I strongly recommend you read this post from the Multipolarity Substack. Here’s a concluding snippet:

Dr Powell’s model suggests that the war is rapidly nearing a tipping point. Ukraine is approaching the fulcrum beyond which the weight of the war tips its forces into rapid depletion, allowing the Russian military to start achieving much more significant territorial gains. In turn, this would lead to accelerated Ukrainian losses through the ruthless reality of the square law. This road heads toward an eventual Ukrainian collapse.

Ukraine’s effective combat power (a composite of manpower, machinery and munitions) is depleting, the model shows, at a net rate that outpaces its replenishment, while Russia’s holds steady or grows marginally. This imbalance, compounded by recent reductions in Western support, suggests a tipping point where Ukrainian force density thins below viability, triggering rapid territorial losses and operational collapse.

That could be foreclosed by, for example, Western troops from any of the various NATO countries but that in turn risks widening the war into global thermonuclear war.

Ukrainian esprit de corps makes little difference. Innovations in warfare make little difference. What matters is how many troops can be fielded by each side.

The TL;DR version: come up with a minimally livable solution quickly.

It has been ten days since my right eye was operated on and almost 25 days since my left eye was operated on. Without eyeglasses I see roughly as well as I did five years ago (without eyeglasses). I use off-the-shelf eyeglasses for the near-sighted I purchased from Amazon for walking around and watching television. Reading, either with or without eyeglasses, is a strain. Driving, with or without eyeglasses, would be dangerous.

My vision is not monotonically improving. Today, for example, my vision using eyeglasses is worse than my vision using eyeglasses was yesterday. I have hopes that the new prescription eyeglasses I will receive after I heal in two-three weeks will enable me to read, drive, and generally function.

In an earlier post I had said that I was planning to elaborate on some of the ways that those who have developed artificial intelligence models like ChatGPT, Claude, and so on may not understand their own creations. This is that post.

The Sapir-Whorf hypothesis is simple to state but far-reaching in its implications. It is that language affects cognition. It comes in two forms, the strong Sapir-Whorf hypothesis, language constrains thought, or the weak form, language makes thinking in certain ways easier. There is substantial evidence that language influences cognition, particularly in perception, categorization, and memory and it has been widely accepted for nearly 60 years. It is the weak form to which I will refer in the balance of this post.

The key point is that It applies to generative artificial intelligence, too. Algorithms designed by native speakers of English and trained using content written in the English language will differ from algorithms designed by Mandarin, Yoruba, or Arabic speakers and trained using Mandarin, Yoruba, or Arabic content will differ in ways we can’t even predict. They can still be grammatically correct or be intelligible but they’ll feel “off”. They won’t uniformly make intuitive sense. Although English and German are closely related linguistically, models created by native speakers of German and optimized for German users will be subtly different from models created by native speakers of English and optimized for English-speaking users.

That won’t be a dealbreaker but it will impair their commercial viability, particularly in certain fields like medicine or law. I strongly suspect that this is an aspect that the developers of gAI models are not sensitive to. There is no cognitive layer on which the linguistic model resides. It’s the other way around. It also may not be something that American managers are sensitive to but that doesn’t mean that it doesn’t apply. It just means that models developed by non-English speakers will not be as useful to native speakers of English as they might be.

The precise linguistic mechanisms are beyond the scope of this post; the important point is simply that different languages encode meaning, context, categorization, and association differently, and models trained on those languages will necessarily reflect those differences. A model can produce flawless English and communicate clearly but still not feel fully native in its assumptions or reasoning patterns. That has serious implications for commercial utility.

That’s why, for example, I don’t worry too much about China’s competing with the U. S. in gAI. I have every confidence in the ability of native speakers of Mandarin to develop their own generative AI models. Models trained primarily on English-language content and optimized for English-speaking users will differ from models trained primarily on Mandarin-language content and optimized for Mandarin-speaking users. Is there enough Mandarin language content on which to train them? I don’t know. Indeed, I doubt that anyone knows. And if the models are train, again, using English language content the results will be subtly different. Whether these differences arise primarily from language structure itself or from the cultures embedded in the training corpora may not matter operationally; the resulting models will still exhibit different intuitions and priorities.

The Chinese are absolutely capable of developing their own models running on their own graphics processor units (GPUs). At the present state of technology those GPUs will require about twice as much electricity as GPUs built in Taiwan or the U. S.

The same is true of developing generative AI models in other languages as well, i.e. Farsi, Arabic, Tagalog, and so on. But the Sapir-Whorf hypothesis will continue to apply.

On May 15^th Pope Leo XIV published the first encyclical of his papacy, Magnifica humanitas (“wonderful humankind”). I wanted to summarize it briefly and make a few observations. I will refer to it here as MH.

MH is rather clearly and intentionally evocative of Leo XIII’s historic encyclical, Rerum novarum (“of new things”—RN) but it differs from the latter in some notable ways. Here are its themes by chapter:

Intro & Biblical Framework Two biblical images frame MH: the Tower of Babel (technology as prideful self-sufficiency that dehumanizes) versus Nehemiah rebuilding Jerusalem’s walls (shared, humble, community-oriented work with God at the center). The encyclical calls everyone to choose the “Nehemiah path.”

Chapter 1 This chapter is a lengthy survey of Catholic social teaching from Leo XIII through Francis, showing how each era produced a response to its “new things.” AI is this generation’s res novae.

Chapter 2 This chapter restates core principles, namely the foundational pillars of human dignity (rooted in being made in God’s image, not in productivity), the common good, the universal destination of goods, subsidiarity, solidarity, and social justice. Notably extends the “universal destination of goods” to include algorithms, data, digital platforms, and patents, arguing these cannot be monopolized by a few. The phrase “universal destination of goods” was first enunciated specifically in Vatican II.

Chapter 3 Technology and Power. Here His Holiness critiques the “technocratic paradigm” (efficiency and profit as the measure of all things). Warns against transhumanism and posthumanism, ideologies that treat human limitation as a bug to be fixed. Rejects the idea that AI can replace what is essentially human. Raises concern about private tech companies whose power now exceeds that of many governments.

Chapter 4 Truth, Work, and Freedom — Three specific threats:

• Truth: AI-driven misinformation endangers democracy; calls for “an ecology of communication” and stronger digital education.
• Work: Automation and AI-driven unemployment threaten human dignity; wages and meaningful work remain central moral concerns.
• Freedom: Digital addiction, behavioral manipulation, and algorithmic surveillance are described as “new forms of slavery.”

Chapter 5 Power vs. Love Here MH condemns the normalization of war, autonomous weapons systems, and the collapse of multilateralism. Calls for disarmament (including of rhetoric), diplomacy, and a “civilization of love” as the alternative to a “culture of power.”

As moral exhortation directed toward individuals, MH is often thoughtful and compelling. As a framework for political economy and governance, however, it raises significant unresolved questions. MH deviates from RN in that in the latter Leo XIII took pains to support the right to private property. MH omits that. As a guide for collective or political action, however, the omission renders it problematic.

Make no mistake, this is no minor omission. Large portions of the modern American economy depend on the creation, monetization, licensing, and protection of intellectual property and digital platforms. That includes the pharmaceutical industry and substantial chunks of the healthcare and legal sectors not to mention Google, Microsoft, and Facebook. The omission is significant because Catholic social teaching has historically balanced the universal destination of goods against an explicit defense of private property. MH appears to shift that balance toward social obligation without clearly defining the limits of legitimate ownership in the digital economy. My suspicion is that some clarifications to MH will be forthcoming soon.

RN defended private property partly because property dispersed power and protected mediating institutions against centralized authority. MH confronts a world in which digital property and network effects can instead concentrate authority at unprecedented scale. The encyclical therefore appears less concerned with property itself than with asymmetries of power emerging from informational monopolies.

Furthermore, calls for international governance introduce serious sovereignty problems for national governments. As I’ve noted before, effective world government implies global consensus and little could be clearer than that there is no such meaningful global consensus.

I wanted to remark on this Washington Post editorial.

On Thursday, President Donald Trump abruptly pulled the plug on the signing of an executive order that would have given federal agencies an early look at the nation’s most powerful artificial intelligence models before their public release. That’s good news: Even the supposedly voluntary review system under consideration could have hardened into a government chokepoint on U.S. AI development.

Here are some additional significant snippets:

The order would reportedly have created a framework for leading AI labs to share their most advanced models with a coalition of national security agencies before public release. It would also have established a joint cybersecurity clearinghouse, run by both government agencies and private-sector representatives, tasked with finding and patching vulnerabilities in the nation’s digital infrastructure before adversaries could exploit them.

and

A coalition of more than 60 Trump allies, organized under the banner of Humans First and backed by Steve Bannon, wrote the president urging mandatory government approval of frontier AI systems before release. Kevin Hassett, the director of the National Economic Council, publicly floated an FDA-style regime earlier this month in which AI models would have to be “proven safe” before they could reach the public.

and

AI poses real cybersecurity risks, but they need to be addressed with care and precision. The president is right to be wary of creating a bureaucratic review regime that erodes America’s edge.

I’m going to divide my remarks into four sections:

• The problem
• The urgency
• What the creators don’t understand
• The solution

The problem

The snippets above call out the national security implications and the “safety” implications. In addition to those there are infrastructure issues and liability issues. The infrastructure issues are highlighted by this graph:

U. S. consumption increased rapidly from 1970 to about 2000, plateaued due to various efficiencies realized, and, driven largely by generative AI and electric vehicles, began to increase around 2020. The rapid build-out of data centers and increased adoption of EVs will ensure that growth continues for the foreseeable future.

At some point utilization will exceed the grid’s capacity. That is likely to produce a series of effects. First, producers may implement controlled voltage reductions of 5–8% to prevent cascading failures. Historically, that has frequently been followed by “rolling blackouts”. Together those will produce wear-and-tear on devices containing electric motors, such as refrigerators, air conditioners, and well pumps. The costs of these effects will not be borne by commercial consumers whose contracts ensure continuous use. They will be borne by household consumers.

Neither executive agencies nor Congress possess the technical knowledge or adaptive speed necessary for effective ex ante control of frontier AI systems. We are in terra incognita. The machine learning researchers who build these systems understand the architecture and the training process. They do not understand and have said publicly they do not understand what the systems have learned, why they produce the outputs they produce, or what they will do in novel situations. That is an accurate description of the current state of knowledge.

The urgency

Basically, we can’t wait for studies or well-formed regulations. The first lawsuits against gAI companies are already being filed. Regional power constraints associated with accelerated data-center growth are already emerging in several U.S. markets, particularly in Texas where data centers are being built. The pace at which data centers are being built is considerable.

What the creators don’t understand

The enormous irony in this is that not only do elected officials or any foreseeable regulatory agency lack the knowledge and understanding, the creators of gAI don’t have the understanding, either. I’ll flesh that out in a later post.

The solution

Fortunately, there is a prospective solution but it’s one I believe with be very controversial and result in considerable backlash: strict liability. Under a regime of strict liability those harmed by gAI would not need to show intent or negligence on the part of the AI companies—all they would need to show are involvement of the companies and harm.

The response of the companies and, presumably, some economists would in all likelihood be that would have a chilling effect. That is an alarmist claim. Strict liability would force the industry to price risk realistically rather than externalizing it. Strict liability would alter incentives but that is precisely its purpose. The companies could continue to proceed at their own pace. It would only ensure that the risks of their actions would be borne by those who benefit most—the companies rather than those who benefit least—ordinary household users and consumers of electricity.

Not being able to read easily, see clearly, or drive is really a pain. Yesterday I walked over to Whole Foods and picked up a few things. That much I can do.

I’m not experiencing any discomfort at this point. At least I’m able to walk around. I wear the eyeglasses I bought from Amazon when I do—it’s a bit of a strain but I can see reasonably clearly when I do.

I figure I have about two more weeks of this incapacitation before I get a new pair of glasses which will enable me to read, watch television, and drive.

Well, it’s done. I now have artificial vision. I noticed almost immediately that my vision without glasses was clearer than it had been since I was in fourth grade. Colors were truer. Everything is still out of focus but not as out of focus as it used to be.

My old prescription is now completely obsolete and it will be a month before it makes any sense to get a new one. Following my ophthalmologist’s instructions I purchased a pair of “cheaters” from Amazon. They’re not perfect but they give me hope that my vision will be easily correctible.

So, now reading is difficult and driving impossible. This will be the longest time I’ve been unable to drive since when I worked in Germany more than 50 years ago. I didn’t drive at all when I was there—I didn’t need to.

I’m only able to type this post because I’m a touch typist. At my high school you had to pass a touch typing test to graduate. Thank you, SLUH.

I’ve been sitting on this post for a while.

Chicago is a city of neighborhoods. You hear that a lot, and it’s true. Chatham, Sauganash, Bronzeville, South Shore all have distinct characters, histories, and loyalties. What they increasingly share is a Walgreens closing. ABC7 ran a story last month about Chatham residents furious over the upcoming closure of the Walgreens at 86th and Cottage Grove. The story is mostly a string of quotes from upset residents, and the upset is real. One man managing kidney transplants and diabetes who takes 14 pills a day, a woman in an electric wheelchair who lives down the block. These are sympathetic people facing a genuine inconvenience, maybe worse.

But the story raises questions it never bothers to ask. I did some quick checking, the kind of thing a reporter could do in twenty minutes. After this closure, Chatham still has three major chain drugstores and several independent local pharmacies. This is not a pharmacy desert. The nearest replacement Walgreens is 1.3 miles away, and Walgreens is even offering 90 days of free prescription delivery to ease the transition.

Here’s some useful context ABC7 didn’t offer: I live in Sauganash, a neighborhood with a very different demographic profile than Chatham. Right now, today, I am as far from my nearest Walgreens as Chatham residents will be after the closure. Nobody is writing outrage stories about Sauganash.
One alderman called this “pharmaceutical genocide.” Another called for charging Walgreens with “first degree corporate abandonment.” That’s vivid language. But Walgreens isn’t a public utility. It’s a company that expanded aggressively into neighborhoods across Chicago for decades, then, when shrinking its footprint made business sense, started closing stores. That’s what large national chains do. They have no covenant with the neighborhood. They never did.

The actual story here isn’t Walgreens’s betrayal. It’s that somewhere along the way, communities stopped patronizing local pharmacies and shifted their loyalty and their prescriptions to national chains that were cheaper and more convenient. The local pharmacist who knew your name and would make a delivery in a pinch got replaced by a corporation that optimizes for shareholder value. When that corporation decides your neighborhood is no longer worth the trouble, you discover that the relationship was always one-sided.

Chatham’s anger is understandable. But the lesson isn’t that Walgreens owes the neighborhood more. It’s that neighborhoods can’t outsource their civic infrastructure to companies whose headquarters are in Deerfield and whose loyalty runs exactly as deep as the profit margin.

Tomorrow (at an ungodly hour) I have my second cataract surgery scheduled. I don’t have as much foreboding about it as I did the first but I don’t look forward to it nonetheless.

My left eye, the one that has already been operated on, is presently in a bizarre inbetween state. There is a notable difference among the vision using that eye alone, the vision using both eyes (with or without glasses), and the vision with my right eye (with or without glasses). With my left eye without my glasses I can read from a distance of about nine inches or closer but the lines of print are sort of wavy. With my glasses I can’t read at all using that eye. With my right eye I can read fairly normally with or without my glasses. My vision is slightly fuzzy now with or without my glasses.

Colors as seen by my left eye are noticeably different. They’re brighter, clearer. As seen by my right eye I now perceive a sort of yellowish tinge to them.

I suspect that this “inbetween” condition will continue for the next month (at least) until I get my new prescription glasses. That will make my regular considerable volume of reading that much more difficult if not completely impossible.

For someone like me, accustomed to spending much of every day reading, that prospect is more disorienting than the surgery itself