a legal education.
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It's not obvious why we did this. We found examples where students announced "I've found a solution to X while conversing with ChatGPT." But that solution was not theirs---it was already reflected elsewhere in the literature, conceptualized by someone else.
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Thus, in work for credit, students may not use AI for several functions:
- conceptualizing
- outlining
-drafting
-revising
- translating
- editing
Any instructor can opt out of this policy or any portion of it.
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Berkeley law has introduced a new, much stricter AI policy
https://t.co/wlNs2cUrKz https://t.co/IFT6fLnU6U
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Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
968.1K21 May
21.7K
11.3K
17.1K
9.6K
16.1K
8.5K
7.1K
3.3K
5.4K
Last 10 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.60%21 May
1.07%
1.70%
2.48%
2.00%
1.98%
1.38%
0.58%
2.47%
0.90%
Reactions — likes, reposts, replies and quotes — divided by views.
What the audience does
Likes71.8%6 147 in total
Reposts10.4%886 in total
Replies2.1%177 in total
Quotes3.1%267 in total
Bookmarks12.6%1 082 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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