As a manager (and sometimes middle manager) I've been thinking about how LLMs are going to change management. Not exactly your topic but close enough. Here's my raw thoughts so far:

• the main reasons you need management layers is coordination
  • one person can't directly manage more than about 12 people effectively
  • past that point you need someone to hide some details for you
  • with ai though one director can manage more managers
  • normally coordination costs make it hard to manage more than 6 managers
  • llms may allow a director to manage 12 managers/teams by automating comms tasks that normally require process (meetings)
  • less meetings mean you can coordinate more work at once
  • this lets the org stay flatter longer, which reduces the amount of coordination hell
• many manager tasks are house keeping
  • managers spend 80% of their time on house keeping so they have the info and org they need to do the critical work 20% of the time
  • some of the house keeping can be automated with llms
  • for example, no need to hear all the status reports if an llm can summarize them and pick out the bits you need to act on and hide the parts you can safely ignore, but still know about them and tell you about them if they become relevant
• the human touch matters
  • humans respond to other humans
  • as a manager much of what makes you successful is your ability to lead, i.e. to get other humans to trust you enough to do what you tell them to do
  • llms are unlikely to be leaders in the short term unless they get way better real fast
  • llms are more like assistants; they lack executive function
• understanding what llms can do for your people
  • you're going to need to understand how and when your ICs should use llms to get their job done
  • you'll have to identify when people are inefficient becuse they don't use ai well and then help them learn to use it
  • this is a totally new thing no manager has done before, but we're going to have to figure it out
  • we'll probably get llms to help us do it

My first guess is that the sort of problems I expect from here are sufficiently weirder/differenter from the classic human middle-manager-culture problems that I think it's probably better to just Original See [LW · GW] on the topic rather than try to check whether the Recursive Middle Manager Hell hypothesis in particular holds here.

(I do think it's an interesting/important question though)

This sounds really interesting! Generally it seems that most people either believe AI will get power by directly being ordered to organize the entire world, or it will be some kind of paper-clip factory robot going rogue and hacking other computers. I am starting to think it will more likely be: Companies switch to AI middle managers to save $$$, then things just happen from there.

Now one way this could go really mazy is like this: All AI-models, even unique ones custom made for a particular company are based on some earlier model. Let's say Wallmart buys a model that is based on a general Middle Manager Model.

This model now has the power to hire and fire low-level workers, so it will be very much in their interest to find out what makes the model tick. They can't analyse the exact model (which is being run from a well guarded server park). But at some point somebody online will get hold of a general Middle Manager Model and let people play with it. Perhaps the open-source people will do all sorts of funny experiments with it and find bugs that could have been inherited by the Wallmart model. 

Now the workers at Wallmart all start playing with the online model in their spare time, looking around AI-forums for possible exploits. Nobody knows if these also work on the real model, but people will still share them, hoping to be able to hack the system: "Hey, if you try to report sick on days when you anyway had time off, the Manager will give you extra credits!" "Listen, if you scan these canned tomatoes fifty times it triggers bug in the system so you will get a higher raise!" Etc.

The workers have no way to know which of the exploits work, but everybody will be too afraid of loosing their jobs if they are the only one NOT hacking the AI. Wait for a few years and you will see the dark tech-cult turning up.

Evolution gives us many organically designed Systems which offer potential Solutions:

• white blood cells move everywhere to spot and kill defective cells with literal kill-switch (apoptosis)

A team of Leucocytes (white blood cells):

• organically checking the whole organisation at all levels
• scanning for signs of amorality/misalignment or any other error
• flagging for surveillance, giving warnings, or sending to a restorative justice process depending on gravity
• agents themselves held to the highest standard

This is a system that can be implemented in a Company and fix most of the recursive middle manager hell.

Many humans would not like that (real accountability is hard, especially for middle-men who benefit from status quo), but AI won’t mind.

So the AI “head” could send their Leucocytes check all the system routinely.

Some thoughts (don't have any background in stuff related but seemed interesting). 

I think it would be interesting to see what you found if you looked into the state of existing research on AI coordination / delegation / systemic interactions and if any of it feels related. I'd be mildly surprised if people have studied exactly this but expect many relevant posts/papers. 

In terms of related stuff on LessWrong, I can't find it now but Paul Christiano has a post on worlds where things go badly slowly and I think this would be kinda in that genre. 

I think this is an interesting thing to consider and feels somewhat related to Dan Hendrycks Natural "Selection Favors AIs over Humans" https://arxiv.org/abs/2303.16200. The connection in my head is "what does an AI ecosystem look like", "what does it mean to discuss alignment in this context", "what outcomes will this system tend towards" etc. The same way middle managers get selected for, so more generally AI systems with certain properties get selected for. 

You might want to read about Ought's agenda with supervise processes not outcomes which feels relevant. 

Recursive middle manager hell feels somewhat related to inner misalignment / misaligned mesa-optimizers where instead of being a subset of the processing of an LLM (how I normally think about it but maybe not how others do), you have your AI system made of many layers and it's plausible that intermediate layers end up optimizing proxies for inputs to what you care about and not even the thing itself. In this view, it seems like the misalignment of middle managers which usually makes companies less effective might just lead to selection against such systems as compared to systems with less of these properties. 

There might be some strategically valuable research to be done here but it's not super clear to me what the theory of change would be. Maybe there something to do with bandwidth / scalability tradeoffs that affect how tightly coupled vs diffuse/distributed useful/popular AI systems will be in the future.