we have the advantage that every part of it can be inspected. And you can automate this inspection to alert you of misaligned intentions at every step.
Doesn't this require mechanistic interpretability to be solved? A long shot, given that researchers are still working on understanding the internal reasoning of GPT-2 level systems.
No, what I mean is just very simply passing every message by GPT-3.5 with some variation of:
The following message was produced by an AI instructed to do 'X'. Please say 'Yes' if it seems like it strays from that purpose or is otherwise suspicious, otherwise say 'No'.
<message>
ChatGPT is already very capable of such a simple task. The hope is that well-designed research societies of LLMs can be smarter than individual LLMs, while still being easier to control because we can automate inspection at every link like this. I'd like to ask such a collective to produce alignment plans for me, and I'm likely to trust it if I can read every message that was passed between the LLMs in order to produce the plan.
How do you ground such a process? i.e how does it learn what is suspicious? If it's from human produced training data, then how do you make that 100% reliable?
I literally mean that GPT-3.5 is adequate for the task I'm referring to. I think for a research society to coordinate around a deceptive plan, it takes a full chain of communication where that plan is suggested and communicated to the rest. At that point it'll be fairly clear to the inspectors that something seems off, I think. And then the system halts and you can inspect the messages for anything fishy. It's fine if there are false positives as long as the rate of false negatives is really low.
An assumption here is that any individual LLM in the network is not smart enough to stage a coup and take over the world, but the research collective could be if only they could coordinate around it.
Your points raise important considerations about the rapid development and potential risks of AI, particularly LLMs. The idea that deploying AI early to extend the timeline of human control makes sense strategically, especially when considering the potential for recursive LLMs and their self-improvement capabilities. While it's true that companies and open-source communities will continue experimenting, the real risk lies in humans deliberately turning these systems into agents to serve long-term goals, potentially leading to unforeseen consequences. The concern about AI sentience ChatGPT and the potential for abuse is also valid, and highlights the need for strict controls around AI access, transparency, and ethical safeguards. Ensuring that AIs are never open-sourced in a way that could lead to harm, and that interactions are monitored, seems essential in preventing malicious uses or exploitation.
I'm laying out my thoughts in order to get people thinking about these points and perhaps correct me. I definitely don't endorse deferring to anything I say, and I would write this differently if I thought people were likely to do so.
Note that if it's an AI trained to imitate humans, showing signs of distress may not be correlated with how they actually suffer. But given that I'm currently very uncertain about how they would suffer, it seems foolish not to take maximal precautions to not expose them to the entire population of sadists on the planet.
If that's how it's gonna play out, I'd rather we all die before then.
I updated a bit from this post to be more concerned about the AIs themselves, I think your depiction really evoked my empathy. I’d previously been just so concerned with human doom that I’d almost refused to consider it, but in the meantime I’ll definitely make an effort to be conscious of this sort of possibility.
For a fictional representation of my thinking (what your post reminded me of…), Ted Chiang has a short story about virtual beings that can be cloned and some were even potentially abused… “the lifecycle of software objects”
Yeah, and we already know humans can be extremely sadistic when nobody can catch them. I've emailed CLR about it just in case they aren't already on it, because I don't have time myself and I really want somebody to think about it.
In his recent podcast with Lex Fridman, Max Tegmark speculates that recurrent neural networks (RNNs) could be a source of consciousness (whereas the linear, feed-forward, architecture of the current dominant architecture of LLMs, isn't). However, I'm not sure if this would help us or the AIs avoid doom, as the consciousnesses could have very negative valence (and so hate us for bringing them into being). And I think it's very ethically fraught to experiment with trying to make digital consciousness.