Dr. David Denkenberger co-founded and is a director at the Alliance to Feed the Earth in Disasters (ALLFED.info) and donates half his income to it. He received his B.S. from Penn State in Engineering Science, his masters from Princeton in Mechanical and Aerospace Engineering, and his Ph.D. from the University of Colorado at Boulder in the Building Systems Program. His dissertation was on an expanded microchannel heat exchanger, which he patented. He is an associate professor at the University of Canterbury in mechanical engineering. He received the National Merit Scholarship, the Barry Goldwater Scholarship, the National Science Foundation Graduate Research Fellowship, is a Penn State distinguished alumnus, and is a registered professional engineer. He has authored or co-authored 156 publications (>5600 citations, >60,000 downloads, h-index = 38, most prolific author in the existential/global catastrophic risk field), including the book Feeding Everyone no Matter What: Managing Food Security after Global Catastrophe. His food work has been featured in over 25 countries, over 300 articles, including Science, Vox, Business Insider, Wikipedia, Deutchlandfunk (German Public Radio online), Discovery Channel Online News, Gizmodo, Phys.org, and Science Daily. He has given interviews on 80,000 Hours podcast (here and here) and Estonian Public Radio, Radio New Zealand, WGBH Radio, Boston, and WCAI Radio on Cape Cod, USA. He has given over 80 external presentations, including ones on food at Harvard University, MIT, Princeton University, University of Cambridge, University of Oxford, Cornell University, University of California Los Angeles, Lawrence Berkeley National Lab, Sandia National Labs, Los Alamos National Lab, Imperial College, Australian National University and University College London.
denkenberger
Yes, SFF is the longest EA application I’ve done, but shorter than I think any non-EA applications I’ve done (excluding pre-proposals and internal university money).
I ran this by a PV expert and he said there would be a lot of R&D to make this happen, but he thought the overall concept of making short-lived low embodied energy PV made sense.
The delivered column counts the output as the electricity produced, which is the one most relevant for our purposes. The primary column shows the more common LCA primary energy convention (Frischknecht et al. (2020)), which measures the thermal energy required to produce that electricity.
If the manufacture of the PV required mostly electricity, the delivered and primary would be more like a factor of 3 different. So they are finding that most of the energy required is high temperature heat, which electricity doesn’t have very much advantage in?
The table below shows the mass of each potentially-constraining element required to build the system at four deployment scales, against world reserves and resources.
Some of the units in the table didn’t render correctly.
Pumped hydro and compressed-air storage at suitable geology can come in below 1 MJ per MJ, but viable reservoirs and salt caverns are scale-limited well short of what a self-replicating economy needs.
Compressed air storage can use regular saline aquifers, like we do for storing natural gas, so I don’t think they will be scale limited.
I think this is very valuable to decompose manual jobs/tasks to see what we could already do with current robots with intelligent control. I think we could have big improvements in that control before AGI.
The number of robots needed to automate manufacturing is not large; in a rapidly growing economy the robot capital stock is small, and making robots is not a significant constraint relative to producing energy and raw materials.
US manufacturing labor is ~13 million, but one robot would displace more than one worker because manufacturing typically runs multiple shifts, so maybe 4 million robots. So that’s about 2 years delay in your model. But by then, we would have built up more manufacturing, so maybe a little longer delay, so that seems significant. But if you repurpose auto manufacturing to making robots, then you could build robots a lot faster.
Thanks—I’ll read those. And did you investigate gold and silver? In my quick analysis, I found that if we had to get as much gold and silver as we produce now from common rock, it would cost more than the entire economy. Of course we would conserve as the price increased, but gold is fairly important in electronics.
I’m glad to see this rigorous analysis of potential growth rates.
I realize you only had OECD data, but how do you think China’s growth rate would compare?
4 hours of battery storage is not nearly enough to create reliable electricity from PV.
Aluminum-wound motors and transformers are roughly 1.3x larger and heavier for the same output, acceptable for most industrial uses.
I agree on the larger volume, but as you note about power conductors, they are typically lighter weight.
A 10x economy is not possible under any assumptions about oil resources.
Unless you turn natural gas or coal into oil, which has already been commercially deployed, but it would need a lot of scale up. Also, some of the capital that consumed oil is no longer in service. And oil is used less for capital formation (smelting, electricity production) than other fossil fuels.
If the supply curve shifts right, quantity supplied increases.
I was saying for the case if managers could still only manage the same number of equivalent people. I agree that they would figure out how to manage more, but do you think they could each manage 1000 equivalent junior AI researchers?
If we already have an autonomous AI researcher, there’s a good chance the researcher takes off to ASI while policy-makers are still trying to figure out what’s doing on. Originally I said it was harder to enforce but really I think the concern is that it makes AI development go a lot faster.
Ok—faster makes more sense. But we have seen with Fable that policy-makers can act fast if they want to. Labs would probably want to use the compute to go for ASI, but they could still make a lot of money if customers paid for the compute (though of course they would need to reserve some compute to support the human AI safety researchers).
I don’t know how employment would play out. If there were an automated Junior AI researcher, then senior AI researchers could plausibly manage 10 of them each (like now) and they may lay off the Junior AI researchers if they can’t manage the automated Junior AI researchers. That would save the AI companies money, but would not really get them more research done. The total potential is millions of automated researchers, so maybe it would be possible for one human to manage 1000 automated researchers? Anyway, it seems to me that at some point, there would be mass layoffs, in which case the workers could argue that they could pivot to safety.
As for whether it is much harder to enforce if there are automated AI researchers, I don’t know. It seems like regardless, they could prohibit training of new more capable models, but I guess the labs might argue they need to train a new safer model? But that blurriness would be the case regardless of whether the researchers are human or AI. Are you saying that it’s harder to enforce a pause if progress is faster or cheaper?
There are now ‘closed loop systems’ that allow data centers to only draw water once.
But they use more energy because they don’t get the evaporative cooling to reduce the strain on the chiller (or potentially obviate the chiller).
But perhaps instead of shutting down, an AI company could reallocate 100% of its budget on some combination of safety research + global coordination to make AI development safer, and do just those things until it runs out of money. Think of how much more safety work a they could do if they dedicated all their resources to the problem!
A lot of people think we should pause at AGI, but one problem is that AI capabilities are spiky, so we will probably get powerful and dangerous capabilities even before it is human level at all tasks. So I was thinking what might actually be politically/economically feasible is pausing further development once they get an automated AI researcher, because all those AI capability researchers are not going to be happy about being laid off. So we could turn them into AI safety researchers!
So what is a mercury to lead problem?
I think that The Game: Penetrating the Secret Society of Pickup Artists claims 7 hours on average of interaction. But in the olden days, you were only supposed to date every week, so that could easily turn into weeks depending on the person.
One student, upon being told that most of the mass in the wood comes from and not the dirt in the ground, said “that’s very disturbing and I wonder how that could happen.” And that’s an MIT graduate.
Yes, and some Harvard grads thought the seasons were caused by varying distance between the Earth and the Sun. However, this source was 1987, and judging by the VHS cassette in yours, it was probably also old. So I suspect that there would greater awareness now with climate change that trees soak up CO2, and that both unis have made more of an effort to have their students know things like this because of the bad press. Also, I expect that there was some cherry-picking. However, I agree with your overall point that many well educated people don’t know basic facts about the world.
massive societal collapse (no food)
What do you think the AI would do that would cause the societal collapse?
Opening the Overton window would be great, but even endorsements of mainstream famous people like Larry King, Seth MacFarlane, Simon Cowell, Paris Hilton, and Britney Spears hasn’t seemed to help much.
Similarly, I have now said my peace about this. Violence is never the answer,
I’m not sure if it was intentional, but I appreciate the pun on saying your piece.
How many people exist who will be willing to buy at that price? Well, there are about 24 million people in the USA with a net worth of over a million dollars — about 40% of the millionaires, worldwide. As a back-of-the-envelope, order-of-magnitude guess, let’s say that there are about 50 million people who could reasonably afford Nectome’s services, that about 2% of these people die each year, and that half of those do so in a way that’s compatible with going to Oregon and getting MAiD — 500k potential clients per year. Even if only one-in-a-thousand people are open to it, philosophically, Nectome really could potentially be serving hundreds of clients per year, if they get really good at marketing. And, if they break the Overton window open, thousands per year is plausible.
I’ve run calculations like this before, and have thought, “Why are there not more cryonicists?” I think the sad reality is that many people who “should” be interested in it just have all sorts of rationalizations for their initial impression that it is weird or unnatural or could be worse than death. So I think your prior should be the rate of people already signing up for cryonics, and argue why Nectome is different. For the average person who might be interested, I don’t think it’s that different. That said, since you can fund this from life insurance with an early payout, I think it’s more affordable to people than your calculation suggests.
Somewhat related: Hanson argues in Age of Em there would be hundreds of unique ems to cover all the jobs, and they would all have a lot of training. But that is for peak performance.
Here’s a paper with islands as a natural experiments providing evidence that colonialism increased the well-being of poor countries.
That probably couldn’t be maintained for the entire expansion to Dyson Swarm, but you might be on track to get there in about a year.