Description du poste
A who-does-what plan for AI safety, built around Trusted Deployers: certified hosts that keep dangerous models guarded without ending open access.
AI has reached a new level of public interest. That may seem like a silly thing to say, as it’s been of interest for a while. But prior (broadly public) interest was about it as a tool, or about the money to be made or lost, or about an effect on jobs.
The new interest demands policy. It demands action. The new interest is connected with risks I consider real. Being real doesn’t make these risks certain. But being real, even with uncertainty, is reason enough to act.
I’ve written lately about risks, cybersecurity risks, and loss-of-control risks. These tried to explain complex topics, starting from the initial premise. Recommendations follow the explanation. This piece will be a bit different. Its focus is upon what I think we should be doing. You might consider it a policy piece. Policy in a completed form has to be a bit broad. There’s always more than one thing going on. As such, I’ll lay out my outline first, and then offer below the extra detail, background and context that I think is important to understanding each point in that outline.
If you’re scanning the outline and see something you disagree with, I’d suggest you continue on, because the outline is, by design, abbreviated, and not fully descriptive.
This isn’t the only effort of this type. Institute for Progress (IFP) and AI Futures are two well known efforts. What distinguishes this most of all is thinking more deeply about how models are deployed. This is a background element that’s somewhat ignored, because it’s not as novel and is not as visible to users. But it’s absolutely critical. I don’t expect this plan would replace plans from well known organizations, but by illustrating a gap, I hope to inspire improvement amongst those plans.
Who and WhatThis outline is categorized by who would be expected to do what. In some cases, someone is expected to do it,