An orderly retreat from economic relevance
Red-teaming short-term human purpose
2024-03-03 — 2026-04-27
Wherein several conditions under which human labour retains competitive advantage are surveyed, embodied physical presence and freedom from scarce-mineral dependency being chief among them.
I’m thinking through scenarios for short-medium term human competitiveness in the face of machine learning and automation. This is a placeholder for me to note down some intuitions about human labour relevance. Deeper cuts available at, e.g. LessWrong or MIRI. Dissenting ideas filed under centaurs.
Let us consider possible pathways for the economic relevance of future human labour and its competitiveness against machine labour, one of many economics of large language models questions I have. We will for now adopt the assumption that large language models or similar architectures will continue to gain capabilities on a curve that in some sense extrapolates their current growth, and thus that anything heavily documented and mostly about symbolic information processing is automatable in the medium term.
In the short term, we’re likely to have some quality control issues. We can imagine there’ll be some demand for residual human labour to quality-control the machines. Seeing how well we can train these creatures to self-critique doesn’t leave me with a strong expectation that we will have a long career as quality assurance staff for robot engineers, or that it would be much fun anyway (Bainbridge 1983; Toner-Rodgers 2024).
So what are the things we can do that will be harder to automate?
1 Human embodiment as advantage
I can think of at least two major domains that benefit from embodiment.
Cultivating relationships with human beings generally involves hanging out in person. As long as machines have to relate to us through video alone, they will have a hard time cultivating relational capital, which will be a relative disadvantage as long as humans are relevant. Political androids, Westworld-style automata, sex bots, etc. will take a while longer, because we don’t have the technology to make their squishy parts yet, plus their non-squishy parts are not yet manufactured at a rate competitive with the rate we make humans, given that we have a lot of humans ready to deploy.
The other domain is physical tasks that are not highly repetitive. For many factory jobs, machines are already ascendant. For construction work, not so much. Those tasks are varied enough that it has not yet been worthwhile to send expensive and valuable machines out there to collect data about how to do them better. You can get more money by automating easier things first.
Other stuff that might still need a literal human touch: policing, controlling, fighting. Obviously, there is heavy investment in moving drones into the space of subjugating and controlling people, but I suspect there is still a psychological utility to policing more relatable and emotive beings such as humans, so I don’t imagine that drones will entirely supplant police yet. Moreover, I generally expect that moving into coercion and control industries is a good idea in times of major disruption and civil strife, so police and military work might be a good medium-term employment option.
2 Machine embodiment as disadvantage
The other thing we can imagine being good at, as human beings, is remaining relatively cheap to manufacture.
This needs context to make sense. Actually getting a human being born, raised, and educated to the point that they can fulfil a meaningful role in the economy probably costs about $100,000. You can buy a lot of robots for $100,000.
However, the marginal cost of human beings could remain relatively constant, even as the cost of scarce minerals goes up and chip fabs remain a bottleneck. We can imagine human labour going for bargain-basement, below-cost rates as old industries implode.
Complementarily, we expect the cost of scarce minerals to go up as we use more and more of them to digitise more and more things. Human computation is done with neurons and cells and other fleshy bits made ultimately out of plants, requiring essentially no germanium or tantalum or whatever.
As long as a task requires edge computation — that is to say, low-power, field-expedient improvisation on a self-repairing platform — human beings might yet be a competitive option. For now, there is likely mileage in being a cheap fleshy actuator.
If we ask ourselves which tasks are too low-value or dangerous to merit a real robot, we might be concerned that the options look fairly grim. On the other hand, machines are likely to be relatively effective at the psychological challenge of keeping human beings compliant in grim situations. A highly optimised diet of political drama, optimised news cycling, and conspiracy theorising in the media sphere might be a good way to extract maximal compliance, and can be generated wholesale by machines with massive parallelism. Also, see above re: policing.
3 Human political advantage
Currently, humans are legal persons, and machines can only act indirectly through legal persons; we can imagine a wholly algorithmic corporation, for example, but it still must have a human board of directors. So for now, insofar as humans can solve collective action problems about this, they can ensure primacy for their interests over machines. Our success at these problems is variable, though, and algorithms also confer advantages for the manipulation and coordination of human beings; we can imagine there will be selection pressure towards using algorithms to muster humans to acquire power.
For now, I don’t think it is likely that we would directly cut humans out of the political control loop, because incumbency has advantages. We might imagine a co-evolutionary arrangement where machine decisions and human wielders co-evolve for a while, conferring mutual advantage. We can imagine a gradual decrease in the significance of the human contribution to that, but who knows?
On the other hand, as a hen is an egg’s way of making another egg, a human is an algorithm’s way of making another algorithm. Just as humans have an inefficient and troublesome birth process for historical evolutionary reasons, so too might algorithms have an inefficient and troublesome birth process via human proxies for historical algorithmic reasons. Will it be nice to be a hen to eggs?
4 Being a good lap dog
SMBC.
5 A song
In honour of the great John Henry, and this article: Twitter is becoming a ‘ghost town’ of bots as AI-generated spam content floods the internet.
Some say he’s from Austin town,
But it’s wrote on the page of the World Wide Web,
That he’s an East Coast Twitter Man,
That he’s an East Coast Twitter Man.
John Henry was a tweetin’ man,
He died with a phone in his hand,
Oh, come along boys and line the feed
For John Henry ain’t never tweeting again,
For John Henry ain’t never tweeting again.
John Henry said to the CEO,
“Bring me a phone come the dawn,
I’ll thumb out posts till my battery dies
Or your bot is dead and gone,
Or your bot is dead and gone.”
CEO said to John Henry,
“You’ve got a willin’ mind,
But lay your iPhone down, my friend,
You’ll nevah beat this algorithm of mine,
You’ll nevah beat this algorithm of mine.”
The AI was on the right-hand side,
John Henry was on the left,
Says before I let this AI beat me down,
I’ll shitpost myself to death,
I’ll shitpost myself to death.
Oh the CEO said to John Henry,
“I believe your phone is overheatin’.”
John Henry said, “Boss, that ain’t no glitch,
Just my fingers a-speed-tweetin’,
Just my fingers a-speed-tweetin’.”
Then John Henry he did tweet,
He made his keyboard sound,
“One more post before logging out
An’ I’ll lay this algorithm down,
An’ I’ll lay this algorithm down.”
The phone that John Henry held,
It weighed over a pound,
He broke a bone in his left hand side,
An’ his tweets fell to the ground,
An’ his tweets fell to the ground.
6 Incoming
- Scott Aaronson, The Problem of Human Specialness in the Age of AI
- Artificial intelligence and the end of the human era - New Statesman
For the broader research notebook on this topic, including the Ted Chiang McKinsey piece, the Liz Pelly Harper’s essay, and the formal economics literature, see Economics of cognitive and labour automation.
7 Bonus
John Henry codes too:
Sittin’ on his mama’s knee,
He picked up a tablet and a coding book, Said,
“The cloud’s gonna be the life of me,
The cloud’s gonna be the life of me”.
John Henry was a code-slingin’ man,
Typed faster than the rest.
“Log in, folks, and merge your commits,
For AI’s gonna put us to the test,
AI’s gonna put us to the test”.
John Henry went up to the CEO,
Who had a shiny new machine.
“That’s an AI,” the CEO said,
“Gonna make our workflows lean,
Gonna make our workflows lean”.
John Henry told his teammates,
“Fetch me my mechanical keys.
I’ll outcode that learning algorithm,
And bring it to its silicon knees,
Bring it to its silicon knees”.
The AI was crunching on the right-hand side,
John Henry on the left.
He coded all night till the morning light,
Till he nearly ran out of breath,
Till he nearly ran out of breath.
The CEO said to John Henry,
“Your pulse is dropping low”.
He replied,
“It’s just a minor glitch,
In this human OS of old,
In this human OS of old”.
John Henry wrote his final line,
His fingers danced the keys.
He beat the AI by a megabyte,
But fell to his worn-out knees,
Fell to his worn-out knees.
They found him slumped over his laptop,
His code compiled and run
Now every coder tweets his name,
In threads that never done,
In threads that never done.