In my last post, I challenged the idea that inner alignment failures should be explained by appealing to agents which perform explicit internal search. By doing so, I argued that we should instead appeal to the more general concept of  malign generalization, and treat mesa-misalignment as a special case.  Unfortunately, the post was light on examples of what we should be worrying about instead of mesa-misalignment. Evan Hubinger wrote, Personally, I think there is a meaningful sense in which all the models I'm most worried about do some sort of search internally (at least to the same extent that humans do search internally), but I'm definitely uncertain about that.Wei Dai expressed confusion why I would want to retreat to malign generalization without some sort of concrete failure mode in mind, Can you give some realistic examples/scenarios of “malign generalization” that does not involve mesa optimization? I’m not sure what kind of thing you’re actually worried about here.In this post, I will outline a general category of agents which may exhibit malign generalization without internal search, and then will provide a concrete example of an agent in the category. Then I will argue that, rather than being a very narrow counterexample, this class of agents could be competitive with search-based agents.  THE SWITCH CASE AGENT Consider an agent governed by the following general behavior,  LOOP:State = GetStateOfWorld(Observation)IF State == 1:PerformActionSequence1() IF State == 2:PerformActionSequence2()...END_LOOP  It's clear that this agent does not perform any internal search for strategies: it doesn't operate by choosing actions which rank highly according to some sort of internal objective function. While you could potentially rationalize its behavior according to some observed-utility function, this would generally lead to more confusion than clarity. However, this agent could still be malign in the following way. Suppose the agent is 'mistaken' about the s