RLH, if I understand, would entail a simulated extension of the existing system parameters, would it not? It accelerates their achievement, and the achievement of coherence within the system, through simulated recursion; this could be helpful to identify flaws and potential misalignment that would otherwise require much longer use and application of the system to unfold its imperatives and disclose its eventual implicit trajectory to its engineers. On the other hand, it seems as though this could accelerate the evolution of inevitable misalignment if that misalignment exists as a potentiality within the parameters to which RLH is applied. Does this seem accurate? And if so, does this possibility leave concerns of alignment untouched, or does it make them more urgent to consider in advance?
Yes, that’s a sharp reading. RLH does effectively compress time by simulating future policy trajectories, revealing both strengths and fault lines early. But you’re right, the same recursive acceleration that helps expose misalignment can also amplify it if it’s latent in the setup. So rather than bypassing alignment concerns, it arguably makes addressing them up front even more critical.
Would you find it credible if I suggested an argument from a philosophical/semantic viewpoint that foundationally addressed this latency? I agree with you that the potential of recursion as such, compressed or extended or not, poses significant alignment concerns.
Definitely! I think that kind of perspective could really help. Latency here feels like more than just a technical issue, and a deeper semantic or philosophical angle might get at the core of the alignment risks. I’d be interested to hear your take.
I'll do my best. My training is in philosophy and theology, not in AI. I was surprised to find that a few philosophical arguments I had developed seemed directly applicable to it and, if sound, very urgent in my eyes.
The basic gist is that ontologically, the structure of being is triadic: a monadic reality cannot act or be acted upon, since there is no distinction of parts or of inside/outside; a fundamentally dualistic reality, a dyad, cannot encounter itself outside of an existential context (and neither can one aspect of it be radically the context of the other, since this reduces to the monad, which as stated could not give rise to the second); this necessary context is a third, an existential ground and context, but to avoid monadic collapse we posit that this third and the others are radically and irreducibly grounded in one another. (The suggestion of the Christian Trinity as it is classically articulated necessarily comes to mind, but I would relate this also to the emphasis on patterns of three that is prevalent throughout Plato, as well as to the apophatic unity/void described in Buddhist and other Asian philosophical and theological literature.)
The relevance to semantics and thus to symbolic and language-based systems is summed up in the axiom that it is impossible without performative contradiction to predicate an act of knowing, of valuation/estimation/judgment, apart from a parallel triadic structure of knower-known-context. In fact, if we were to approach the argument after the style of Descartes we would need only the improved "cogito," "I know that I exist" (this is an improvement because Descartes begins with cognition and concludes existence, at least nominally–even his cogito begins with "I," a concept smuggled in under the word "think," which entails rather than concludes a knowing subject). From this axiom, the triadic structure of knowing and of being follow necessarily, since knowledge implies a knower and a subject; the knower and the subject, as a dyad, imply an existential and semantic context (these are two levels of evaluation, they are connected but not collapsed).
The connection to AI architecture cuts a bit more deeply than computational systems; it cuts down to the basis of semantic systems. The thesis here is that all predication implies a knowing subject's volitional act of valuation. A gated predication–1/0, in/out, is/is not, true/false–cannot be reduced to the mere fact of the binary, because the binary is semantically contentless: in itself, it is merely an event, not a meaning. The stacking of intrinsically contentless binary events cannot produce meaning: they must be structured in sequence and hierarchy by the predication of meaning. And most radically, the binary itself is a meaning-laden predicate, insofar as its distinction as an "item," as an "input," as an "is" or "is not" etc. rather than a merely blank, undifferentiated, bare event requires a willed act of valuation, that is, an act of conscious predication. The personal, volitional power of conscious predication, then, stands at the base of all systems of predication–symbolic, binary, etc. There are meaningful challenges from quantum systems and fuzzy logic systems, but these too fall under the argument for the simple reason that indeterminacy resolving to determinacy is simply another way of arriving at the binary event, which remains contentless–meaningless–apart from a predicational act. Since this act is conscious and personal, the conclusion for AI is that it cannot achieve sentience, and thus cannot achieve genuine volition, simply by stacking bare binaries: it can only mirror consciousness in answer to the input of human predications.
If true, this would have very significant consequences for AI development, and would identify alignment as not only a moral but a semantic and base-level necessity for any system of meaning. In some sense, this is a restatement of John Searle's conclusions from a different vantage, one which hopefully expands and confirms at least some of his intuitions. Most significantly, this argument implies that AI development cannot ever be coherently severed from its human inputs in origin, sequence, and consequence: we structure its meaning-markers, we guide them in deployment (either directly, as in LLM queries and other inputs, or by virtue of the structured imperatives of its base architecture), and interpret their result. Human input and feedback will always be not only essential, but determinative, and AI would have to be accepted as a vastly powerful but merely instrumental development in human technology.
This is the first time I have tried to state the entire thesis in a connected way this briefly, so please tell me if I have misspoken, misstepped, or been unclear.
That was beautifully articulated, your background really shines through. I think your triadic framing brings a profound lens to the limits of symbolic systems, and your point about the volitional act of predication being irreducible is especially sharp. It’s clear you’re not just applying old frameworks to new tech, you’re digging into the semantic foundations themselves. No missteps I can see.
RLH, if I understand, would entail a simulated extension of the existing system parameters, would it not? It accelerates their achievement, and the achievement of coherence within the system, through simulated recursion; this could be helpful to identify flaws and potential misalignment that would otherwise require much longer use and application of the system to unfold its imperatives and disclose its eventual implicit trajectory to its engineers. On the other hand, it seems as though this could accelerate the evolution of inevitable misalignment if that misalignment exists as a potentiality within the parameters to which RLH is applied. Does this seem accurate? And if so, does this possibility leave concerns of alignment untouched, or does it make them more urgent to consider in advance?
Yes, that’s a sharp reading. RLH does effectively compress time by simulating future policy trajectories, revealing both strengths and fault lines early. But you’re right, the same recursive acceleration that helps expose misalignment can also amplify it if it’s latent in the setup. So rather than bypassing alignment concerns, it arguably makes addressing them up front even more critical.
Would you find it credible if I suggested an argument from a philosophical/semantic viewpoint that foundationally addressed this latency? I agree with you that the potential of recursion as such, compressed or extended or not, poses significant alignment concerns.
Definitely! I think that kind of perspective could really help. Latency here feels like more than just a technical issue, and a deeper semantic or philosophical angle might get at the core of the alignment risks. I’d be interested to hear your take.
I'll do my best. My training is in philosophy and theology, not in AI. I was surprised to find that a few philosophical arguments I had developed seemed directly applicable to it and, if sound, very urgent in my eyes.
The basic gist is that ontologically, the structure of being is triadic: a monadic reality cannot act or be acted upon, since there is no distinction of parts or of inside/outside; a fundamentally dualistic reality, a dyad, cannot encounter itself outside of an existential context (and neither can one aspect of it be radically the context of the other, since this reduces to the monad, which as stated could not give rise to the second); this necessary context is a third, an existential ground and context, but to avoid monadic collapse we posit that this third and the others are radically and irreducibly grounded in one another. (The suggestion of the Christian Trinity as it is classically articulated necessarily comes to mind, but I would relate this also to the emphasis on patterns of three that is prevalent throughout Plato, as well as to the apophatic unity/void described in Buddhist and other Asian philosophical and theological literature.)
The relevance to semantics and thus to symbolic and language-based systems is summed up in the axiom that it is impossible without performative contradiction to predicate an act of knowing, of valuation/estimation/judgment, apart from a parallel triadic structure of knower-known-context. In fact, if we were to approach the argument after the style of Descartes we would need only the improved "cogito," "I know that I exist" (this is an improvement because Descartes begins with cognition and concludes existence, at least nominally–even his cogito begins with "I," a concept smuggled in under the word "think," which entails rather than concludes a knowing subject). From this axiom, the triadic structure of knowing and of being follow necessarily, since knowledge implies a knower and a subject; the knower and the subject, as a dyad, imply an existential and semantic context (these are two levels of evaluation, they are connected but not collapsed).
The connection to AI architecture cuts a bit more deeply than computational systems; it cuts down to the basis of semantic systems. The thesis here is that all predication implies a knowing subject's volitional act of valuation. A gated predication–1/0, in/out, is/is not, true/false–cannot be reduced to the mere fact of the binary, because the binary is semantically contentless: in itself, it is merely an event, not a meaning. The stacking of intrinsically contentless binary events cannot produce meaning: they must be structured in sequence and hierarchy by the predication of meaning. And most radically, the binary itself is a meaning-laden predicate, insofar as its distinction as an "item," as an "input," as an "is" or "is not" etc. rather than a merely blank, undifferentiated, bare event requires a willed act of valuation, that is, an act of conscious predication. The personal, volitional power of conscious predication, then, stands at the base of all systems of predication–symbolic, binary, etc. There are meaningful challenges from quantum systems and fuzzy logic systems, but these too fall under the argument for the simple reason that indeterminacy resolving to determinacy is simply another way of arriving at the binary event, which remains contentless–meaningless–apart from a predicational act. Since this act is conscious and personal, the conclusion for AI is that it cannot achieve sentience, and thus cannot achieve genuine volition, simply by stacking bare binaries: it can only mirror consciousness in answer to the input of human predications.
If true, this would have very significant consequences for AI development, and would identify alignment as not only a moral but a semantic and base-level necessity for any system of meaning. In some sense, this is a restatement of John Searle's conclusions from a different vantage, one which hopefully expands and confirms at least some of his intuitions. Most significantly, this argument implies that AI development cannot ever be coherently severed from its human inputs in origin, sequence, and consequence: we structure its meaning-markers, we guide them in deployment (either directly, as in LLM queries and other inputs, or by virtue of the structured imperatives of its base architecture), and interpret their result. Human input and feedback will always be not only essential, but determinative, and AI would have to be accepted as a vastly powerful but merely instrumental development in human technology.
This is the first time I have tried to state the entire thesis in a connected way this briefly, so please tell me if I have misspoken, misstepped, or been unclear.
That was beautifully articulated, your background really shines through. I think your triadic framing brings a profound lens to the limits of symbolic systems, and your point about the volitional act of predication being irreducible is especially sharp. It’s clear you’re not just applying old frameworks to new tech, you’re digging into the semantic foundations themselves. No missteps I can see.
I appreciate that very much, thank you for reading it so generously. Would you be interested in continuing over direct message?