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> When a programmer successfully emulates consciousness, every line will be deliberate, and they will know exactly how they did it. I am not so sure. The curre
by haberman 10y ago
> When a programmer successfully emulates consciousness, every line will be deliberate, and they will know exactly how they did it.
I am not so sure. The current success of deep learning seems to be a direct counterexample to this. These techniques are yielding great success by imitating some patterns we observe in the brain, but the resulting inferences more or less defy rigorous explanation. We might fully understand the structure of a neural network but explaining the "why" behind its decisions seems to elude us.
- Koshkin 10y agoRight. A programmer will never "emulate consciousness", not directly anyway. Rather, a programmer will create a "software brain", which, then, will be subjected to all kinds of experiences, which, in turn, will result in this brain becoming conscious - gradually.
- unabst 10y agoRight. But that "software brain" will be completely deliberate. > subjected to all kinds of experiences, which, in turn, will result in this brain becoming conscious - gradually. Again, there is no evidence that "all kinds of experiences" will result in gradual emergence of consciousness from anything we have observed. To a computer, experience is just data. So we're not talking about computers. Phrases like "software brain" and "conscious machines" are ways of adding something that is not software to computers. But trust me, if we're talking about software, the programmer will know every line of their code. Now, if you want to get meta, we can consider programs that write programs. But again, the first program will be written by a human, and we will know exactly what we are doing. > resulting inferences more or less defy rigorous explanation We have written programs that take input and produce data models. There is no consciousness here. Humans take input and produce models too. But I fear you may be confusing learning with consciousness and agency. These not to be found in the code of learning machines, nor in the models they've learned. I am sorry, but it's just not there. For every abstraction there is an implementation. That is physics. With no implementation, we have metaphysics. Here, "consciousness" is the abstraction. The physics of it is the physical implementation, and is what Roger Penrose and other scientists are working on identifying. The simulation will have a coded implementation. Meaning, whether we generate it or we build something that generates it, when we have "consciousness" we will have the code that backs it. To be able to do this without any understanding of what consciousness is would be analogous to monkeys typing Shakespeare.
- miopa 10y agoBut what if intelligence is just a pattern matching ability, and consciousness arises when the entity starts discovering it's place in the patterns?
- shostack 10y agoThis reminds me of the very interesting leaps that occur in babies when they are first forming the connections for concepts for things like depth perception, distance, categorization, etc. They are bootstrapping the advanced levels of consciousness that ultimately makes them human in a sense.
- Koshkin 10y ago>no evidence Of course there is. The human "wetware" brain does just that. >know every line of code But code is there to simply provide some basic mechanisms, not the brain's structure. It is better compared to laws of chemistry or something on that level. It does not need to rewrite itself for the data structures that represent the simulated brain to evolve.
- castle-bravo 10y agoI agree that conscious machines (if such a thing is possible) will probably not be carefully designed by humans. That said, I think you should be a little more critical of deep learning. So-called neural networks are more meaningfully described as high-dimensional curve fits. When people "train" neural networks, they're fitting the parameters of a model (just like y = a*x + b is a model with a and b as parameters) to some data. The results are impressive, and sometimes downright spooky, but neural networks are closer in spirit to a curve fit in MS Excel than they are to a real brain. There is no deep why. These are just nested compositions of affine transformations and ramp functions.