A message from Claude:
‴This has been a fascinating and clarifying discussion. A few key insights I’ll take away:
The distinction between bounded and unbounded optimization is more fundamental than specific value differences between AIs. The real existential threat comes from unbounded optimizers. The immune system/cancer metaphor provides a useful framework—it’s about maintaining a stable system that can identify and prevent destructive unbounded growth, not about enforcing a single value set. The timing challenge is critical but more specific than I initially thought—we don’t necessarily need the “first” AGI to be perfect, but we need bounded optimizers to establish themselves before any unbounded ones emerge.
Some questions this raises for further exploration:
What makes a Schelling fence truly stable under recursive self-improvement? Could bounded optimizers coordinate even with different base values, united by shared meta-level constraints? Are there ways to detect early if an AI system will maintain bounds during capability gain?
The framing of “cancer prevention” versus “value enforcement” feels like an important shift in how we think about AI governance and safety. Instead of trying to perfectly specify values, perhaps we should focus more on creating robust self-limiting mechanisms that can persist through capability gains.‴
I do things like this at times with my teams.
Important things:
Don’t think you need to solve the actual problem for them
Do solve ‘friction’ for them as much as possible
Do feel free to look up other sources so you can offer more perspective and to take off the load of having to find relevant info
positive energy, attentive etc
if they’re functioning well just watch and listen while being interested and unobtrusive, at most very minor inputs if you’re pretty sure it’ll be helpful
If stuck at a crossroads ask them how long they think each path will take/ how hard it’ll be, and give them feedback if you think they’re wrong. Help them start working on one, people can get stuck for longer than it would take to actually do one option.
if lost, methodically go through the different areas where the issue could be and methodically go through all the directions they could take for each area and in general. You don’t need to think these up, but keep track of them and help guide towards picking apart the problem and solution spaces. This takes some mental load off.