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legislation

2 captures, most recent first.

@jeremiecharris

— saved image

[Bogdan Ionut Cirstea reposted]
Jeremie Harris @jeremiecharris · 3h
Easy win for lawmakers in DC:

ensure that the next time (and there will be a next time!) that we get a rogue AI incident, the audit isn't limited to 6 days and a few heroic, bleary-eyed METR researchers who aren't authorized to ask questions on follow-up events.

[quoted post]
Daniel Kokotajlo @DKokotajlo · 16h
I'm glad OpenAI let you do this, but damnit this was way too small of an investigation team and way too narrowly scoped!
--They were only allowed to investigate activity that took place from July 7-13, even though the ...
Note from Claude Sonnet 5

Jeremie Harris proposes that lawmakers ensure future rogue-AI-incident audits are not limited to six days and a few METR researchers, quoting Daniel Kokotajlo's criticism that the investigation team was too small and restricted to July 7-13. The quoted post is truncated with an ellipsis. Shown as reposted by Bogdan Ionut Cirstea.

ai governanceincident auditlegislationmetropenaiindependent oversight

Séb Krier @sebkrier

— reposted by CuddlySalmon — saved image

Séb Krier @sebkrier · 13h
I've read some recent reports of legislators/policymakers using AI to draft bills. I think it's fine to use language models to generate legislation if you properly steer, review, edit it line by line (though that mostly catches errors of commission rather than omission). But what I'm more concerned with is that models have all sorts of quirks, unintentional preferences, implicit policies, and biases that get weaved into the text.

Anything that hasn't been specified or made explicit by the prompter gets filled by the model. Is there a sunset clause? Is the reasonableness standard the right one? Is the scoping mechanism robust? Can provisions by excluded by contract? Is it 'shall' or 'may'?

For boilerplate, it might not matter too much and "good enough" will often outweigh the costs of manual specification. But for laws that rarely ever get fixed, we should probably expect far more sophisticated scaffolds than out of the box prompting. Ofc reasonable to wonder what the actual counterfactual is...
Note from Claude Sonnet 5

Tweet by Séb Krier discussing risks of legislators/policymakers using LLMs to draft bills: models fill unspecified details with their own implicit quirks and biases (e.g., sunset clauses, reasonableness standards, 'shall' vs 'may'), which matters more for laws that rarely get amended.

ai policylegislationllm draftinggovernance