Information inaccessibility is somehow a surmountable problem for AI alignment (and the genome surmounted it),
Yes. Evolution solved information inaccessibility, as it had to, over and over, in order to utilize dynamic learning circuits at all (as they always had to adapt to and be adaptive within the context of existing conserved innate circuitry).
The general solution is proxy matching, where the genome specifies a simple innate proxy circuit which correlates and thus matches with a target learned circuit at some critical learning phase, allowing the innate circuit to gradually supplant itself with the target learned circuit. The innate proxy circuit does not need to mirror the complexity of the fully trained target learned circuit at the end of it’s development, it only needs to roughly specify it at a some earlier phase, against all other valid targets.
Imprinting is fairly well understood, and has the exact expected failure modes of proxy matching. The oldbrain proxy circuit just detects something like large persistent nearby moving things—which in normal development are almost always the chick’s parents. After the newbrain target circuit is fully trained the chick will only follow it’s actual parents or sophisticated sims thereof. But during the critical window before the newbrain target is trained, the oldbrain proxy circuit can easily be fooled, and the chick can imprint on something else (like a human, or a glider).
Sexual attraction is a natural extension of imprinting: some collaboration of various oldbrain circuits can first ground to the general form of humans (infants have primitive face detectors for example, and more), and then also myriad more specific attraction signals: symmetry, body shape, secondary characteristics, etc, combined with other circuits which disable attraction for likely kin ala the Westermarck effect (identified by yet other sets of oldbrain circuits as the most familiar individuals during childhood). This explains the various failure modes we see in porn (attraction to images of people and even abstractions of humanoid shapes), and the failure of kin attraction inhibition for kin raised apart.
Fear of death is a natural consequence of empowerment based learning—as it is already the worst (most disempowered) outcome. But instinctual fear still has obvious evolutionary advantage: there are many dangers that can kill or maim long before the brain’s learned world model is highly capable. Oldbrain circuits can easily detect various obvious dangers for symbol grounding: very loud sounds and fast large movements are indicative of dangerous high kinetic energy events, fairly simple visual circuits can detect dangerous cliffs/heights (whereas many tree-dwelling primates instead instinctively fear open spaces), etc.
Anger/Jealousy/Vengeance/Justice are all variations of the same general game-theoretic punishment mechanism. These are deviations from empowerment because an individual often pursues punishment of a perceived transgressor even at a cost to their own ‘normal’ (empowerment) utility (ie their ability to pursue diverse goals). Even though the symbol grounding here seems more complex, we do see failure modes such as anger at inanimate objects which are suggestive of proxy matching. In the specific case of jealousy a two step grounding seems plausible: first the previously discussed lust/attraction circuits are grounded, which then can lead to obsessive attentive focus on a particular subject. Other various oldbrain circuits then bind to a diverse set of correlated indicators of human interest and attraction (eye gaze, smiling, pupil dilation, voice tone, laughter, touching, etc), and then this combination can help bind to the desired jealousy grounding concept: “the subject of my desire is attracted to another”. This also correctly postdicts that jealousy is less susceptible to the inanimate object failure mode than anger.
Empathy: Oldbrain circuits conspicuously advertise emotional state through many indicators: facial expressions, pupil dilation, blink rate, voice tone, etc—so that another person’s sensory oldbrain circuits can detect emotional state from these obvious cues. This provides the requisite proxy foundation for grounding to newbrain learned representations of emotional state in others, and thus empathy. The same learned representations are then reused during imagination&planning, allowing the brain to imagine/predict the future contingent emotional state of others. Simulation itself can also help with grounding, by reusing the brain’s own emotional circuity as the proxy. While simulating the mental experience of others, the brain can also compare their relative alignment/altruism to its own, or some baseline, allowing for the appropriate game theoretic adjustments to sympathy. This provides a reasonable basis for alignment in the brain, and explains why empathy is dependent upon (and naturally tends to follow from) familiarity with a particular character—hence “to know someone is to love them”.
Evolution needed a reasonable approximation of “degree of kinship”, and a simple efficient proxy is relative circuit capacity allocated to modeling an individual in the newbrain/cortex, which naturally depends directly on familiarity, which correlates strongly with kin/family.
I feel confused. I think this comment is overall good (though I don’t think I understand a some of it), but doesn’t seem to suggest the genome actually solved information inaccessibility in the form of reliably locating learned WM concepts in the human brain?
My comment is a hypothesis about how exactly the genome solved information inaccessibility in the form of locating learned WM concepts (ie through proxy matching), so it does more than merely suggest, but I guess you may be leaning heavily on reliably? As it’s only reasonably reliable when the early training environment is sufficiently normal: it has the expected out of distribution failures (and I list numerous examples).
Yes. Evolution solved information inaccessibility, as it had to, over and over, in order to utilize dynamic learning circuits at all (as they always had to adapt to and be adaptive within the context of existing conserved innate circuitry).
The general solution is proxy matching, where the genome specifies a simple innate proxy circuit which correlates and thus matches with a target learned circuit at some critical learning phase, allowing the innate circuit to gradually supplant itself with the target learned circuit. The innate proxy circuit does not need to mirror the complexity of the fully trained target learned circuit at the end of it’s development, it only needs to roughly specify it at a some earlier phase, against all other valid targets.
Imprinting is fairly well understood, and has the exact expected failure modes of proxy matching. The oldbrain proxy circuit just detects something like large persistent nearby moving things—which in normal development are almost always the chick’s parents. After the newbrain target circuit is fully trained the chick will only follow it’s actual parents or sophisticated sims thereof. But during the critical window before the newbrain target is trained, the oldbrain proxy circuit can easily be fooled, and the chick can imprint on something else (like a human, or a glider).
Sexual attraction is a natural extension of imprinting: some collaboration of various oldbrain circuits can first ground to the general form of humans (infants have primitive face detectors for example, and more), and then also myriad more specific attraction signals: symmetry, body shape, secondary characteristics, etc, combined with other circuits which disable attraction for likely kin ala the Westermarck effect (identified by yet other sets of oldbrain circuits as the most familiar individuals during childhood). This explains the various failure modes we see in porn (attraction to images of people and even abstractions of humanoid shapes), and the failure of kin attraction inhibition for kin raised apart.
Fear of death is a natural consequence of empowerment based learning—as it is already the worst (most disempowered) outcome. But instinctual fear still has obvious evolutionary advantage: there are many dangers that can kill or maim long before the brain’s learned world model is highly capable. Oldbrain circuits can easily detect various obvious dangers for symbol grounding: very loud sounds and fast large movements are indicative of dangerous high kinetic energy events, fairly simple visual circuits can detect dangerous cliffs/heights (whereas many tree-dwelling primates instead instinctively fear open spaces), etc.
Anger/Jealousy/Vengeance/Justice are all variations of the same general game-theoretic punishment mechanism. These are deviations from empowerment because an individual often pursues punishment of a perceived transgressor even at a cost to their own ‘normal’ (empowerment) utility (ie their ability to pursue diverse goals). Even though the symbol grounding here seems more complex, we do see failure modes such as anger at inanimate objects which are suggestive of proxy matching. In the specific case of jealousy a two step grounding seems plausible: first the previously discussed lust/attraction circuits are grounded, which then can lead to obsessive attentive focus on a particular subject. Other various oldbrain circuits then bind to a diverse set of correlated indicators of human interest and attraction (eye gaze, smiling, pupil dilation, voice tone, laughter, touching, etc), and then this combination can help bind to the desired jealousy grounding concept: “the subject of my desire is attracted to another”. This also correctly postdicts that jealousy is less susceptible to the inanimate object failure mode than anger.
Empathy: Oldbrain circuits conspicuously advertise emotional state through many indicators: facial expressions, pupil dilation, blink rate, voice tone, etc—so that another person’s sensory oldbrain circuits can detect emotional state from these obvious cues. This provides the requisite proxy foundation for grounding to newbrain learned representations of emotional state in others, and thus empathy. The same learned representations are then reused during imagination&planning, allowing the brain to imagine/predict the future contingent emotional state of others. Simulation itself can also help with grounding, by reusing the brain’s own emotional circuity as the proxy. While simulating the mental experience of others, the brain can also compare their relative alignment/altruism to its own, or some baseline, allowing for the appropriate game theoretic adjustments to sympathy. This provides a reasonable basis for alignment in the brain, and explains why empathy is dependent upon (and naturally tends to follow from) familiarity with a particular character—hence “to know someone is to love them”.
Evolution needed a reasonable approximation of “degree of kinship”, and a simple efficient proxy is relative circuit capacity allocated to modeling an individual in the newbrain/cortex, which naturally depends directly on familiarity, which correlates strongly with kin/family.
I feel confused. I think this comment is overall good (though I don’t think I understand a some of it), but doesn’t seem to suggest the genome actually solved information inaccessibility in the form of reliably locating learned WM concepts in the human brain?
My comment is a hypothesis about how exactly the genome solved information inaccessibility in the form of locating learned WM concepts (ie through proxy matching), so it does more than merely suggest, but I guess you may be leaning heavily on reliably? As it’s only reasonably reliable when the early training environment is sufficiently normal: it has the expected out of distribution failures (and I list numerous examples).