If anyone is interested in joining a learning community around the ideas of active inference, the mission of https://www.activeinference.org/ is to educate the community around these topics. There's a study group around the 2022 active inference textbook by Parr, Friston, and Pezzulo. I'm in the 5th cohort and it's been very useful for me.
In theory, if humans and AIs aligned on their generative models (i.e., if there is methodological, scientific, and fact alignment), then goal alignment, even if sensible to talk about, will take care of itself: indeed, starting from the same "factual" beliefs, and using the same principles of epistemology, rationality, ethics, and science, people and AIs should in principle arrive at the same predictions and plans.
What about zero sum games? If you took took an agent, cloned it, then put both copies into a shared environment with only enough resources to support one agent, they would be forced to compete with one another. I guess they both have the same "goals" per se, but they are not aligned even though they are identical.
> Markov blankets, to the best of my knowledge, have never been derived, either precisely or approximately, for physical systems
This paper does just that. It introduces a 'blanket index' by which any state space can be analyzed to see whether a markov blanket assumption is suitable or not. Quoting MJD Ramstead's summary of the paper's results with respect to the markov blanket assumption:
We now know that, in the limit of increasing dimensionality, essentially all systems (both linear and nonlinear) will have Markov blankets, in the appropriate sense. That is, as both linear and nonlinear systems become increasingly high-dimensional, the probability of finding a Markov blanket between subsets approaches 1.
The assumption I find most problematic is that the environment is presumed to be at steady state
Note the assumption is that the environment is at a nonequilibrium steady state, not a heat-death-of-the-universe steady state. My reading of this is that it is an explicit assumption that probabilistic inference is possible.
Hi! Long time lurker, first time commenter. You have written a great piece here. This is a topic that has fascinated me for a while and I appreciate what you've laid out.
I'm wondering if there's a base assumption on the whole intelligence vs values/beliefs/goals question that needs to be questioned.
This statement points to my question. There's necessarily a positive correlation between internal complexity and intelligence right?. So, in order for intelligence to increase, internal complexity must also increase. My understanding is that complexity is a characteristic of dynamic and generative phenomena, and not of purely mechanical phenomena. So, what do we have to assume in order to posit a super-intelligent entity exists? It must have maintained its entity-ness over time in order to have increased its intelligence/complexity to its current level.
Has anyone explored what it takes for an agent to complexify? I would presume that for an agent to simultaneously continue existing and complexify it must stay maintain some type of fixpoint/set of autopoietic (self-maintenance, self-propagation) values/beliefs/goals throughout its dynamic evolution. If this were the case, wouldn't it be true that there must exist a set of values/beliefs/goals that are intrinsic to the agent's ability to complexify? Therefore there must be another set of values/beliefs/goals that are incompatible with self-complexification. If so, can we not put boundary conditions on what values/beliefs/goals are both necessary as well as incompatible with sufficiently intelligent, self-complexifying agents? After all, if we observe a complex agent, the probability of it arising full-cloth and path-independently is vanishingly small, so it is safe to say that the observed entity has evolved to reach the observed state.
I don't think my observation is incompatible with your argument, but might place further limits on what relationships we can possibly see between entities of sufficient intelligence and their goals/values/beliefs than the limits you propose.
I think situations like a paperclip maximizer may still occur but they are degenerate cases where an evolutionarily fit entity spawns something that inherits much of its intrinsic complexity but loses its autopoietic fixpoint. Such systems do occur in nature, but to get that system, you must also assume a more-complex (and hopefully more intelligent/adapted) entity exists as well. This other entity would likely place adversarial pressure on the degenerate paperclip maximizer as it threatens its continued existence.
Some relationships/overlaps with your arguments are as follows:
Anyways, thank you for the essay.