Abstract
Here, I present GDP (per capita) forecasts of major economies until 2050. Since GDP per capita is the best generalized predictor of many important variables, such as welfare, GDP forecasts can give us a more concrete picture of what the world might look like in just 27 years. The key claim here is: even if AI does not cause transformative growth, our business-as-usual near-future is still surprisingly different from today.
Results
In recent history, we’ve seen unprecedented economic growth and rises in living standards.
Consider this graph:[1]
How will living standards improve as GDP per capita (GDP/cap) rises? Here, I show data that projects GDP/cap until 2050. Forecasting GDP per capita is a crucial undertaking as it strongly correlates with welfare indicators like consumption, leisure, inequality, and mortality. These forecasts make the future more concrete and give us a better sense of what the world will look like soon. Abstract thoughts about utopia generate little emotional energy; I find these forecasts more plastic and informative, because GDP/cap is highly predictive of welfare.[2] GDP/cap’s generalized predictive power helps us paint a more vivid picture of what the world will look like soon. The business-as-usual near future suggested by the data below could be seen as a soft lower bound on how much the world will change. And yet, this world still seems radically different from today.
Since the figures below are adjusted for purchasing power parity (PPP), you can compare the GDP/cap of a poorer country in 2050 with the GDP/cap of a richer country in 2020. For instance, between now and 2050, China’s GDP/cap will go from $19k to $43k, which is similar to France’s today. And so, by 2050, 1.3B Chinese people might enjoy a lifestyle not dissimilar to that of a typical French person today.
These GDP/cap are ~3x[3] higher than the median (i.e. typical) income, due to income inequality. Instead of downward adjusting them in our head we can also read them as an approximation of the typical combined consumption three person household.[4] And so, we can still look at these figures and imagine the median household income in Japan today and in China in 2050 to be ~$40k.
2020 | 2024 | 2030 | 2040 | 2050 | |||||||||
Pop. | GDP | GDP/ cap | GDP/ cap | Pop. | GDP/ cap | GDP | Pop. | GDP/ cap | GDP | Pop. | GDP/ cap | GDP | |
US | 334M | $20T | $60K | $68K | 356M | $66K | $23T | 374M | $76K | $28T | 389M | $88K | $34T |
Netherlands | 17M | $1T | $54K | $59K | 18M | $61K | $1T | 18M | $71K | $1T | 18M | $85K | $1T |
S. Arabia | 34M | $2T | $55K | $56K | 39M | $70K | $3T | 43M | $86K | $4T | 46M | $102K | $5T |
Germany | 80M | $4T | $52K | $54K | 79M | $59K | $5T | 77M | $69K | $5T | 75M | $82K | $6T |
Australia | 26M | $1T | $52K | $53K | 28M | $58K | $2T | 31M | $67K | $2T | 33M | $77K | $3T |
S. Korea | 51M | $2T | $42K | $47K | 53M | $50K | $3T | 52M | $59K | $3T | 51M | $70K | $4T |
Canada | 38M | $2T | $48K | $48K | 40M | $53K | $2T | 42M | $61K | $3T | 44M | $70K | $3T |
UK | 67M | $3T | $45K | $47K | 70M | $52K | $4T | 73M | $61K | $4T | 75M | $71K | $5T |
France | 66M | $3T | $44K | $48K | 68M | $50K | $3T | 70M | $56K | $4T | 71M | $66K | $5T |
Japan | 125M | $5T | $40K | $43K | 120M | $47K | $6T | 114M | $54K | $6T | 107M | $63K | $7T |
Poland | 38M | $1T | $31K | $39K | 37M | $40K | $2T | 35M | $53K | $2T | 33M | $63K | $2T |
Spain | 46M | $2T | $39K | $42K | 46M | $47K | $2T | 46M | $53K | $2T | 45M | $61K | $3T |
Malaysia | 32M | $1T | $32K | $31K | 36M | $42K | $2T | 39M | $54K | $2T | 41M | $69K | $3T |
Italy | 60M | $2T | $39K | $45K | 59M | $43K | $3T | 58M | $48K | $3T | 57M | $55K | $3T |
Turkey | 82M | $2T | $26K | $35K | 88M | $34K | $3T | 93M | $43K | $4T | 96M | $54K | $5T |
Russia | 143M | $4T | $28K | $31K | 139M | $34K | $5T | 133M | $45K | $6T | 129M | $55K | $7T |
China | 1403M | $27T | $19K | $20K | 1416M | $27K | $38T | 1395M | $34K | $47T | 1348M | $43K | $58T |
Thailand | 69M | $1T | $19K | $19K | 68M | $25K | $2T | 66M | $34K | $2T | 62M | $45K | $3T |
Argentina | 46M | $1T | $22K | $21K | 49M | $27K | $1T | 53M | $34K | $2T | 55M | $43K | $2T |
Mexico | 135M | $3T | $19K | $21K | 148M | $25K | $4T | 158M | $32K | $5T | 164M | $42K | $7T |
Colombia | 50M | $1T | $16K | $16K | 53M | $21K | $1T | 55M | $28K | $2T | 55M | $38K | $2T |
Iran | 83M | $2T | $21K | $17K | 89M | $27K | $2T | 91M | $35K | $3T | 92M | $42K | $4T |
Indonesia | 272M | $4T | $14K | $13K | 295M | $18K | $5T | 312M | $25K | $8T | 322M | $33K | $11T |
Brazil | 216M | $3T | $15K | $17K | 229M | $19K | $4T | 236M | $25K | $6T | 238M | $32K | $8T |
S. Africa | 57M | $1T | $14K | $13K | 60M | $19K | $1T | 63M | $28K | $2T | 66M | $39K | $3T |
Egypt | 101M | $1T | $13K | $14K | 117M | $17K | $2T | 134M | $23K | $3T | 151M | $29K | $4T |
Vietnam | 98M | $1T | $8K | $12K | 105M | $12K | $1T | 110M | $19K | $2T | 113M | $28K | $3T |
India | 1389M | $12T | $8K | $8K | 1528M | $13K | $20T | 1634M | $18K | $30T | 1705M | $26K | $44T |
Philippines | 108M | $1T | $10K | $10K | 124M | $13K | $2T | 137M | $17K | $2T | 148M | $22K | $3T |
Bangladesh | 170M | $1T | $5K | $8K | 186M | $7K | $1T | 197M | $11K | $2T | 202M | $15K | $3T |
Pakistan | 208M | $1T | $6K | $6K | 245M | $8K | $2T | 279M | $10K | $3T | 310M | $14K | $4T |
Nigeria | 207M | $1T | $6K | $5K | 263M | $7K | $2T | 327M | $9K | $3T | 399M | $11K | $4T |
Mean/Sum | 5851M | $116T | $28K | 6251M | $34K | $155T | 6545M | $42K | $202T | 6740M | $51K | $259T |
Discussion
In the GDP/cap forecasts above, one thing jumps out: in just 27 years, the world might be fundamentally changed. I find it illustrative to imagine yourself being 27 years older in a world where:
China’s GDP is the largest in the world, and India’s is as big as the US’s. Indonesia’s economy is the fourth largest.
Some large poorer countries like Nigeria still have relatively low incomes (~$10k/cap). India’s GDP/cap will grow from $8k to $26k (like Mexico today) and China’s from $19k to $43k (like Japan today).
A billion people in big rich countries (e.g. US, Western Europe) will be as rich as the very few millions of people living in small very rich countries today (~$80k/cap like in Switzerland, Norway).[5] Relative to population, these countries might have big influence on the world via science (where rich countries have more scientific papers per person[6]), or aid (e.g. the UK’s aid budget is only 2x that of Norway’s despite a 10x larger population[7]).
As world GDP doubles, the global average GDP/cap also doubles from ~$12k to ~$25k, which is still fairly poor, but getting towards an income that frugal people can live on in rich countries. Most humans will have relatively good healthcare, education, and travel, and high-quality food, work opportunities, and access to global knowledge. The recent book ‘The World in 2050’[8] argues that in 2050, two-thirds of the world’s population will be middle class or rich.
A richer world might also have:[9]
lower birth rates and fewer people
more democracy
more gender equality and other social and political rights
greater life satisfaction
enhanced social trust
Generally, in 2050 we should expect the wealth gap between richer and poorer countries to be smaller. Poorer countries have been catching up with richer ones since the ’90s[10] (but see[11]). They grow faster than rich countries because of fast catch-up or ‘copy-and-paste’ growth, whereas richer countries at the frontier can’t grow as fast anymore since ideas are getting harder to find. This leads to convergence in countries’ wealth. Looking at this in action: just 27 years ago, Lithuania’s and Estonia’s GDP/cap (PPP-adjusted) were ~⅓ of Japan’s, but, surprisingly, now they’re the same.[12] We might be surprised again in 27 years. Crucially, the changes ahead seem radically more dramatic than the changes between 27 years ago and now.
Values and Culture
What will people’s values be in 2050? Since 1980, the West has moved away from ‘obedient values’ towards ‘emancipative values’ and became more internally homogenous.[13] Overall, the world is moving towards Western values, but non-Western nations are adopting different values at different speeds. Concretely, nations are de-emphasizing religion and moving from valuing obedience to valuing independence relatively quickly, but they are slower to adopt Western secular-rational and self-expression values, such as beliefs about homosexuality, abortion, divorce, prostitution, euthanasia, childhood obedience, and suicide. This leads to convergence of values in some areas and divergence in others.[14]
Much of the variation in values between societies can be explained by GDP/cap differences and boils down to two broad dimensions:[15]
Traditionalist vs secular-rational: Traditionalists value their country, god, authority, obedience, and marriage. As countries’ wealth increases, citizens’ sense of existential security increases, moving them towards secular-rational values.
Survival vs self-expression: Survival values prioritize security over liberty. Those with survival values tend to be more homophobic, uninterested in political action, distrustful of outsiders, and less happy. As people transition from industrial to knowledge societies, their sense of agency increases and they move towards self-expression values.
Since richer people tend to favor secular-rational and self-expression values over traditionalist and survivalist values, we should expect people in 2050 to be more secular and more interested in self-expression than people today.
GDP growth has been argued to lead to ‘Greater opportunity, tolerance of diversity, social mobility, commitment to fairness, and dedication to democracy.’[16] (but also more meat consumption[17]).
In 2050, people will be older, on average. From 1970 to 2022, the global median age has already increased from 20 to 30 years; it’s projected to further increase to 36 by 2050. Unexpectedly, Chinese people will be older than people in the US and the EU.[18],[19] People become slightly more conservative as they age.[20]
In ‘The World in 2050’, McRae argues that ideas will flow more from east to west. China and other Asian nations’ technological advancements will contribute to broader ‘Easternisation’, signifying a global power shift toward the East, just as the world was Europeanized in the 19th century and Americanized in the 20th century. Now, in the 21st century, due to fast catch-up and population growth, the world is being ‘asianized’[21]).
McRae also claims that the anglosphere will become even more important: English-speaking countries will make up 40% of the world’s GDP, and populous countries on many continents will be English-speaking (Americas: US; Africa: Nigeria; Asia: India; Oceania: Australia; Europe: British Isles).
Growth could be much faster
As mentioned above, this data offers a soft lower bound on how much the world could change over the next 26 years. In contrast, however, some have speculated that future growth could be extremely fast. For example, MacAskill writes:
‘Given that growth rates have increased 30x since the agricultural era, it’s not crazy to think that they might increase 10x again; but if they did, the world economy would double every 2.5 years.’[22]
Or relatedly, Karnovsky’s ‘Most Important Century’ hypothesis[23] claims:
The far future is very unfamiliar and could come surprisingly fast.
AI might drive a productivity boom this century that could advance AI even further and lead to a long-lasting, galaxy-wide civilization that could be anything from very utopian to very dystopian.
We might shape this transition and massively impact many future people, if we can make sense of the situation enough to find helpful actions. But we aren’t ready for this.
Despite these seemingly ‘too wild to take seriously’ claims, there are many reasons we could be living in wild times, and we should be ready for anything.
But here, in the business-as-usual near-future scenario, nothing has to go ‘zoom’; this ‘can go on’, perhaps with only modest innovation, even without a transformative AI productivity boom and even if ideas are getting harder to find[24] or Chinese growth slows down.[25],[26] Such a future might even be recognizable to us today because we know what rich countries look like.
I am not arguing that the business-as-usual scenario is more likely than a transformative AI scenario that makes the world economy double every 2.5 years—I am merely making a weaker claim by suggesting that this ‘lower bound’ world is already surprisingly different from today (we could call it wild). Indeed, it might be this intermediate step of continued ‘business as usual’ growth that will lead to transformative AI (see below). This means that GDP/cap projections can also help us get a better sense of what the world could look like in the lead-up to transformative AI. And we have a better sense of how far the world will change, since we know how countries changed when they went from $10k to $40k per capita GDP. Experts suggest that there’s more than a 10% chance of transformative AI by 2036 and a ~50% chance by 2060.[27] In the absence of catastrophes, it seems like that the inverse probability − 50% chance that we will be in live in this non-TAI world until 2060.
Implications for AI
GDP forecasts inform forecasts of global challenges (e.g. climate models depend on growth).[29] For instance, both OpenPhil and Epoch estimate that the most expensive AI training run will reach some limit based on economic constraints (i.e. 1% of US GDP).[30] I’ll now discuss how AI might influence future GDP/cap figures, and vice versa.
AI causes growth: Most top economists think that AIs such as ChatGPT have a measurable impact on national innovation,[31] and many agree that AI will substantially boost EU/US per capita income over the next 30 years—perhaps more than the internet.[32],[33] Forecasts suggest that AI may increase the US growth rate by 0.6-3.6% until 2040[34] and annual global GDP by 7%.[35] Other economists argue against this and estimate an upper bound on GDP gains might be more modest at ~1.7% over the next 10 years.[36]
Growth might speed up AI development: If India’s GDP/cap really grows from $8k to $26k (equivalent to Russia’s today) and China’s from $19k to $43k (equivalent to Japan’s today), and if India and China have, relative to their population, as many researchers as Russia and Japan do today, then that would double today’s global research force of 10M.[37] Demographics suggests that China will have ~11M college graduates of which ~half were STEM graduates per year until 2040, resulting in ~80M new STEM workers, and then decline due to falling fertility (cf. the US has a total of 16M graduates).[38]
Global R&D spending is currently ~$1T[39], and this might double if GDP more than doubles. Until 2015, the percentage of GDP spent on R&D was roughly constant at ~2%, but it’s now 2.5%.[40] Even if returns to research diminish and new ideas are getting harder to find,[41] more funding might still speed up research effectively. Doubling the number of workers also increases the rate of idea production, and thus innovation. The non-rivalry of ideas means that someone can use an idea without impinging on someone else’s use of that idea (e.g. your use of the chain rule doesn’t prevent other people from using the chain rule). And so for R&D, doubling the inputs to production more than doubles output, as we adopt innovations created by others. Surprisingly, this effect is very large even if new ideas are getting much harder to find.[42]
A recent Epoch report[43] argues that the mid-20th century economic slowdown follows from the standard economic growth model and the demographic transition, which decoupled population growth from economic growth, leading to declining fertility and growth rates. In contrast, AI workforces can expand rapidly, as hardware manufacturing is not constrained like human population growth, and software can be copied cheaply, which allows the ‘population’ of AI workers to grow and innovate at the same time. Unless AI-driven growth is slowed, AI labor might increase the speed of growth a lot until physical bottlenecks stop this at very high levels of growth by current standards.
The three main first-order inputs for AI progress are:[44]
training data
compute
algorithmic efficiency
Doubling the global research force will likely mean more scientists and research engineers working on improving algorithmic efficiency and driving down prices for compute. Globally, ~2% of World ‘GDP’ or ~$2.4T/year will be spent on all R&D (~20% is spent on basic R&D, which has increased over time) [45],[46],[47] As a rule, the richer the country, the higher the share of GDP it spends on R&D.[48] For instance, US R&D is 3% of GDP.[49] The EU aims to increase combined public and private investment in R&D to 3.5% of GDP by 2025.[50] The UK wants to increase it to 2.4% of GDP by 2027.[51] (see roadmap[52]). NATO spends more than half of the ~$2T spent on the military globally.[53] NATO countries have agreed to spend 2% of GDP on defense by 2024; at least 20% of the 2% target should be spent on major equipment, including related military R&D. These international agreements are pegged to GDP. This means that their budgets (e.g. military, research) are coupled so that they increase in lockstep with GDP. If we grow GDP, which economies optimize for,[54] we automatically increase these budgets, which creates risks from emerging technologies like synthetic biology and AI. These dynamics are relevant to the principle of differential technological development.[55]
Will growth slow?
‘Before the Industrial Revolution, it took many centuries for the world economy to double in size; now it doubles every twenty-five years [...] [Over the last fifty years, global GDP / person grew by 2% / year, and all major geographic areas are experiencing significant growth. Growth economists surveyed thought that this trend would stay broadly the same, at 2.1% / year]’[56]
World GDP growth seems to be slowing down from ~5% per year in the 1960′s, to ~4% in the 70s, to ~3% in ’80s, ’90s, ’00s, to ~2.5% in the 2010s. I naively extrapolated this trend[57] and found ~2% in 2030 and 1% in 2050:
This trend might continue, albeit more gradually:[58]
By 2027 GDP/cap growth in the median rich country will be <1.5% a year. In some countries, such as Canada and Switzerland, it might be ~0%.[59] Forecasts predict that growth will continue to slow for ‘structural reasons such as aging populations, shifts from goods to services, slowing innovation, and debt.’[60] It might also be because scientific progress is slowing.[61] IT–related productivity increases explain 75% of all recent US productivity growth,[62] with similar results globally.[63]
While IT, new tech and an interconnected world may accelerate growth further, the effect might not be so huge: true, while big ideas advance the knowledge frontier, which transformed the West from 1870-1970, now growth has slowed (cf The Great Stagnation), and progress is harder with fewer low-hanging fruits, more complex knowledge and societal stagnation.[64]
But even if GDP percentage growth slows, wellbeing growth can still speed up, for two reasons:
The dollar GDP/capita growth rate goes up. Even if we adjust for inflation, Americans had ~$600 more every year in the 60s, but now have ~$900 more per year in the 2010s.[65]
The next $1k/cap increase in a country at $10k/cap is worth 10x as much as in a country with $100k/cap, because, the utility gained from increasing consumption from $10k to $11k is much greater than the utility gained from increasing consumption from $100k to $101k, even though the absolute dollar amounts are the same.[66] As more countries experience catch-up growth and lift large populations out of poverty, the total utility experienced by the world’s population could increase a lot, even if the overall rate of global growth slows, since utility gains from improving living standards at lower levels of income are much larger than the utility gains from equivalent absolute increases at higher levels of income.
Methods
I used three datasets for this analysis: PwC’s 2017 simplified Solow growth model, Gapminder’s 2021 model, and Goldman Sachs’ 2022 model.
The main source is PwC’s 2017[67] simplified Solow growth model, which takes into account demographics, human capital like education, growth in the physical capital stock, and technological progress, which drives improvements in total factor productivity (TFP) adjusted (TFP roughly gauges if we get more efficient and not just use more labor).
Gapminder’s 2021 model uses IMF forecasts until 2026, and then assumes that all countries converge to a common global growth rate of 2% per year. Correlations between their forecasts and PwC’s are high (>.9), but with some differences; for example, GapMinder estimates that in 2050 India’s GDP will be $28T (with a GDP/cap of $17K), while PwC’s model estimates $44T ($26K).[68] In the last column in the spreadsheet, I averaged the two models for 2050.
Goldman Sachs’ 2022 model uses a simple Cobb-Douglas model to estimate real GDP (per capita). Correlations between this model and the previous two are high (>.9). But what jumps out is that real GDP growth lags quite far behind PPP-adjusted growth. For instance, China’s real GDP/cap in 2050 is only $25K (compared to $43k PPP-adjusted, similar to Japan’s today), which isn’t even as high as Korea’s today ($29K). Put differently, the difference between real and PPP-adjusted GDP/cap means that (for instance) for China, its population in 2050 might have a similar quality of life to Japan’s today, but even by 2050, they might not be able to afford as many imports as Koreans today.
‘Persistence’ of growth
As always, note that these models are very crude and should not be taken literally, but they’re preferable to leaving our assumptions about the future unarticulated, fuzzy, and vague.It is better to be wrong than vague, and to state explicit assumptions that can be questioned and falsified (as the common aphorisms in statistics go: ‘Truth will sooner come out of error than from confusion’, ‘All models are wrong, but some are useful’, ‘You’re not even wrong’, ‘It is better to be roughly right than precisely wrong’, ‘Better clear than clever’, etc.). So, our models might be off, but they help us think through relevant considerations and formalize our intuitions. This very much applies here, since these models will very likely be off.
Some argue that it’s hard to forecast GDP[69] and population growth[70], despite knowing all essential variables. But others show that, strikingly, some growth might be surprisingly persistent: in many rich countries, GDP/cap from 100 years ago predicts GDP/cap today well within a few percentage points, as average growth is usually ~2%.[71]
Relatedly, even though GDP doesn’t measure welfare perfectly, it is one of the best predictors of welfare.[72] See also further links on GDP as a proxy for welfare below.
Future Research
Here are some research questions in this area that might be useful:
Improve GDP forecasts (perhaps using Machine Learning in Google Sheet to project GDP data and IMF forecasts from here.Create (or scrape) a database of forecasts from the academic and gray literature that say ‘By 2050, X (e.g. China’s GDP) will be Y’ and then feed them into current models that predict Z based on X, to see what Z values are at 2050?
Many countries optimize quite hard for GDP growth. Can this optimize long-term expected global welfare? (Cf. ‘Of the comprehensive macroeconomic indices already available to us, which serve best as proxies for long-term expected global welfare (incl but not limited to x-risks considerations)? What would be the broad policy implications of targeting such indices instead of GDP/cap?’[73])
Research GDP growth futures or GDP linked bonds to discover market-based estimates of future GDP
Create an ‘Almanac 2050’
Forecast ‘Our World in Data’ data with these GDP forecasts
Review the literature on forecasts by 2050 (e.g. (projection OR projected OR predicted OR ‘estimated to be’) AND (‘by 2040’ OR ‘by 2050’) or use Elicit for this)
Review the degrowth debate: Very worryingly, anti-growth sentiment is rising a lot in OECD countries:
But ″How much economic growth is necessary to reduce global poverty substantially?′ Lots:
Appendix: Further reading
The World in 2050
In 1996, McRae published ‘The World in 2020’. I only skimmed it but it seems like it makes some good predictions (e.g. Brexit, working from home, ‘video phones’, online retail), though crucially it seems to underestimate how central the internet was going to be. Now, 25 years later, he just published ‘The World in 2050’[74]. Tl;dr:
In 2050, Two-thirds of the world’s population will be middle class or rich
Ideas will flow more from east to west.
The anglosphere will become even more important: In 2050, the most populous countries on every continent will be English-speaking: Americas; US. Africa; Nigeria, Asia; India. Australia; Oceania. Europe; British isles. English-speaking countries will make up 40% of world GDP.
China — the world’s largest economy — moves from aggression to cooperation because its population gets older.
The EU diverges into a core and a periphery.
India will become a great power, but also face challenges, and its future is uncertain.
Africa will become more important but finding jobs for its many young people will be its greatest challenge.
Globalization changes its direction from moving goods to moving ideas and money.
New technologies will change our lives again.
A more harmonious relationship between humankind and our planet will arise –- we’ll grow sustainably.
Economics
Textbooks:
Intro to Modern Economic Growth — by the most highly-cited economist of recent decades
Intro to Economic Growth by Charles Jones and Dietrich Vollrath
Vollrath also wrote a popular book on growth: Fully Grown: Why a Stagnant Economy Is a Sign of Success
More selected papers on growth by Jones and a talk ‘The past and future of economic growth: a semi-endogenous perspective’ and The Facts of Economic Growth
Syllabus on Economic Theory & Global Prioritization (which covers growth theory)
Discussion on Thomas Philippon’s paper on TFP growth being linear — EA Forum
Podcast: Can the economy grow indefinitely?
Book: The Empty Planet on how population growth is important for growth
Keynote Speech by Professor Lant Pritchett | Coping with Bad Shocks: Lessons from Growth Dynamics slides: Coping with bad shocks: Lessons from growth dynamics
Patrick Collison’s selection of quotes from papers on growth
GDP as a proxy for welfare
Weird GDP effects:
If you move from a poor to a rich country and start a firm where you earn 10x more, GDP per capita will fall and welfare will rise in both countries (cf. ‘Median wages for all workers only rose 3% from 1980-2005, yet they rose 15% or more for each race/sex subgroup. Because the relative group sizes changed.’)
If we develop technology to make a product cheaper (or free), GDP and GDP per capita will fall (e.g. Gmail, Wikipedia, freeware)[75]. GDP/cap has a hard time accounting for the value of new and free goods in the digital economy. Also see, My Ordinary Life: Improvements Since the 1990s · Gwern
How the World Really Works: The Science Behind How We Got Here and Where We’re Going: In 1800, we needed 10 mins of human labor to produce 1KG of wheat, now it’s two seconds; and we now use ~700x more energy than people in 1900.[76]
Challenges to Mismeasurement Explanations for the US Productivity Slowdown | NBER
Why we’re very much richer than the GDP numbers tell us we are
The Two Sides of Chinese GDP by Nancy Qian — Project Syndicate
Evidence from 33 countries challenges the assumption of unlimited wants ‘In most countries, more than half of the population believes that $1-10M or less would be enough to achieve their ideal life, but a significant minority (8–39%) want as much money as possible, suggesting unlimited wants.’[77]
AI
Explosive growth from AI automation: A review of the arguments
PwC’s Global Artificial Intelligence Study: Sizing the prize
Could Advanced AI Drive Explosive Economic Growth? — Open Philanthropy
Productivity Gains Could Propel The AI Software Market To $14 Trillion By 2030 —ARK Invest
The Great Inflection? A Debate About AI and Explosive Growth—Asterisk
- A ‘slow takeoff’ might still look fast
80k podcasts:
Forecasting
Generally, GDP seems to be the most important thing to forecast, but forecasters rarely highlight its central importance.
Metaculus predictions:
World GDP in 2028 – $114T
China-to-USA GDP ratio in 2050 is currently at 1.34, the table above predicts 1.55
How many people will be living in liberal democracies in the world in the following years?
GDP Growth Has Averaged 0.6pp Weaker than We Expected in 2011 by Goldman
Future Indices: How Crowd Forecasting Can Inform the Big Picture
Will genetic engineering raise IQ by at least 10 points by 2050? 55%
Will synthetic bioweapons infect at least 100 people by 2030?
‘This Can’t Go On’ looks at economic growth and scientific advancement over the course of human history. Over the last few generations, growth has been pretty steady. But zooming out to a longer time frame, it seems that growth has greatly accelerated recently; is near its historical high point; and is faster than it can be for all that much longer (there aren’t enough atoms in the galaxy to sustain this rate of growth for even another 10,000 years).[78]
MacAskill on population forecasting[79]: ‘By 2100 Nigeria’s population will grow to 791 million (Vollset et al., 2020), and India’s 1.09 billion people will outnumber China’s 732 million by almost 50% (Vollset et al., 2020). The forecast for Nigeria is highly sensitive to the assumed pace of progress in female educational attainment and access to contraceptives. The Vollset et al. forecasts are available online at VizHub- Population Forecasting’
2030: How Today’s Biggest Trends Will Collide and Reshape the Future of Everything (Kindle Edition)
The boring timeline The World in 2072
Fiction
The Will to Battle (2017) by Ada Palmer (Review: ‘Sensational. Palmer starts in an Enlightenment utopia (post-war, post-nationalism, post-scarcity, post-gender, post-theocracy, post-fideism, post-meat, post-capital-punishment, post-nuclear-family, general justice via universal voluntary surveillance) and then shows what the tensions will do to any system that has to handle humans as we are.’)
Headbirths, or, the Germans are Dying out — Literature Nobel laureate Guenther Grass starts this novel by vividly painting a satirical picture of how crazy the world might look like if Germany had the population of China and if the world could bear it.
Here are the finalists from FLI’s $100K Worldbuilding Contest — EA Forum
Sci-fi short stories about AI 2041
Appendix: Causal Model Between Growth, Liberal Democracy, Human Capital, Peace, and X-Risk
Below I have a rough and unfinished conceptual dynamic causal model between growth, liberal democracy, human capital, peace, and x-risk, that summarizes the evidence for their relationships.
Economic Growth causes…
Growth causes stability: growth shocks predict violent conflict in a country [80]
Does growth cause democracy?
Growth causes dedication to democracy, greater opportunity, tolerance of diversity, social mobility, commitment to fairness
Another paper says the evidence is mixed
Wikipedia on democracy and economic growth
Democracy causes...
Democracy causes peace & stability:
Democratic peace—the idea that democracies rarely fight one another—has been called ‘the closest thing we have to an empirical law in the study of international relations’ and the relationship is ~5x ‘as robust as that between smoking and lung cancer’.
Does Democracy Bring International and Domestic Peace and Security?
Democracy causes growth (⅓ the effect of human capital)
Democracy and Economic Growth: a Literature Review: the paper examines channels through which democracy could affect growth.
Does Democracy Cause Economic Growth, Stability, and Work for the Poor?
Human Capital:
Existential Security:
Democracy:
Are Democracies Better for Social Protection of the Poor, Gender Equality, and Social Cohesion?
‘Chance of conflict declines by ~1% points with 1 SD decline in high fertility (~2 births / woman). 1 SD increase in low secondary education decreases the chance of conflict by about ~1 percentage points, while 1 SD increase in high secondary education decreases conflict by ~1% points. These represent relatively sizable marginal effects considering that the average chance of dyadic conflict is ~3%. 1 SD change in the human capital composite variable, low or high, is about 2x as large as the effect of 1 SD change in low democracy.’
Peace causes Growth: ‘civil war reduces annual growth by 0.01–0.13 percentage points, and high-intensity inter-state conflict reduces annual growth by 0.18–2.77 percentage points’
Human capital causes…
Human capital causes growth (3x effect size of democracy)
Peace & stability causes...
Note that everything is correlated and an in-depth evidence review of ‘Does X cause Y?’ argues that ‘We ultimately need to choose between (a) believing some overly complicated theory of the relationship between X and Y, which reconciles all of the wildly conflicting and often implausible things we’re seeing in the studies; (b) more-or-less reverting to what we would’ve guessed about the relationship between X and Y in the absence of any research.’
This looks cool and I want to read it in detail, but I’d like to push back a bit against an implicit take that I thought was present here: namely, that GDP takes into account major technological breakthroughs. Let me just quote some text from this article: What Do GDP Growth Curves Really Mean?
Yeah I actually do cite that piece in the appendix ‘GDP as a proxy for welfare’ where I list more literature like this. So yeah, it’s not a perfect measure but it’s the one we have and ‘all models are wrong but some are useful’ and GDP is quite a powerful predictor of all kinds of outcomes:
In a 2016 paper, Jones and Klenow used measures of consumption, leisure, inequality, and mortality, to create a consumption-equivalent welfare measure that allows comparisons across time for a given country, as well as across countries.[6]
This measure of human welfare suggests that the true level of welfare of some countries differs markedly from the level that might be suggested by their GDP per capita. For example, France’s GDP per capita is around 60% of US GDP per capita.[7] However, France has lower inequality, lower mortality, and more leisure time than the US. Thus, on the Jones and Klenow measure of welfare, France’s welfare per person is 92% of US welfare per person.[8]
Although GDP per capita is distinct from this expanded welfare metric, the correlation between GDP per capita and this expanded welfare metric is very strong at 0.96, though there is substantial variation across countries, and welfare is more dispersed (standard deviation of 1.51 in logs) than is income (standard deviation of 1.27 in logs).[9]
GDP per capita is also very strongly correlated with the Human Development Index, another expanded welfare metric.[10] If measures such as these are accurate, this shows that income per head explains most of the observed cross-national variation in welfare. It is a distinct question whether economic growth explains most of the observed variation across individuals in welfare. It is, however, clear that it explains a substantial fraction of the variation across individuals.
I checked the paper and it looks like they’re comparing welfare by “how much more would person X from the US have to consume to move to another country i?” Which results in equations like this:
which says what the factor λsimplei , should be in terms of differences in life expectancy, consumption, lessure and inequality. So I suppose it isn’t suprising that it’s quite correlated with GDP, given the individual correlations at play here, but I am suprised that it is so strongly correlated since I’d expect e.g. life expectancy vs gdp to correlate at maybe 0.8[1]. Which is a fair bit weaker than a 0.96 correlation!
I checked. It’s 0.67.
This seems to come from European countries.
Good point. I grabbed the dataset of gdp per capita vs life expectancy for almost all nations from OurWorldInData, log transformed GDP per capita and got a correlation of 0.85.
I think there’s a good chance the degree to which the world of 2050 looks different to the average person might have very little to do with GDP.
On the one hand, a large chunk of the GDP growth I expect will come from changes in how we produce, distribute, and use energy and chemicals and water and food and steel and concrete etc. But for most people what will mostly feel the same is that their home is warm in winter and cool in summer, and they can get from place to place reasonably easily, and they have machines that do their basic household chores.
On the other hand, something like self-driving cars, or augmented or virtual reality, or 3D printed organs, could be hugely tranaformative for society without necessarily impacting GDP growth much at all.
To me, the empiric status of that claim feels quite unclear. Is that your personal opinion? Is it a general pattern for which there’s existing data?
Yes, good catch, this is based on research from the World Value Survey—I’ve added a citation.