Beware selective reductionism!
If you want to be reductionist, you can do that about anything. Humans are ultimately quarks, there’s no free will, and we have imperatives and rules governing our behavior on every scale. There’s more nuanced discussion to be had but I think it should start with ‘and why doesn’t that reductionism also apply to humans (with a slight twist)?’
> And the human brain is just a bundle of electrical signals.
the more we look the more we find that this is not the case. and i don’t have to invoke any philosophy here, just remind you that neurotransmitter modulation and glial cells exist.
> Are you saying neurotransmitter modulation and glial cells cannot be represented by electrical signals?
Certainly neither of them are action potentials, which are usually the (exclusive and therefore imo incomplete) basis for the mental model of people who claim things like "the brain is just electrical signals." No. It's not. It's a vastly more complicated system of organ(s) than that even if you're willing to draw a line in the sand between brain and environment -- and that's no easy feat itself!
At the end of the day, saying "it's just electrical signals" is a crude way of saying "it's using a model of computation that we understand and can replicate". The first claim may not be strictly true, but it seems you're implying second one is.
This is relevant because the universal function approximaters we are training everyday are capable of representing this computational model, undermining the argument that there is somehow a difference between the model of computation done in the brain and the computation done by neural networks.
> At the end of the day, saying "it's just electrical signals" is a crude way of saying "it's using a model of computation that we understand and can replicate".
oh. well, that’s just a naive embrace of the andy grove fallacy.
as of this moment, the brain’s computational model (and if there is one, and if so how many) is neither well understood nor replicable.
it’s almost a category error to describe the process as “reverse engineering”, but even if that’s an appropriate mental model, it turns out that reverse engineering an evolved system that’s taken 4.5 billion years and has had no human design additions at all has very little in common with any similar approach you could take in, say, inspecting the trained weights of a neural network to back out what’s going on.
Is that why they’re not intelligent? Or an entirely unrelated factor? Would anything change if you implemented exactly the same algorithms on a decimal computer instead? I don’t think it would.
No, the ones and zeros are irrelevant, but like "leaves of three, let it be" you won't accidentally identify something as intelligent, just like you won't accidentally identify a plant as safe to touch. In both cases, the intelligence or the urushiol allergy are coincidal with the rule of thumb.
Follow up: is that answer well-defined (it's not using other nebulous concepts to avoid having to rigorously define it), and does it accept all of the things you think should be called "conscious" and reject all of the things you think should not be?
> It does not understand in the way humans understand.
And?
If it can match to a point where it knows exactly what everything is, and presumably is capable of (or eventually will be able to) making decisions based on that information well enough to obey the rules of the road, then it doesn't really matter if it's using trillions of simple logic gates or a human brain.
Human understanding enables inference. Say your full self driving car is driving down the freeway and an enormous explosion / forest fire / volcano erupts in the distance, it'll blissfully drive towards the disaster - because it has no comprehension of what the orange sky, shaking ground, fleeing people imply.
This is a extreme example but the more we learn about driving the more we realise our ability to do it is based on inference not only about the world, but about the intentions of other drivers.
There's no 'decision' being made by a self driving car - it's matching its predefined set of visual inputs to a set of behaviours. It can never scale to adapt to the unknown - even in principle.
Eventually the cars will indeed be good about determining the intentions of other drivers, not by any sort of body language we might be able to instinctively infer, but by learning what people often do and playing out those scenarios, ensuring it can handle either outcome. We aren't looking for 'perfect', even in the advent of human lives being at risk when going 80 mph on the freeway, it just needs to handle events with an outcome of an order of magnitude fewer incidents/deaths than the current paradigm of human drivers.
> It can never scale to adapt to the unknown - even in principle.
But the human will be able to fill in for the inference cars don't have. Even if we get to level 5 where there's no steering wheel, the human can still control the car's destination and what sort of operation modes the car is in; if there is some event and full-scale panic ensues, the AI driver isn't going to hit people in the street - either the human can instruct it to turn around, or they can get out of the car, since even now it's not really safe try to weave between humans in the street to reach your destination.
> Communication between humans and machines is hindered by a lack of shared awareness.
Yeah... by the fact that humans aren't aware that AI is just a bunch of 1s and 0s and not actually aware. There's no intelligence here.
> Scene understanding
... it cannot understand. It can only match. It does not understand in the way humans understand.