Circa a week ago I posted asking whether bringing up molecular nanotechnology(MNT) as a possible threat avenue for an unfriendly artificial intelligence made FAI research seem less credible because MNT seemed to me to be not obviously possible. I was told to some extent, to put up and address the science of MNT or shut up. A couple of people also expressed an interest in seeing a more fact and less PR oriented discussion, so I got the ball rolling and you all have no one to blame but yourselves. I should note before starting, that I do not personally have a strong opinion on whether Drexler-style MNT is possible. This isn't something I've researched previously, and I'm open to being convinced one way or the other. If MNT turns out to be likely at the end of this investigation, then hopefully this discussion can provide a good resource for LW/FAI on the topic for people like myself not yet convinced that MNT is the way of future. As far as I'm concerned, at this point all paths lead to victory.
While Nanosystems was the canonical reference mentioned in the last conversation. I purchased it, then about 2/3rds of the way through this I figured Engines of Creation was giving me enough to work with and cancelled my order. If the science in Nanosystems is really much better than in EoC I can reorder it, but I figured we'd get started for free. 50 bucks is a lot of money to spend on an internet argument.
Before I begin I would like to post the following disclaimers.
1. I am not an expert in many of the claims that border on MNT. I did work at a Nanotechnology center for a year, but that experience was essentially nothing like what Drexler describes. More relevantly I am in the process of completing a Ph.D. in Physics, and my thesis work is on computational modeling of novel materials. I don't really like squishy things, so I'm very much out of my depth when it comes to discussions as to what ribosomes can and cannot accomplish, and I'll happily defer to other authorities on the more biological subjects. With that being said, several of my colleagues run MD simulations of protein folding all day every day, and if a biology issue is particularly important, I can shoot some emails around the department and try and get a more expert opinion.
2. There are several difficulties in precisely addressing Drexler's arguments, because it's not always clear to me at least exactly what his arguments are. I've been going through Engines of Creation and several of his other works, and I'll present my best guess outline here. If other people would like to contribute specific claims about molecular nanotech, I'll be happy to add them to the list and do my best to address them.
3. This discussion is intended to be scientific. As was pointed out previously, Drexler et al. have made many claims about time tables of when things might be invented. Judging the accuracy of these claims is difficult because of issues with definitions as mentioned in the previous paragraph. I'm not interested in having this discussion encompass Drexler's general prediction accuracy. Nature is the only authority I'm interested in consulting in this thread. If someone wants to make a Drexler's prediction accuracy thread, they're welcome to do so.
4. If you have any questions about the science underlying anything I say, don't hesitate to ask. This is a fairly technical topic, and I'm happy to bring anyone up to speed on basic physics/chemistry terms and concepts.
I'll begin by providing some background and highlighting why exactly I am not already convinced that MNT, and especially AI-assisted rapid MNT is the future, and then I'll try and address some specific claims made by Drexler in various publications.
Conservation of energy:
Modelling is hard:
Solving the Schrodinger equation is essentially impossible. We can solve it more or less exactly for the Hydrogen atom, but things get very very difficult from there. This is because we don't have a simple solution for the three-body problem, much less the n-body problem. Approximately, the difficulty is that because each electron interacts with every other electron, you have a system where to determine the forces on electron 1, you need to know the position of electrons 2 through N, but the position of each of those electrons depends somewhat on electron 1. We have some tricks and approximations to get around this problem, but they're only justified empirically. The only way we know what approximations are good approximations is by testing them in experiments. Experiments are difficult and expensive, and if the AI is using MNT to gain infrastructure, then we can assume it doesn't already have the infrastructure to run its own physics lab.
A factory isn't the right analogy:
The discussion of nanotechnology seems to me to have an enormous emphasis on Assemblers, or nanofactories, but a factory doesn't run unless it has a steady supply of raw materials and energy resources both arriving at the correct time. The evocation of a factory calls to mind the rigid regularity of an assembly line, but the factory only works because it's situated in the larger, more chaotic world of the economy. Designing new nanofactories isn't a problem of building the factory, but a problem of designing an entire economy. There has to be a source of raw material, an energy source, and means of transporting material and energy from place to place. And, with a microscopic factory, Brownian motion may have moved the factory by the time the delivery van gets there. This fact makes the modelling problem orders of magnitude more difficult. Drexler makes a big deal about how his rigid positional world isn't like the chaotic world of the chemists, but it seems like the chaos is still there; building a factory doesn't get rid of the logistics issue.
The reason we can't solve the n-body problem, and lots of other problems such as the double pendulum and the weather is because it turns out to be a rather unfortunate fact of nature that many systems have a very sensitive dependence on initial conditions. This means that ANY error, any unaccounted for variable, can perturb a system in dramatic ways. Since there will always be some error (at the bare minimum h/4π) this means that our AI is going to have to do Monte Carlo simulations like the rest of us smucks and try to eliminate as many degrees of freedom as possible.
The laws of physics hold
I didn't think it would be necessary to mention this, but I believe that the laws of physics are pretty much the laws of physics we know right now. I would direct anyone who suggests that an AI has a shot at powering MNT with cold fusion, tachyons, or other physical phenomena not predicted by the standard model to this post. I am not saying there is no new no physics, but we understand quantum mechanics really well, and the Standard Model has been confirmed to enough decimal places that anyone who suggests something the Standard Model says can't happen is almost certainly wrong. Even if they have experimental evidence that is supposed to 99.9999% percent correct.
Drexler's claims about what we can do now with respect to materials science in general are true. This should be unsurprising. It is not particularly difficult to predict the past. Here are 6 claims he makes that we can't currently accomplish which I'll try and evaluate:
- Building "gear-like" nanostructures is possible (Toward Integrated Nanosystems)
- Predicting crystal structures from first principles is possible (Toward Integrated Nanosystems)
- Genetic engineering is a superior form of chemical synthesis to traditional chemical plants. (EoC 6)
- "Biochemical engineers, then, will construct new enzymes to assemble new patterns of atoms. For example, they might make an enzyme-like machine which will add carbon atoms to a small spot, layer on layer. If bonded correctly, the atoms will build up to form a fine, flexible diamond fiber having over fifty times as much strength as the same weight of aluminum." (EoC 10)
- Proteins can make and break diamond bonds (EoC 11)
- Proteins are "programmable" (EoC 11)
2. True. This isn't true yet, but should be possible. I might even work on this after I graduate, if don't go hedge fund or into AI research.
3. Not wrong, but misleading. The statement "Genetic engineers have now programmed bacteria to make proteins ranging from human growth hormone to rennin, an enzyme used in making cheese." is true in the same sense that copying and pasting someone else's code constitutes programming. Splicing a gene into a plasmid is sweet, but genetic programming implies more control than we have. Similarly, the statement: "Whereas engineers running a chemical plant must work with vats of reacting chemicals (which often misarrange atoms and make noxious byproducts), engineers working with bacteria can make them absorb chemicals, carefully rearrange the atoms, and store a product or release it into the fluid around them." implies that bacterial synthesis leads to better yields (false), that bacteria are careful(meaningless), and implies greater control over genetically modified E.Coli than we have.
4a. False. Flexible diamond doesn't make any sense. Diamond is sp3 bonded carbon and those bonds are highly directional. They're not going to flex.. Metals are flexible because metallic bonds, unlike covalent bonds, don't confine the electrons in space. Whatever this purported carbon fiber is, it either won't be flexible, or it won't be diamond.
4b. False. It isn't clear that this is even remotely possible. Enzymes don't work like this. Enzymes are catalysts for existing reactions. There is no existing reaction that results in a single carbon atom. That's an enormously energetically unfavorable state. Breaking a single carbon carbon double bond requires something like 636 kJ/mol (6.5eV) of energy. That's roughly equivalent to burning 30 units of ATP at the same time. How? How do you get all that energy into the right place at the right time? How does your enzyme manage to hold on to the carbons strongly enough to pull them apart?
5. "A flexible, programmable protein machine will grasp a large molecule (the workpiece) while bringing a small molecule up against it in just the right place. Like an enzyme, it will then bond the molecules together. By bonding molecule after molecule to the workpiece, the machine will assemble a larger and larger structure while keeping complete control of how its atoms are arranged. This is the key ability that chemists have lacked." I'm no biologist, but this isn't how proteins work. Proteins aren't Turing machines. You don't set the state and ignore them. The conformation of a protein depends intimately on its environment. The really difficult part here is that the thing it's holding, the nanopart you're trying to assemble is a big part of the protein's environment. Drexler complains around how proteins are no good because they're soft and squishy, but then he claims they're strong enough to assemble diamond and metal parts. But if the stiff nanopart that you're assembling has a dangling carbon bond waiting to filled then it's just going to cannibalize the squishy protein that's holding it. What can a protein held together by Van der Waals bonds do to a diamond? How can it control the shape it takes well enough to build a fiber?
6. All of these tiny machines are repeatedly described as programmable, but that doesn't make any sense. What programs are they capable of accepting or executing? What set of instructions can a collection of 50 carbon atoms accept and execute? How are these instructions being delivered? This gets back to my factory vs. economy complaint. If nothing else, this seems an enormously sloppy use of language.
Some things that are possible
I think we have or will have the technology to build some interesting artificial inorganic structures in very small quantities, primarily using ultra-cold, ultra-high-vacuum laser traps. It's even possible that eventually we could create some functional objects this way, though I can't see any practical way to scale that production up.
"Nanorobots" will be small pieces of metal or dieletric material that we manipulate with lasers or sophisticated magnetic fields, possibly attached to some sort of organic ligand. This isn't much of a prediction, we pretty much do this already. The nanoworld will continue to be statistical and messy.
We will gain some inorganic control over organics like protein and DNA (though not organic over inorganic). This hasn't really been done yet that I'm aware of, but stronger bonds>weaker bonds makes sense. I think there are people trying to read DNA/proteins by pushing the strands through tiny silicon windows. I feel like I heard a seminar along those lines, though I'm pretty sure I slept through it.
That brings me through the first 12 pages of EoC or so. More to follow. Let me know if the links don't work or the formatting is terrible or I said something confusing. Also, please contribute any specific MNT claims you'd like evaluated, and any resources or publications you think are relevant. Thank you.