This argument seems to be based on the view that “jobs” are just tasks that need to be done in the economy, and that it’s better if we have AI/robots that can do those tasks more efficiently. But “jobs” have a dual role—for most people, they are also the main pathway for upward social mobility.
Financial capital follows a power law distribution. Human capital is normally distributed. Jobs are therefore the main mechanism we have in society for those who were not lucky enough to be born into financial capital to nevertheless earn a living and get a share of the vast wealth that “the economy” produces. If that mechanism is obliterated—what other ways are there to ensure people not born into financial capital to get wealth? Will they have to rely on altruism alone?
I have heard people worry that the new wealth produced by AI will all be concentrated in the hands of, say, five people, and the rest of us will be left to starve.
I think this is a strawman of actual wealth concentration concerns. Most reasonably informed people I know who hold these concerns aren’t expecting AI’s wealth to be concentrated in the hands of 5 people. But AI’s wealth could easily be concentrated in the hands of the people who hold the majority of AI-related capital—say, the top 10% globally − 800 million people (and their descendants) - with few pathways for those not born into capital to get a share of that wealth. Even the top 1% globally is 80 million people.
If these 80 million people hold the vast majority of wealth and power, it is foolish to think that the rest of society can “just keep doing what they’re currently doing”, completely unaffected. For example, if the top 80 million people got incredibly wealthy to the point that they each got private jets (according to Google, there are currently only about 25k private jets), that alone could raise air pollution or carbon emissions in a way that definitely impacts the other 99% of the world.
Hello. You may be interested in how the distribution of income before tax (not wealth) has evolved across time. The 1 % of people with the highest income had around 20 % of the total income before tax both now, and 200 years ago.
The data in this area is pretty shaky. On the graph you have shared specifically:
Although the graph goes back to 1820, there is actually very limited data before WWI, as most countries didn’t have income taxes back then (which is the main source of data). In fact, when you click on the individual countries, most of them do not go back before 1900. The US starts in 1913, China starts in 1979, India in 1923, Indonesia in 1984 and Nigeria in 1985. Japan’s series doesn’t start until 2008!! Clicking through the countries, it looks like countries with considerably less than half of the current world’s population had any data before 1900, and I am not sure what extrapolations they had to make to get the “World” figures they use for teh graph.
I would also be very sceptical of income data for developing countries, which tend to have large “informal economies”.
China is an interesting case. There is no doubt that China has experienced enormous economic growth since its economy opened up in the late 1970s. But the graph for China shows the income share of the top 10% growing from 28% of China’s income to 41.7%! Caveats about data reliability still apply, but that is quite a shocking increase in inequality.
More generally—there is some evidence that median wages have started to decouple from general productivity growth, with the labour share of income declining over the past ~20-30 years. Economists argue about the data, the causes of this, and whether it is a temporary or lasting change. But some think it is because “superstar” firms with low labour shares have taken a greater market share thanks to globalisation and digitsation. See e.g. Autor et al (2020), and this 2018 OECD working paper.
In any case, I don’t think we are going to resolve this disagreement by exchanging data because: (1) data is limited; (2) there are so many different ways to interpret the data and experts genuinely disagree on this; and (3) we can also argue over the extent to which the past predicts the future. I think there is only so much we can learn from the past as I am concerned AI can be different in important ways—i.e. I think it is very plausible that the distributional impacts of automating cognitive labour will be quite different to the impacts of automating physical labour or routine, administrative tasks, but I won’t be able to prove this with data.
The main reason I replied wasn’t to get into an argument over data as that can go on for days with no resolution. Rather, I replied because I saw this post already had a fair number of “disagree-votes” and only one comment explaining why, so I thought I should at least explain my alternative view.
Thanks for the good points. Here is the same graph for the United States (US). The income before tax of the 1 % of people with the most income was supposedly 20.4 % in 1913, and 20.7 % in 2024. I am sharing data for the US because it covers a long period (111 years), and “has been the world’s largest economy since about 1900” until 2015.
Re: bets—I am highly uncertain about AI timelines myself. Amongst the EA/AI community, I think my timelines would be considered “long”—I expect major advancements in robotics will be needed for AI to displace more than about 20% of the current jobs in developed countries, and I don’t expect that could happen within the next 10 years.
This argument seems to be based on the view that “jobs” are just tasks that need to be done in the economy, and that it’s better if we have AI/robots that can do those tasks more efficiently. But “jobs” have a dual role—for most people, they are also the main pathway for upward social mobility.
Financial capital follows a power law distribution. Human capital is normally distributed. Jobs are therefore the main mechanism we have in society for those who were not lucky enough to be born into financial capital to nevertheless earn a living and get a share of the vast wealth that “the economy” produces. If that mechanism is obliterated—what other ways are there to ensure people not born into financial capital to get wealth? Will they have to rely on altruism alone?
I think this is a strawman of actual wealth concentration concerns. Most reasonably informed people I know who hold these concerns aren’t expecting AI’s wealth to be concentrated in the hands of 5 people. But AI’s wealth could easily be concentrated in the hands of the people who hold the majority of AI-related capital—say, the top 10% globally − 800 million people (and their descendants) - with few pathways for those not born into capital to get a share of that wealth. Even the top 1% globally is 80 million people.
If these 80 million people hold the vast majority of wealth and power, it is foolish to think that the rest of society can “just keep doing what they’re currently doing”, completely unaffected. For example, if the top 80 million people got incredibly wealthy to the point that they each got private jets (according to Google, there are currently only about 25k private jets), that alone could raise air pollution or carbon emissions in a way that definitely impacts the other 99% of the world.
Hello. You may be interested in how the distribution of income before tax (not wealth) has evolved across time. The 1 % of people with the highest income had around 20 % of the total income before tax both now, and 200 years ago.
The data in this area is pretty shaky. On the graph you have shared specifically:
Although the graph goes back to 1820, there is actually very limited data before WWI, as most countries didn’t have income taxes back then (which is the main source of data). In fact, when you click on the individual countries, most of them do not go back before 1900. The US starts in 1913, China starts in 1979, India in 1923, Indonesia in 1984 and Nigeria in 1985. Japan’s series doesn’t start until 2008!! Clicking through the countries, it looks like countries with considerably less than half of the current world’s population had any data before 1900, and I am not sure what extrapolations they had to make to get the “World” figures they use for teh graph.
I would also be very sceptical of income data for developing countries, which tend to have large “informal economies”.
China is an interesting case. There is no doubt that China has experienced enormous economic growth since its economy opened up in the late 1970s. But the graph for China shows the income share of the top 10% growing from 28% of China’s income to 41.7%! Caveats about data reliability still apply, but that is quite a shocking increase in inequality.
More generally—there is some evidence that median wages have started to decouple from general productivity growth, with the labour share of income declining over the past ~20-30 years. Economists argue about the data, the causes of this, and whether it is a temporary or lasting change. But some think it is because “superstar” firms with low labour shares have taken a greater market share thanks to globalisation and digitsation. See e.g. Autor et al (2020), and this 2018 OECD working paper.
In any case, I don’t think we are going to resolve this disagreement by exchanging data because: (1) data is limited; (2) there are so many different ways to interpret the data and experts genuinely disagree on this; and (3) we can also argue over the extent to which the past predicts the future. I think there is only so much we can learn from the past as I am concerned AI can be different in important ways—i.e. I think it is very plausible that the distributional impacts of automating cognitive labour will be quite different to the impacts of automating physical labour or routine, administrative tasks, but I won’t be able to prove this with data.
The main reason I replied wasn’t to get into an argument over data as that can go on for days with no resolution. Rather, I replied because I saw this post already had a fair number of “disagree-votes” and only one comment explaining why, so I thought I should at least explain my alternative view.
Thanks for the good points. Here is the same graph for the United States (US). The income before tax of the 1 % of people with the most income was supposedly 20.4 % in 1913, and 20.7 % in 2024. I am sharing data for the US because it covers a long period (111 years), and “has been the world’s largest economy since about 1900” until 2015.
I remain open to bets against short timelines for transformative AI (TAI), or what they supposedly imply, up to 10 k$. Do you see any that we could make?
Re: bets—I am highly uncertain about AI timelines myself. Amongst the EA/AI community, I think my timelines would be considered “long”—I expect major advancements in robotics will be needed for AI to displace more than about 20% of the current jobs in developed countries, and I don’t expect that could happen within the next 10 years.