Apropos of everything

Robert Nozick and John Rawls were intellectual rivals, friendly colleagues, and even members of the same reading group. Their conversations, at least the ones we were privy to through their iterations of published work, were dedicated to reconciling the role of the state in manifesting the best possible world. Nozick, it can be said in a gratuituous oversimplification, favored a minimal government while Rawls, similarly oversimplified, favored a larger, wider reaching set of government institutions. Both were well aware of the risks and rewards of concentrating power within government institutions, they simply arrived at different conclusions based on risks each wanted to minimize versus those they were willing to incur.

My mental model of the evolution of government (influenced heavily by Nozick and refined towards the end by Rawls) goes something like this:

  1. 100,000 years ago roving bands of humans grow to thrive in their environment by solving collective action problems, largely through familial relations. Larger groups have more success hunting, foraging, and protecting themselves from predators.
  2. Eventually some groups get so good at collective action that they begin to prey on other smaller groups. These “bandits” gain more through resources taken by force than they would strictly producing resources through hunting and foraging.
  3. This creates an arms race in group size, with bigger groups having the advantage while facing the diminishing marginal returns imposed by difficultings in maintaining the integrity of collective action in the face of individual incentives to free ride i.e. its hard to get people to pull their weight when their parents aren’t watching.
  4. Some groups mitigate these difficulties, growing larger still. At some threshold of group size, the rewards to mobilitity are overtaken by the rewards to maintaining institutions and resources (freshwater, shelter, opportunities for agriculture), leading to stationary groups.
  5. These stationary groups begin to act as “stationary bandits”, extracting resources from both outsiders for the benefit of their group and from their members for the benefit of their highest status members.
  6. Differing institutions evolve across groups, varying the actions prescribed and proscribed for leaders, members (citizens), and non-members. Some groups are highly restrictive, others less so. Some groups are more extractive, funneling resources to a select minority. Some groups redistribute more , others less.
  7. Democracy evolves specifically as an institution to replace hereditary lines, a deviation from the familial lines that sat the origin of the state all the way back at step 1. Its correlation with other institutions is less certain, though it does seem to move hand-in-hand with personal property rights and market-based economies. Democracies begin to differentiate themselves based on the internal, subsidiary institutions they favor and instantiate.

A lot of my political leanings can be found not in favoring Nozick or Rawls, but in the risk immediately preceding their point of divergence. When I look at well-functioning modern democracies, I see an exception to the historical rule. I see thousands of years of stationary bandits voraciously extracting resources while high status members taking desperate action to maintain power in a world where property rights are weak and collective action is tenuous. Rawls saw a growing state as a opportunity to create justice through fairer, more equitable outcomes. Nozick saw a growing state as a further concentration of power that, no matter how potentially benevolent today, would eventually attract the most selfish and venial, leading to corruption and return to the purest stationary bandit, only now with the newfound scale.

Both strike as me as perfectly reasonable concerns about very real risks. Which do I believe the greater risk? Depends on the news and what I had for breakfast that day. In the current political context, both in the US and several other democracies, I am of the growing opinion they would be in broad agreement that the biggest risk is not the perversion of democracy from suboptimal policies and subsidiary institutions (step 7), but rather a disastrous reversion to the pre-democratic institutions (step 6).

The most underrated aspect of democracy may very well be its fragility. While historical rarity may not be undeniable evidence of inherent fragility, but it would certainly suggest that once achieved it is worth the overwhelming dedication of resources, including the sacrifice of welfare optimality, to ensure its perserverance.

It cost a lot to get here. A lot. Sacrifices that are hard to even conceive of, let alone empathize with, while living within the profound luxury of modern life. I have no doubt that many of us will find ourselves underwhelmed with the policy platforms of the full menu of viable candidates made available to voters at every level of national and local office in a few weeks. So take this little scribbling for exactly what it is: an argument to vote against candidates that reduce the probability of our constitutional republic remaining intact. By comparison, all the other differences add up to a historical rounding error.

Is the Universe Legible to Intelligence?

I borrowed the following from the posted transcript. Bold emphasis added by me. This starts at about minute 36 of the podcast “Tyler Cowen – Hayek, Keynes, & Smith on AI, Animal Spirits, Anarchy, & Growth” with Dwarkesh Patel from January 2024.

Patel: We are talking about GPT-5 level models. What do you think will happen with GPT-6, GPT-7? Do you still think of it like having a bunch of RAs (research assistants) or does it seem like a different thing at some point?

Cowen: I’m not sure what those numbers going up mean or what a GPT-7 would look like or how much smarter it could get. I think people make too many assumptions there. It could be the real advantages are integrating it into workflows by things that are not better GPTs at all. And once you get to GPT, say 5.5, I’m not sure you can just turn up the dial on smarts and have it, for example, integrate general relativity and quantum mechanics.

Patel: Why not?

Cowen: I don’t think that’s how intelligence works. And this is a Hayekian point. And some of these problems, there just may be no answer. Like maybe the universe isn’t that legible. And if it’s not that legible, the GPT-11 doesn’t really make sense as a creature or whatever.

Patel (37:43) : Isn’t there a Hayekian argument to be made that, listen, you can have billions of copies of these things. Imagine the sort of decentralized order that could result, the amount of decentralized tacit knowledge that billions of copies talking to each other could have. That in and of itself is an argument to be made about the whole thing as an emergent order will be much more powerful than we’re anticipating.

Cowen: Well, I think it will be highly productive. What tacit knowledge means with AIs, I don’t think we understand yet. Is it by definition all non-tacit or does the fact that how GPT-4 works is not legible to us or even its creators so much? Does that mean it’s possessing of tacit knowledge or is it not knowledge? None of those categories are well thought out …

It might be significant that LLMs are no longer legible to their human creators. More significantly, the universe might not be legible to intelligence, at least of the kind that is trained on human writing. I (Joy) gathered a few more notes for myself.

A co-EV-winner has commented on this at Don’t Worry About the Vase

(37:00) Tyler expresses skepticism that GPT-N can scale up its intelligence that far, that beyond 5.5 maybe integration with other systems matters more, and says ‘maybe the universe is not that legible.’ I essentially read this as Tyler engaging in superintelligence denialism, consistent with his idea that humans with very high intelligence are themselves overrated, and saying that there is no meaningful sense in which intelligence can much exceed generally smart human level other than perhaps literal clock speed.

I (Joy) took it more literally. I don’t see “superintelligence denialism.” I took it to mean that the universe is not legible to our brand of intelligence.

There is one other comment I found in response to a short clip posted by @DwarkeshPatel  by youtuber @trucid2

Intelligence isn’t sufficient to solve this problem, but isn’t for the reason he stated. We know that GR and QM are inconsistent–it’s in the math. But the universe has no trouble deciding how to behave. It is consistent. That means a consistent theory that combines both is possible. The reason intelligence alone isn’t enough is that we’re missing data. There may be an infinite number of ways to combine QM and GR. Which is the correct one? You need data for that.

I saved myself a little time by writing the following with ChatGPT. If the GPT got something wrong in here, I’m not qualified to notice:

Newtonian physics gave an impression of a predictable, clockwork universe, leading many to believe that deeper exploration with more powerful microscopes would reveal even greater predictability. Contrary to this expectation, the advent of quantum mechanics revealed a bizarre, unpredictable micro-world. The more we learned, the stranger and less intuitive the universe became. This shift highlighted the limits of classical physics and the necessity of new theories to explain the fundamental nature of reality.
General Relativity (GR) and Quantum Mechanics (QM) are inconsistent because they describe the universe in fundamentally different ways and are based on different underlying principles. GR, formulated by Einstein, describes gravity as the curvature of spacetime caused by mass and energy, providing a deterministic framework for understanding large-scale phenomena like the motion of planets and the structure of galaxies. In contrast, QM governs the behavior of particles at the smallest scales, where probabilities and wave-particle duality dominate, and uncertainty is intrinsic.

The inconsistencies arise because:

  1. Mathematical Frameworks: GR is a classical field theory expressed through smooth, continuous spacetime, while QM relies on discrete probabilities and quantized fields. Integrating the continuous nature of GR with the discrete, probabilistic framework of QM has proven mathematically challenging.
  2. Singularities and Infinities: When applied to extreme conditions like black holes or the Big Bang, GR predicts singularities where physical quantities become infinite, which QM cannot handle. Conversely, when trying to apply quantum principles to gravity, the calculations often lead to non-renormalizable infinities, meaning they cannot be easily tamed or made sense of.
  3. Scales and Forces: GR works exceptionally well on macroscopic scales and with strong gravitational fields, while QM accurately describes subatomic scales and the other three fundamental forces (electromagnetic, weak nuclear, and strong nuclear). Merging these scales and forces into a coherent theory that works universally remains an unresolved problem.

Ultimately, the inconsistency suggests that a more fundamental theory, potentially a theory of quantum gravity like string theory or loop quantum gravity, is needed to reconcile the two frameworks.

P.S. I published “AI Doesn’t Mimic God’s Intelligence” at The Gospel Coalition. For now, at least, there is some higher plane of knowledge that we humans are not on. Will AI get there? Take us there? We don’t know.