Ezra Klein and Derek Thompson’s new book “Abundance” has been described as “not so much a book as a Discourse-generating machine”, and you know how much I love one of those. It’s only just been published so I haven’t read it yet, but Mike Konczal is a good lad and I’ve read his review. My immediate reaction was that this is a perfect application for one of my own hobby horses – taking the cybernetic perspective just makes it so much easier to express one of the key problems here and to see what the tradeoffs are.
Mike starts by setting out the issue that Abundanceism aims to address:
“The Empire State Building, then the world’s tallest building at 102 stories, was completed in 1931. Building that majestic structure, later called one of the Seven Wonders of the Modern World by the American Society of Civil Engineers, took just one year and 45 days. Contrast that with just about anything we try to build now. And it’s not just speed. In the 1970s, 1.7 million new homes were constructed each year. Since 2021, with a population that’s more than 50 percent larger and an ongoing housing crisis, we’ve built only 1.4 million new homes a year. Or consider major legislation. Medicare was signed into law on July 30, 1965. Less than one year later, sign-ups were already available, with elderly beneficiaries just needing to mail back a single card. In our time, Medicare was expanded in the 2022 Inflation Reduction Act to allow for the negotiation of common prescription drug prices. However, the new prices for the ten drugs it will cover won’t come fully online until 2026, just in time for President Trump to take credit for them going into the midterms.”
My first point here might be to express “surprise at the surprise”. Of course things are slower and more difficult now – the reason that it’s more difficult to build the second million homes is that the first million homes get in the way! One of the underlying sources of my irrational beef with economic geography is that it often tries to imply that increasing returns to scale are the normal and common case, rather than an unusual phenomenon that tends to be very localised in space and time[1].
In fact, usually the bigger things get, the more difficult it becomes to grow them any more. Adding things is an additive process, hence the name, but the number of potential connections between things grows multiplicatively. So things get exponentially more complicated as they get linearly bigger. More effort needs to be put into their plumbing, metaphorically but also literally. There are more people who will be inconvenienced by the new thing, and there is just more … bloody … stuff in the way. (My mind keeps going back to the parable of the Welsh slate heaps). Pretty quickly you get diminishing marginal returns and after a while it’s entirely possible to get diminishing absolute returns.
So does that mean abundance is doomed? I don’t think so, or at least I don’t think there’s any good reason to believe that we’re in the same endgame phase as the slate quarries. I just wanted to put that point up there, so that, as ever, we’re starting from a position of respect for the problem. I do think it’s correct in an important sense to say, as Mike does, that “modern liberalism became too obsessed with saying no”. But it isn’t obviously true – constant growth and increasing returns aren’t so fundamentally the natural way of things that the only thing holding us back from nirvana must be the dratted regulatory state.
And the problem can be stated quite succinctly if we think about “the dratted regulatory state” in formal terms, as a regulator in the formal sense of being an implicit model of the system, which can only deal with the system at a level of complexity equal to or less than its own. The problem of abundanceism, restated in this form, is simply that the liberal regulatory state isn’t adequate to the task.
Specifically, the problem is that, for the reasons noted above, as things grow and become more complex, a greater proportion of their energy and resources have to be devoted to purely internal and administrative matters. The regulatory model needs, ideally, to grow alongside the system that it’s modelling, so that it’s still capable of representing the complexity of the system.
If it doesn’t, then the people who still have the job of stopping things getting in the way of each other will reorganise, in order to try to continue to do their job with an inadequate model. One of the most effective organisational techniques to do this is to replace, as much as possible, “how and why” questions with “yes or no” questions. The “planning system” gradually stops being one in which the word “planning” has something close to its ordinary meaning, and moves toward becoming a “permissioning authority”.
As the resource imbalance gets bigger, another organisational/cognitive technique which helps reduce the load even more is to adopt something like the Hippocratic principle. It’s much easier to turn a “no” into a “yes” than vice versa, and part of the cost of building something is that it constrains what can be built in the future. So, the greater your uncertainty about the future (perhaps because you don’t have the capacity to think about it any more), the more likely you are to be worried about closing off options.
Where I think I end up with this is in a view that the battle between “builders” and “blockers” is mischaracterised. These are two wrong answers to a problem which is fundamentally caused by the imbalance between the complexity of the system and the capacity to manage it. Neither builders, nor blockers, but planners.
(I will revert on this subject once I’ve read the book – also, watch this space for a really exciting forthcoming piece published elsewhere, where I try to actually apply this analysis to the real world!)
[1] Because of their known very great popularity with economists, planners and policymakers, I’d be very interested to know more about the assumptions with respect to increasing and diminishing returns to scale which are built into video games like Civilisation, SimCity and such.
This is fun!!!
Back in the day when NASA was more like a university than a business, there were lectures about aeronautical and other subjects us lazy good for nothing drones could attend. One that sticks in the peabrain was a talk by a group that wanted to build a STOL port in the East River. they foolishly tried to gain community support by holding meetings with the impacted community. The response, of course, was NFW!!! In discussions with the residents, they found that there was nothing anyone could say that would gain their permission to do anything. They had been F'd over so many times, think Robert Moses, that they did not believe anything anyone said.
When I played Sim City (way back when) it was clear that the larger the city, the more maintenance and bad events happening increased faster than growth generated income. The same happens with GAAP accounts where businesses need higher profitability to grow to overcome cash flow demands on costs.
Some things scale well - factory production, farms acquiring more land. Infrastructure doesn't, even "easy things" like computer and phone networks as they become more complex.
AI and software can reduce the complexity for human managers. However, as we see with such systems, the algorithms become opaque and difficult to subject to analysis, especially when bad outcomes result. [As your book indicates]. My sense is that control needs to be pushed down as far as possible, and ideally, most managers should be more like "One Minute Managers" relinquishing management decisions to as low a level as possible.
The other problem with "abundance" is that our accounting rarely deals with externality costs. We can easily increase the production of plastic containers, but the costs of pollution from production and [lack of] disposal are not fully costed. While I do not support "degrowth", I do think we need to reduce the consumption of non-recyclable items as far as possible to emulate biology as much as possible. Will AI be able to help with this?