Three cheers for the Substack MVPs in replies, the predominant reason many of us newbies joined the platform.
Implicit in John B’s perspective, the train has left the station and won’t be making a U-turn. Leaving us where?
The lively exchange on employment typology, trajectory and productivity is the heart of AI’s societal impact. In reading, my mind went to the very old Zager and Evans tune, “In the Year 2525,” projecting the image of “…legs got nuthin’ to do, some machine doin’ that for you.” When the song sees future “arms hangin’ limp at their sides,” it overlooks the innate, human need for challenge, the nudge of curiosity.
I’d also add that economic prognostication and empirical assessment often leave a gap – quality of life. “Happiness” metrics, such as Bhutan’s GNH are qualitative, maybe not mainstream, yet still valuable in their outlook, and I believe influential in how we gauge AI and humanity’s future.
As innovators innovate, I don’t see masses of “lemmings” awaiting a next directive, but new-found activities that will push more souls to climb Maslow’s model.
Thank you for the Friday morning thoughts, a very pleasant wake-up call.
This post glosses over the distributional impacts of productivity in the 21st century. In the last 20 years, two thirds of productivity gains have come from 20% of the workers (the knowledge economy). Like 25% have come from the software NAICS codes (2-3% of the U.S. workforce). When you de-average everything, the optimist story is not nearly as clean as the headline dataset.
There is a similar argument to consumption. Part of why the frontier of consumption has expanded is because we’ve transactionalized larger and larger swathes of the human experience. You can argue whether that is good or bad - but you can’t argue that it has happened. Or that it’s been a big consumption / GDP tailwind.
Anyway I agree - time to build. But the historical record is not one that paints a picture of abundant opportunity. It’s one of a narrow set of tail outcomes.
You are making three points and I think two of them actually support the thesis rather than challenge it.
On concentration: you are right that productivity gains have been narrowly distributed. That is the Engels’ Pause section of the essay, not a rebuttal of it. The entire argument is that productivity gains accrue to a narrow set of actors until the tools become labor-augmenting rather than labor-replacing. You are describing the pause. I am describing what breaks it. We are looking at the same data from different positions on the timeline.
On consumption: I agree completely that we have transactionalized enormous swaths of the human experience. That is not a counterpoint to the elasticity of human wants. It is the elasticity of human wants. Keynes could not have imagined that people would pay for meditation apps, convenience delivery, and streaming subscriptions because those categories did not exist. Whether you think that expansion is good or bad is a values question. Whether it happened is an economics question. It happened. That is the point.
On “narrow tail outcomes”: this is where I think the framing gets slippery. The post-Engels’ Pause period in Britain, the post-war deployment period after mass production, the two decades after the dot-com crash. These were not narrow tail outcomes. They were broad-based transformations in how people lived and earned. They just did not arrive instantly, and they did not arrive for everyone at the same time. The historical record does not say “abundant opportunity appeared overnight.” It says “abundant opportunity appeared for the people who built during the transition while everyone else was still arguing about the last economy.” Which is the point of the essay.
We agree on the most important sentence: time to build. I would just push back on the idea that the historical record is pessimistic.
It is demanding. It rewards the people who read it correctly and move. That is not the same thing as narrow.
Yes. I think we agree on 95%. I think the nuance is: the people who build during the transition is a definitionally narrow set of people. And that as the economy gets more capital light fewer of what I will call “lemming advancement opportunities” appear downstream of those builders overnight. This is why the fraction of successful new enterprises that end up employing more than one person has shrunk in the last 20 years. And AI will amplify that dynamic.
Which is why it’s time to build. The economy will continue its arc of offering more upside to those with agency + skill + luck and less and less
Couldn’t agree more. It is a narrow set of people who build, and needs to become larger during this transition.
Additionally, I think these conversations often gloss over the immediate impact felt by those in mid-career in favor of the longitudinal view of new jobs, sectors, opportunities created.
Brilliant post John. Thanks again for reminding us why history is so essential as a lens to understand what is happening with AI and the workforce. I agree that there is going to be a sharp shock for the labour market, but for those people using AI as a collaborator to build rather than as a competitor to fear the horizons look almost unparalleled. 🙏
Three cheers for the Substack MVPs in replies, the predominant reason many of us newbies joined the platform.
Implicit in John B’s perspective, the train has left the station and won’t be making a U-turn. Leaving us where?
The lively exchange on employment typology, trajectory and productivity is the heart of AI’s societal impact. In reading, my mind went to the very old Zager and Evans tune, “In the Year 2525,” projecting the image of “…legs got nuthin’ to do, some machine doin’ that for you.” When the song sees future “arms hangin’ limp at their sides,” it overlooks the innate, human need for challenge, the nudge of curiosity.
I’d also add that economic prognostication and empirical assessment often leave a gap – quality of life. “Happiness” metrics, such as Bhutan’s GNH are qualitative, maybe not mainstream, yet still valuable in their outlook, and I believe influential in how we gauge AI and humanity’s future.
As innovators innovate, I don’t see masses of “lemmings” awaiting a next directive, but new-found activities that will push more souls to climb Maslow’s model.
Thank you for the Friday morning thoughts, a very pleasant wake-up call.
So glad the piece and conversation was a plus to your day, John! Have a great weekend. 🤓🙏🏼
This post glosses over the distributional impacts of productivity in the 21st century. In the last 20 years, two thirds of productivity gains have come from 20% of the workers (the knowledge economy). Like 25% have come from the software NAICS codes (2-3% of the U.S. workforce). When you de-average everything, the optimist story is not nearly as clean as the headline dataset.
There is a similar argument to consumption. Part of why the frontier of consumption has expanded is because we’ve transactionalized larger and larger swathes of the human experience. You can argue whether that is good or bad - but you can’t argue that it has happened. Or that it’s been a big consumption / GDP tailwind.
Anyway I agree - time to build. But the historical record is not one that paints a picture of abundant opportunity. It’s one of a narrow set of tail outcomes.
You should also read the Citadel piece that was the inspiration for the editorial. It’s fascinating and I think speaks to much of what you raised.
Thanks so much for the thoughtful response!
You are making three points and I think two of them actually support the thesis rather than challenge it.
On concentration: you are right that productivity gains have been narrowly distributed. That is the Engels’ Pause section of the essay, not a rebuttal of it. The entire argument is that productivity gains accrue to a narrow set of actors until the tools become labor-augmenting rather than labor-replacing. You are describing the pause. I am describing what breaks it. We are looking at the same data from different positions on the timeline.
On consumption: I agree completely that we have transactionalized enormous swaths of the human experience. That is not a counterpoint to the elasticity of human wants. It is the elasticity of human wants. Keynes could not have imagined that people would pay for meditation apps, convenience delivery, and streaming subscriptions because those categories did not exist. Whether you think that expansion is good or bad is a values question. Whether it happened is an economics question. It happened. That is the point.
On “narrow tail outcomes”: this is where I think the framing gets slippery. The post-Engels’ Pause period in Britain, the post-war deployment period after mass production, the two decades after the dot-com crash. These were not narrow tail outcomes. They were broad-based transformations in how people lived and earned. They just did not arrive instantly, and they did not arrive for everyone at the same time. The historical record does not say “abundant opportunity appeared overnight.” It says “abundant opportunity appeared for the people who built during the transition while everyone else was still arguing about the last economy.” Which is the point of the essay.
We agree on the most important sentence: time to build. I would just push back on the idea that the historical record is pessimistic.
It is demanding. It rewards the people who read it correctly and move. That is not the same thing as narrow.
Thanks again for the share! 🤓🙏🏼
Opportunity to help for everyone else
🤓🙏🏼🤓🙏🏼
Yes. I think we agree on 95%. I think the nuance is: the people who build during the transition is a definitionally narrow set of people. And that as the economy gets more capital light fewer of what I will call “lemming advancement opportunities” appear downstream of those builders overnight. This is why the fraction of successful new enterprises that end up employing more than one person has shrunk in the last 20 years. And AI will amplify that dynamic.
Which is why it’s time to build. The economy will continue its arc of offering more upside to those with agency + skill + luck and less and less
Couldn’t agree more. It is a narrow set of people who build, and needs to become larger during this transition.
Additionally, I think these conversations often gloss over the immediate impact felt by those in mid-career in favor of the longitudinal view of new jobs, sectors, opportunities created.
Brilliant post John. Thanks again for reminding us why history is so essential as a lens to understand what is happening with AI and the workforce. I agree that there is going to be a sharp shock for the labour market, but for those people using AI as a collaborator to build rather than as a competitor to fear the horizons look almost unparalleled. 🙏