I haven’t read the universal learning hypothesis essay (2015) yet, but at first glance, it also looks vulnerable to a behavior genetic critique (and probably an evolutionary psychology critique as well).
In my view, evolved predispositions shape many aspects of learning, including Bayesian priors about how the world is likely to work, expectations about how contingencies work (e.g. the Garcia Effect that animals learn food aversions more strongly if the lag between food intake and nausea/distress is a few minutes/hours rather than immediate), domain-specific inference systems that involve some built-in ontologies (e.g. learning about genealogical relations & kinship vs. learning about how to manufacture tools). These have all been studied for decades by behaviorist learning theorists, developmental psychologists, evolutionary psychologists, animal trainers, etc....
A lot of my early neural network research & evolutionary simulation research aimed to understand the evolution of different kinds of learning, e.g. associative learning vs. habituation and sensitization vs. mate preferences based on parental imprinting, vs. mate value in a mating market with mutual mate choice.
BTW I found this linked article fascinating, and it’s a very important subject for those trying to create safe brain-like AGI by reverse engineering the brain’s alignment mechanisms (empathy/love/altruism).
It’s sometimes called the ‘pointing problem’: the agent’s utility function must use specific concepts from the dynamic learned world model, but it seems difficult to make this connection, because the utility function is innate and the specific concepts we want it to reference will be small targets that could appear anywhere in the complex learned world model.
I describe the problem a bit here, and my current best guess of how the brain solves this (correlation guided proxy matching) is a generalization of imprinting mechanisms. Shard theory is also concerned with the problem.
and probably an evolutionary psychology critique as well)
The article collects the evidence which disproves the central evolved modularity hypothesis of ev psych, which was already pretty decisive in 2015 and has only grown moreso.
I haven’t read the universal learning hypothesis essay (2015) yet, but at first glance, it also looks vulnerable to a behavior genetic critique (and probably an evolutionary psychology critique as well).
In my view, evolved predispositions shape many aspects of learning, including Bayesian priors about how the world is likely to work, expectations about how contingencies work (e.g. the Garcia Effect that animals learn food aversions more strongly if the lag between food intake and nausea/distress is a few minutes/hours rather than immediate), domain-specific inference systems that involve some built-in ontologies (e.g. learning about genealogical relations & kinship vs. learning about how to manufacture tools). These have all been studied for decades by behaviorist learning theorists, developmental psychologists, evolutionary psychologists, animal trainers, etc....
A lot of my early neural network research & evolutionary simulation research aimed to understand the evolution of different kinds of learning, e.g. associative learning vs. habituation and sensitization vs. mate preferences based on parental imprinting, vs. mate value in a mating market with mutual mate choice.
BTW I found this linked article fascinating, and it’s a very important subject for those trying to create safe brain-like AGI by reverse engineering the brain’s alignment mechanisms (empathy/love/altruism).
It’s sometimes called the ‘pointing problem’: the agent’s utility function must use specific concepts from the dynamic learned world model, but it seems difficult to make this connection, because the utility function is innate and the specific concepts we want it to reference will be small targets that could appear anywhere in the complex learned world model.
I describe the problem a bit here, and my current best guess of how the brain solves this (correlation guided proxy matching) is a generalization of imprinting mechanisms. Shard theory is also concerned with the problem.
Jacob—thanks! Glad you found that article interesting. Much appreciated. I’ll read the links essays when I can.
The article collects the evidence which disproves the central evolved modularity hypothesis of ev psych, which was already pretty decisive in 2015 and has only grown moreso.