Discover more from Adventure Capital
The Murky Phase: Pollution and Data
Epistemic Status: Cautiously optimistic about a very broad theory of economic revolutions.
I read a very long but good article by Venkatesh Rao in the financial times recently. It draws broad parallels between the upheaval of labor, true entrepreneurship, and capital in the industrial revolution.
Analysts in the industrial revolution couldn’t make sense of it. They tried to use the maps and ideas of the agricultural revolution. They used the wrong map. Before the industrial revolution, “labor” was farmers. Afterwards it was factory hands. After the tech revolution, maybe labor will be followers of the Lean Startup. Maybe YCombinator is the new University. Maybe Venture Capitalists are the new middle managers.
Venkatesh’s article showed a very powerful idea when you want to learn from history. To use historical rhyming to make predictions, we must step far enough back. We must look at the modern day from a distance far enough to smooth out how history doesn’t perfectly repeat. You can’t predict what happens to farm labor in industry if you wonder how farmers will work in factories. That’s the wrong map. You have to abstract. You put together:
the kind of mass work we need (factory hands).
the teaching infrastructure to make the workers (public schools)
the transport/housing for the new workers (mass housing and transit)
This historical rhyming goes further than labor. I see a very concrete rhyme between Pollution and Personal Data. They are not very similar at first glance. Let’s step back and squint at history. What is pollution in the abstract? What are the key bits that make pollution what it is?
An excessive accumulation.
poorly-understood, possibly-harmful material with externalized costs.
secondary to the major driver of the economic revolution.
We didn’t know what pollution did when it first began accumulating.
We had early critics of its potential harm, but the effects were hard to detect and in the future. The gains were very concrete and in the present: Cars! Roads! Money!
Some early critics said delicate natural systems might get hurt. But we didn’t yet have the tools to prove this.
Pollution was secondary to the main driver of industry. making steel, oil, and os on.
The costs of pollution fell outside the companies making the steel, oil, etc.
Society took a long time to address pollution. We needed new tools to understand (public health). We had to convince society there was harm (e.g. anti-smog campaigns). We had to understand the costs of pollution and pair it with the production (fix externalities).
We should be able to point at the modern historical rhymes. What are the modern day rhymes? Where is the tech revolution’s pollution, whistleblowers, the Environmental Protection Agency, the National Parks Service?. Let’s see if it works:
Is Personal Data:
An excessive accumulation?
poorly-understood, possibly-harmful material with externalized costs?
secondary to the major driver of the economic revolution?
We did not guess the societal effects on reams of personal data collection at first. Social media outrage culture might be just one negative side effect. But whatever the cost is, we are making it worse as it continues to accumulate.
Some early critics said it could very well be dangerous from first principles. They said we are not the customer, but the product. Now we have eerily-accurate ads targeted at us. Outrage-bait media dominates what we read. Algorithms send us down radicalization rabbit holes. Kids are dying of diseases that vaccines defeated several decades ago
Personalized Data accumulation is secondary to the main driver: Near zero-cost distribution of information. Collecting all this personal data on the side is not as secondary, but the amount is secondary. Much of the data collected on you isn’t used to make money. But they collect it all anyway in case it might come in handy later.
We are far too cavalier as a society about the misuse of the personalized data. We did the same with pollution. What are the real consequences from data breaches, anyway? A short bit of bad PR? Remember the massive Experian leak? A large corporation that leaked damaging data like your social security number, address, and detailed financial records. They got a stern warning in congress. We probably need to make the producers of pollution pay the *full* cost of their actions.
So how might we use this theory to predict where things are going? This is already getting long, so here’s some breadcrumbs to get you thinking: