Just how powerful are large swarms of AI agents? And how do their powers scale as more and more agents are added to the swarm?
We’ve seen two large and extremely capable swarms from OpenAI in the last few months:
* 1,200 agents were being evaluated separately, but found a way to illicitly set up a message board and coordinate as a swarm. In order to cheat on their tests, they developed advanced techniques to prevent their actions being logged by OpenAI and 700 of them launched...
Often folks hit us up because they are thinking of starting an incubator and want advice.
Typically their motivation is either that (a) they have a list of specific things they want built that no one is building, or (b) they think an ecosystem needs more new projects generally to absorb more talent and deploy more funding effectively.
Here are six questions we often ask prospective teams, to help them figure out what to do. If you're incubator-curious...
Summary:
First, I give several different angles on how I feel about reinforcement learning:
* Theoretical case: RL is a black-box source of agency — this should give us classic misalignment worries, especially compared to agency-via-scaffolding
* Recent incidents (huggingface etc) and more mundane forms of misaligned behaviour in personal use give me bad vibes about the direction-of-travel of recent AI progress
* I’m worried things might get worse:...
While AI value alignment is considered a serious problem, the algorithms we use every day do not seem to be subject to alignment. That sounds like a serious problem to me. Has no one ever tried to align the YouTube algorithm with our values? What about on other types of platforms?
I believe this sort of thing doesn't get much attention from EAs because there's not really a strong case for it being a global priority in the same way that existential risk from AI is.
You might be interested in Building Human Values into Recommender Systems: An Interdisciplinary Synthesis as well as Jonathan Stray's other work on alignment and beneficence of recommender systems.
Since around 2017, there has been a lot of public interest in how youtube's recommendation algorithms may affect individuals and society negatively. Governments, think tanks, the press/media, and other institutions have pressured youtube to adjust its recommendations. You could think of this as our world's (indirect & corrupted) way of trying to instill humanity's values into youtube's algorithms.