Against WBE (Whole Brain Emulation)

I'm confused by the premise that "Most people agree that WBE is the first step to FAI." "Friendly AI" is, if I'm not mistake, a term invented by EY, and neither he nor the others here have been particularly in favor of WBE in the past. Did you perhaps mean AGI (artificial general intelligence)?

I had to look up what WBE stands for. You should probably define it the first time you use it.

EDIT: It's whole brain emulation, in case anyone gets to the comments without getting it.

WBE is basically porting spaghetti code to a really different architecture... it may first seem easy, but...

What comes to mind is some C64 emulators that included logic for a simulated electron beam that scanned the display... as there were games that changed the memory while it was being read in order to... be able to use more colors? I'm not sure, but C64 computers are still created by humans, while evolution had millions of years to mess our brains up with complicated molecular-level stuff.

As I see it, WBE wouldn't be an one-step achievement but rather a succession of smaller steps, building various kinds of implants, interfaces, etc, "rewriting" parts of it to have the same functionality, until we end up having a brain made out of new code, making the old, biology-based part irrelevant.

That said... I don't think WBE would solve FAI so easily. The current concept is along the lines of "if we can build a working brain without either us or it knowing how it works, that's safe". That is indeed true, but only if we can treat it as a black box all along. Unfortunately, we can't avoid learning stuff about how minds work in the process, so by the time we get the first functional WBE instance, maybe every grad student would be able to hack a working synthetic AGI together just by reading a few papers...

I don't know where you get the "most people". Many here think it is a possible step, others think it is irrelevant to GAI, and some even consider it harder than GAI. I think you may be confusing learning from neurological science and models with the more extensive Whole Brain Emulation, many do think we can learn from the former to help with GAI.

are there any good arguments against the feasibility of WBE

Against the feasibility? Heck yes. It's a ridiculously hard technical problem. Building a mind from scratch sounds much easier. Airplanes were invented in 1903 and we still don't have a scanner that can copy birds.

Storage requirements for example. There are about 10^11 neurons and 10^14 synapses. If we don't model them all, there is absolutely no guarantee that you'll get a human, let alone a specific human. And there's some news that glial cells play an important role in cognition, too, so that's another couple hundred billion cells and more connections.

Even if saying everything important about a cell or synapse only takes 10 bytes, that still a few internetworths of data to keep running in parallel. In contrast, there are plenty of optimizing tricks that you can play with something made out of code rather than opaque physical data. Even if the first seed AI is as complicated as a human brain, it could be smushed down to smaller processing requirements because it's in an easily manipulable language. So if computing power requirements end up determining which comes first, it seems quite likely that seed AI comes first.

I made a discussion post a while back trying to get a handle on how hard this problem is by looking at progress on nematode brain emulation.

Most people agree that WBE is the first step to FAI

Agree that it is the first step, or a first step? We don't know enough about developing an FAI to be able to say the former with any certainty, do we?

Hmm I don't know much about the actual feasibility of AGI, but I happen to know a bit about neurology and even if there are really powerful scanninga technique on the horizon - for example according to a researcher I recently spoke to, MRI with 10^−6 m resolution are currently available - WBE seems really hard to do. Aside for the already mentioned number of neurons and synapses (and glia), there are (according to my lectures) about 1000 different kinds of neurons, lots of different synapses, various densities of ion-channels at different locations, you have local, global and semi-global neurotransmitters, passive conductive properties of dendrites/axons differ and change over time, DNA modification in responds to some stimuli. I think you get the point. It's not impossible I guess, some things could probably be left out/compressed but still . . .

What seems (at least to me) more plausible is just that a lot of the "macroscopic tricks" (example: receptor fields could be applied when engineering AI and maybe AGI.

There are many difficulties with WBE :

1. As other people said, the storage/computing power required.

2. The scanning itself.

3. All the interactions between the brain and the rest of the body, our brain is constantly fed with input from nerves from eyes, ears, nose, the skin, even the inside of the body ... Unsettle that too much, and you're likely to drive the brain mad.

4. The chemical part : the brain stimulated by chemicals (hormones, drugs, ...) we don't know exactly if we can just model neurons and synapses (like we do in neural networks) or if we need a much lower-level (atom by atom) simulation to get a working brain, since the brain is constantly affected by various chemicals.

So... WBE is of course theoretically possible, but it seems a harder challenge to me than building an GAI "from scratch" (which is already a hard task).

A large number of the other technologies, such as microscopy, image processing, and computational neuroscience are driven by research and niche applications.

I was talking with someone about this a couple months ago, and as far as nondestructive brain imaging goes, it may be theoretically impossible. I forget the details of the argument, but the kind of resolution you would need to observe neurons is so high that the effective penetration of whatever signal you use to observe them is too small to see the whole brain. It was just an off-the-cuff Fermi estimate, though, so I wouldn't bet any probability mass on it.

If this is the case, it seems to be a reasonable argument against practical feasibility. Getting someone to trust destructive imaging techniques would be a much steeper uphill battle.

EDIT: For comparison, the roadmap expects a resolution of 5 x 5 x 50 nm. Modern CT scans get 0.2 mm resolution, according to Wikipedia. Obviously there's room for improvement, but the question is, that much?

Different required technologies have different support and drivers for developmenComputers are developed

There appears to be a cut'n'paste typo in the quote from the WBE paper quoted from. I guess because the error occurs over a page boundary.

comment moved to another thread http://lesswrong.com/lw/8k7/will_the_emulations_save_us_from_the_robots/

Given that many people consider the scenario in which WBE comes before AGI, to be safer than the converse, shouldn't we be talking about this more?

Building it on the moon would be safer in the same sense. Should we be talking about that more?

What probability do you guys assign to the likelihood that WBE comes before AGI?

Pretty low - under 1%.