Experience curves, large populations, and the long run

If our civilization avoids catastrophe, will we generally be able to advance technology to close to physical limits, match or exceed observed biological abilities, and colonize the universe? Or will we be stuck in a permanent technological plateau before that, reaching a state where resources are insufficient to make the breakthroughs to acquire resources and continue progress? Experience curves, which forecast cost improvements in technology as a function of cumulative production, are a popular tool for technological forecasting and perform relatively well compared to other statistical approaches, although they inevitably have significant and increasing error as one extrapolates further. If we consider the maximum energy resources and population of the Earth, combined with the potential lifetime of human civilization (absent existential catastrophe), experience curves extrapolate to immense technological improvements (constrained by physical limits), more than sufficient to colonize the rest of the solar system, which in turn yields a billionfold increase in potential scale to fund interstellar colonization. Such extrapolation would suggest matching or exceeding biological capacities we currently lack, such as the computational efficiency of brain tissue, or the rapid energy payback of algae as solar energy and manufacturing devices.

Terrestrial solar energy could eventually support extremely large economies and populations

If we are interested in whether Earth's civilization could ever reach various technological milestones, or long run economic output and populations that Earth could sustain, the terrestrial solar energy resource can provide helpful information. Using efficiencies of the best lab solar cells, covering the earth with solar panel platforms could provide a thousand times as much energy as our civilization currently uses, and more than a hundred times the production of the terrestrial biosphere. Historical experience curve and cost data suggest this energy supply could be much cheaper than current energy prices, although with increasing overhead costs as less desirable areas such as ocean platforms and less sunny lands are used. Energy payback times are already under a year for energy-efficient solar in good locations, and have been falling along with prices, so solar energy can power its own construction, and with advanced robotics and AI might eventually grow at extremely rapid rates. 

The High Frontier, space based solar power, and space manufacturing

The High Frontier, published in 1976 by Gerard K O'Neill, lays out a vision of economically profitable space colonization in artificial orbital habitats, and guessed (while disclaiming it as prediction) that it was "unlikely" that a space community would not be established in 30 years. I was interested in why those forecasts were made, and why they turned out wrong, as data points for thinking about forecasting future technological developments. The book lays out a case that in the long run space habitats can support immensely larger populations and wealth than the planets in the Solar System. In the medium term it argued that a government program to invest hundreds of billions of dollars to build space factories and Lunar mining facilities would eventually let them produce solar power a few times more efficiently than terrestrial solar power production, and that this would drive space colonization. This seems to have been doomed for multiple reasons, radically underestimating launch costs and likely fatally underestimating the increased costs of space production (to be paid for out of a 2-3x improvement in solar radiation), as well as requiring immense government funding. As a means to improve solar power cost-effectiveness, it would have been far inferior to solar cell R&D. Subsequent orders-of-magnitude improvement in launch costs per kW of solar cells make space-based solar more plausible than at the time, but the challenge of competing with terrestrial solar and especially terrestrial scale economies of industry remains high.

Financial returns of interstellar colonization for the sedentary

Summary: In thinking about the likelihood of interstellar colonization by our civilization, or possible alien civilizations, one question is motivation: how strong are the incentives to do so? If moderately fast self-replicating probes can build infrastructure in a new solar system and send back information or material goods requiring extensive experimentation or computation to produce, then even at current market interest rates a colonization mission could deliver extremely high return on investment. For patient long-lived decision-makers with strong property rights or stability, returns could be overwhelming.

How immigration could make AMF more cost-effective

Summary: charities that save the lives of the global poor have more economic impact than one might think because a portion of the very poor may emigrate to other countries and enormously increase their productivity, and this portion may greatly increase if some developed countries open their borders.

Open borders in (at least) one (developed) country

Over at the Open Borders Blog Vipul Naik and co-bloggers have discussed an enormous variety of arguments for and against a system of open borders. Immigrants from poor countries earn much more when they move to rich countries, a "place premium." If this place premium is unaffected by very high levels of immigration, then open borders could greatly increase world GDP and eliminate almost all absolute poverty. Refugees would be guaranteed a place to escape bad conditions, governments would face incentives to improve their policies to keep their population from leaving.

So immigration is very much worth a look for those interested in effective altruism. This post covers a point that seems to me to have been relatively neglected among open borders advocates (although it has been discussed more by advocates of charter cities): it seems most of the expected benefits do not require a global system of open borders, just open borders in one or a few countries with the right properties, a much easier goal.

Can catch-up growth take us to the stars?

Will our civilization ever be able to colonize the stars and avert astronomical waste? Will we create computer programs more intelligent and energy-efficient than ourselves, enabling much larger and smarter sapient populations? We don't know exactly how hard it will be to engineer interstellar probes, or build AI, and we probably won't be sure until we actually do so.

However, we can shed some light on the question of whether humanity will ever be able to colonize the stars by asking how existing methods and technologies could increase our capacities, if they were deployed widely and to their limits. Here's a thought experiment: if we imagine that we were magically frozen in roughly our current technological regime for a time, long enough for Malthusian population growth and competition, how much would our economic and scientific production grow? By Malthusian, I mean that population would keep increasing until food costs started to price people out of reproduction, with higher-income folk reproducing more, and institutions that lead to high incomes spreading through migration, imitation or conquest.

Below the fold, I consider several dimensions where existing systems could simply be scaled up to increase global output and R&D: bringing poor countries up to the standards of rich countries, increasing population, and increasing average human capital within countries to near the level of the best-endowed households. Collectively, I estimate they could increase global R&D efforts by more than one hundred fold.

Philosophers vs economists on discounting

Temporal discounting is not about time
Economists doing cost-benefit analysis normally make use of temporal discounting, i.e. benefits further in the future count for less than those nearer to the present. In part this is done to reflect the availability of positive investment returns, but normally analysis also include an additional element of pure temporal preference.

Say that I set up a sealed habitat for some plants and cute bunny rabbits. The rabbits are placed in suspended animation, and the habitat is rocketed out of the Solar System by an automated spacecraft which will never return to interact with our world again. At a predesignated time, the rabbits will be revived and go on to live happy lives in the sealed habitat for a time and then die. With significant pure temporal preference this spacecraft is much more valuable if it is set to revive the isolated rabbits after 5 years rather than 50.

Indeed, economists typically make use of constant exponential discounting, e.g. reducing the valuation of benefits by 3% per year. At a 3% annual discount rate the value of future benefits will be cut by more than half every 23 years. After 230 years a good would be valued at less than a thousandth of an immediate counterpart.   But to most people the change in activation time does not make such an overwhelming difference. Further, constant exponential discounting makes strong distinctions between different far-future periods: benefits received in 1 million years are still more than a thousand times as valuable as benefits received in 1,000,230 years.

But real humans mostly don't care about such distinctions. A difference of a few centuries added onto a  million years is a negligible change in time: in either case they lie far beyond the current era and the proportional change is small. Favoring the earlier time for a thousandfold reduction in the goods achieved seems absurd in that context. Humans may be impatient within our own lives, care more about our children than distant descendants, and so forth, but the constant exponential discounting framework just doesn't make sense of our attitudes towards the further future.

Because of cases like this philosophers tend to reject the idea of pure temporal preference for social cost-benefit analysis, e.g. with respect to climate change, and often critique economists for persisting in making use of it. But economists are not fools, and the reasons why so many continue to do so are worth thinking about.