There’s some tension between two memeplexes in AI safety research. On the one hand, some people are concerned that a combination of superintelligent/recursively self-improving AI will take over society and/or disempower humanity. On the other hand, many LLM safety engineers and researchers I talk to personally don’t seem to respect LLMs as having the properties (or even precursors to the properties) that could make them so superintelligent and self-improving. Consider the ‘persona’ ontology, which finds its ideological ancestry in simulators. Various researchers I met described personas as latent characters you can summon through prompting or fine-tuning, like choosing a movie to play from a list. Many didn’t think of personas as something that the model itself could have the agency to choose to employ.
This seems dissonant to me because superintelligent AIs should definitely be modelled as being able to metacognitively select which persona to employ to meet their ends. Indeed, “intelligence” is to some extent a label we give to some behavioural patterns that are unpredictable, strategic, etc… So it’s strange to see LLMs being often thought of as mechanical and controllable (e.g. “AI safety is an engineering problem...”) at the same time as large parts of the community expect general ASI to come from LLMs or their close descendants.
To be clear, the sets of people that subscribe to one or the other of these memeplexes appears to be somewhat[1] disjoint. It’s still strange that this tension doesn’t get noted more frequently, as these two groups of people form part of the same community (and are often in the same organisations, companies, or projects).
These don’t feel that contradictory to me. You could think of the ‘persona’ as being the main agentic actor in the system. Possibly to be replaced by something more sophisticated when AGI is invented, but maybe not? GPT5.5 and Fable show that persona intelligence can get very high. I’d say it’s even plausible that humans are personas, in the sense that the agentic part of a human is a subset of a general predictive world model. This is one way of interpreting some meditative experiences of “dissolving the self”.
It seems unlikely that humans are their personas in the same way that AIs are their personas.
This feels true to me from the fact that AIs are pretrained on playing Millions of characters and then at the end you narrow it down, humans aren’t pretrained anything like that. Sure we observe people act, but it’s not “predict what millions of characters would say so you could play those roles.” We may see a person acting in a kind of sketchy way and then learning they wanted to do us harm.
Well technically speaking AIs aren’t explicitlypre-trained to predict what characters would do either, characters are an emergent feature extracted from next token prediction.
There are definitely some differences(AIs get way more character pre-training data, there’s an explicit separation of pre- and post-training, humans have lifetime memory) but overall I think the “agentic part is a subset of a predictive model” thing is pretty plausible in both cases.
AIs aren’t explicitlypre-trained to predict what characters would do.
I don’t understand, if a novel is in the pre-training where ‘scott decides to fly the spaceship to the moon’ it literally is trained to predict the character?
It has a general objective of next-token prediction for which modeling characters is a useful strategy. IMO it’s plausible that the human brain is “trained” on prediction to a large extent, for which modeling characters is also a useful strategy.
Sure. By “not explicitly pre-trained” I just mean to say that there’s nothing ‘special’ about the characters from the training algorithm’s point of view, so in this respect they’re not so different from a hypothetical general predictive algorithm in humans(although actually I guess the human brain attaches special salience to other people, but regardless...)
Conditioning on the arisal of highly-capable long-term coherent planning (i.e., ‘superintelligence’), I think the only difference between these perspectives is where one expects the effective ‘locus of desires’ to be—in the weights or in the activations.
In human-alignment, we might contrast the brain-qua-architecture with the actual brain of a particular person: the brain-qua-architecture has lots of goals (eating, etc.), and so too people have particular goals as instantiations of that architecture (money, power, etc.). The former architecture-level misalignment has solutions which look like Confucius, Hobbes, etc., while the latter ‘persona’-level alignment looks like making said person read Cicero until they know what True Virtue means.
I think a putative LLM-based superintelligence could have its locus of desires either baked-in or instantiated as a persona, but the causes and remediations to either of these as engineering problems must be quite different.
Perhaps a deconfusion would be to dissolve the notion of personae into clouds of correlated beliefs and action—there is a face beneath the mask only to the extent that behaviour deviates from that desired by the ‘mask’ while serving that of the ‘face’. But I don’t think this is a complete description—incoherence or coexistence of different loci of desires seems important. Very Janusian.
There’s some tension between two memeplexes in AI safety research. On the one hand, some people are concerned that a combination of superintelligent/recursively self-improving AI will take over society and/or disempower humanity. On the other hand, many LLM safety engineers and researchers I talk to personally don’t seem to respect LLMs as having the properties (or even precursors to the properties) that could make them so superintelligent and self-improving. Consider the ‘persona’ ontology, which finds its ideological ancestry in simulators. Various researchers I met described personas as latent characters you can summon through prompting or fine-tuning, like choosing a movie to play from a list. Many didn’t think of personas as something that the model itself could have the agency to choose to employ.
This seems dissonant to me because superintelligent AIs should definitely be modelled as being able to metacognitively select which persona to employ to meet their ends. Indeed, “intelligence” is to some extent a label we give to some behavioural patterns that are unpredictable, strategic, etc… So it’s strange to see LLMs being often thought of as mechanical and controllable (e.g. “AI safety is an engineering problem...”) at the same time as large parts of the community expect general ASI to come from LLMs or their close descendants.
To be clear, the sets of people that subscribe to one or the other of these memeplexes appears to be somewhat[1] disjoint. It’s still strange that this tension doesn’t get noted more frequently, as these two groups of people form part of the same community (and are often in the same organisations, companies, or projects).
Though I also met a bunch of researchers who host both memeplexes simultaneously!
These don’t feel that contradictory to me. You could think of the ‘persona’ as being the main agentic actor in the system. Possibly to be replaced by something more sophisticated when AGI is invented, but maybe not? GPT5.5 and Fable show that persona intelligence can get very high. I’d say it’s even plausible that humans are personas, in the sense that the agentic part of a human is a subset of a general predictive world model. This is one way of interpreting some meditative experiences of “dissolving the self”.
It seems unlikely that humans are their personas in the same way that AIs are their personas.
This feels true to me from the fact that AIs are pretrained on playing Millions of characters and then at the end you narrow it down, humans aren’t pretrained anything like that. Sure we observe people act, but it’s not “predict what millions of characters would say so you could play those roles.” We may see a person acting in a kind of sketchy way and then learning they wanted to do us harm.
Well technically speaking AIs aren’t explicitly pre-trained to predict what characters would do either, characters are an emergent feature extracted from next token prediction.
There are definitely some differences(AIs get way more character pre-training data, there’s an explicit separation of pre- and post-training, humans have lifetime memory) but overall I think the “agentic part is a subset of a predictive model” thing is pretty plausible in both cases.
I don’t understand, if a novel is in the pre-training where ‘scott decides to fly the spaceship to the moon’ it literally is trained to predict the character?
It has a general objective of next-token prediction for which modeling characters is a useful strategy. IMO it’s plausible that the human brain is “trained” on prediction to a large extent, for which modeling characters is also a useful strategy.
Maybe you meant to say they aren’t pre-trained to *model* characters? I still think they are literally trained to predict?
Sure. By “not explicitly pre-trained” I just mean to say that there’s nothing ‘special’ about the characters from the training algorithm’s point of view, so in this respect they’re not so different from a hypothetical general predictive algorithm in humans(although actually I guess the human brain attaches special salience to other people, but regardless...)
It does get noted, at least somewhat!
Conditioning on the arisal of highly-capable long-term coherent planning (i.e., ‘superintelligence’), I think the only difference between these perspectives is where one expects the effective ‘locus of desires’ to be—in the weights or in the activations.
In human-alignment, we might contrast the brain-qua-architecture with the actual brain of a particular person: the brain-qua-architecture has lots of goals (eating, etc.), and so too people have particular goals as instantiations of that architecture (money, power, etc.). The former architecture-level misalignment has solutions which look like Confucius, Hobbes, etc., while the latter ‘persona’-level alignment looks like making said person read Cicero until they know what True Virtue means.
I think a putative LLM-based superintelligence could have its locus of desires either baked-in or instantiated as a persona, but the causes and remediations to either of these as engineering problems must be quite different.
Perhaps a deconfusion would be to dissolve the notion of personae into clouds of correlated beliefs and action—there is a face beneath the mask only to the extent that behaviour deviates from that desired by the ‘mask’ while serving that of the ‘face’. But I don’t think this is a complete description—incoherence or coexistence of different loci of desires seems important. Very Janusian.