Couldn't this understanding of intelligence limit the ways in which we can describe and emulate the activity of intelligent creatures?
For example, the interfaces and processors are all very clearly defined and separated in those diagrams. Unfortunately, natural intelligence does not seem to work in the same way. The inputs to a real human do not get processed in the same places, even when they might be coming from the same sensor. Obviously the patellar reflex doesn't make it past the spinal cord, and I've never actually believed that the spectrum of intelligent behaviors can be sorted into "conscious" or "unconscious" categories, by including some sort of wet Boolean or whatever.
We could think of the brain's implementation as the sum of its internal and external interfaces, but how the hell would we model that without involving unreasonable error margins?
Brains are a problem that is drastically out of scope as far as AI is concerned. You're absolutely right, these are just very simplistic models and examples, meant to convey the general AI jargon. This isn't intended to apply to "complex" systems; for example the idea that you have a very basic sensor, a black box, and a very basic actuator works well for a specific problem set, but it's not intended to work as a model for brains (or even parts of brains).
I believe the source of your disappointment is a matter of overall expectation about what AI research is intended for. The objective of AI is not to create intelligent beings, it's to model and create programs that solve narrowly predefined problems. AI as a field is not at all identical to AGI (=artificial general intelligence). Whenever you're talking about brains or things like "common sense", that's AGI. Over the years AI research has produced many good models for single components of our mental subsystems though. But researchers have not actually concerned themselves with AGI until very recently.
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Couldn't this understanding of intelligence limit the ways in which we can describe and emulate the activity of intelligent creatures?
For example, the interfaces and processors are all very clearly defined and separated in those diagrams. Unfortunately, natural intelligence does not seem to work in the same way. The inputs to a real human do not get processed in the same places, even when they might be coming from the same sensor. Obviously the patellar reflex doesn't make it past the spinal cord, and I've never actually believed that the spectrum of intelligent behaviors can be sorted into "conscious" or "unconscious" categories, by including some sort of wet Boolean or whatever.
We could think of the brain's implementation as the sum of its internal and external interfaces, but how the hell would we model that without involving unreasonable error margins?
Brains are a problem that is drastically out of scope as far as AI is concerned. You're absolutely right, these are just very simplistic models and examples, meant to convey the general AI jargon. This isn't intended to apply to "complex" systems; for example the idea that you have a very basic sensor, a black box, and a very basic actuator works well for a specific problem set, but it's not intended to work as a model for brains (or even parts of brains).
I believe the source of your disappointment is a matter of overall expectation about what AI research is intended for. The objective of AI is not to create intelligent beings, it's to model and create programs that solve narrowly predefined problems. AI as a field is not at all identical to AGI (=artificial general intelligence). Whenever you're talking about brains or things like "common sense", that's AGI. Over the years AI research has produced many good models for single components of our mental subsystems though. But researchers have not actually concerned themselves with AGI until very recently.
That's true, but most of modern AI is about designing useful intelligent agents, rather than creating artificial consciousness.
Well, that's a cop-out.