"Magnifica Humanitas" is No "Rerum Novarum"

At the risk of seemingly disagreeing with "Magnfica Humanitas," it is still possible to compare that document with Rerum Novarum, upon which the new encyclical is based, and see clear differences, beyond the specific problems tackled by each document.

At the risk of downplaying artificial intelligence impact, which many could characterize as a general-purpose technology that will transform nearly every industry, the encyclical Rerum Novarum ("Of New Things"), issued by Pope Leo XIII on May 15, 1891, was not addressed “merely” to the impact of the industrial revolution on workers.

Laissez-faire economics; private property; socialist and Marxist ideas were paramount issues also tackled by Rerum Novarum. 

To the extent that Pope Leo XIV’s encyclical Magnifica Humanitas is modeled purposefully on Rerum Novarum, we can compare the two documents.

To be sure, Rerum Novarum focused on:

• potential exploitation of the working class

• Protecting workers

• Materialism, moral and spiritual issues

• ideological extremes (unregulated capitalism and socialism).

But Rerum Novarum also clearly established some clear and practical guidance for Catholic social teaching that are unmatched by any other religion or spiritual belief. 

Catholic social teaching means the Catholic church is clearly and officially:

• Opposed to socialism and collectivist economics

• A supporter of the fundamental right of private property

• A supporter of the right to form trade unions and other intermediate social institutions

• A supporter of market-based economies. 

Magnifica Humanitas is focused on AI’s impact on human dignity. And, to be sure, it warns of the dangers of concentrated “technocratic” power. 

But calls for ethical governance, transparency, accountability, subsidiarity (participation by communities), solidarity and orienting technology toward the common good and human flourishing are not in the same league as opposing both unrestrained capitalism and socialism (communism). 

Rerum Novarum defended the right of private property, for example. So Magnifica Humanitas might criticize unethical behavior, but it does not call for expropriation.

Magnifica Humanitas argues for an AI that serves humanity, not dominates it. We might see that as in line with the argument of Rerum Novarum. Some possible differences are that Rerum Novarum had more direct and practical implications. 

Rerum Novarum:

• Made opposition to socialism foundational for Catholic social teaching

• Specifically supported the role of labor unions and other social groupings

• Supports private property rights as essential for human freedom and creativity

• Supports market-based economics. 

Magnifica Humanitas, in my reading, includes nothing similar. 

Socialists and other leftists might argue Magnifica Humanitas supports expropriation of an AI firm’s  property. Since Rerum Novarum, that is in conflict with Catholic social teaching. 

Magnifica Humanitas contains no similar institutional practices (supporting labor unions as a counterweight and many types of intermediate institutions (family, guilds, social organizations) as a way of restraining the exercise of all social power by the state. 

Magnifica Humanitas contains no new proposals for restricting market economies or embracing socialism or expropriation. 

Instead, it is a moral exhortation; a statement of principles; a broad action to exercise prudence.  

As Rerum Novarum arguably shaped moral discourse, legitimized reforms, and encouraged balanced responses over revolution, so Magnifica Humanitas attempts the same. 

Still, one might read the new document as offering few practical pillars, compared to Rerum Novarum.

Equity Valuations are High, But are They "Too High?"

As common as it is to compare today’s artificial intelligence equity valuations to dot-com bubble levels, there is a reasonable argument to be made that the two periods are not similar, even if market leadership spikes resemble past booms. 

source: Bank of America Global Research, Leo Nelissen 

Of course, we might also note that each valuation boom “ended” at some point, with valuations normalizing. 

So it is rational to expect a repeat. 

On the other hand, the comparisons might be wrong. 

Forward price-earnings ratios for market leaders are nowhere near internet bubble levels, though that might not be the case for smaller growth names. 

source: Ritholz Wealth Management, Leo Nelissen 

The “complication” is earnings growth. So long as that continues, so does the support for valuation.

Magnifica Humanitas is not a Comprehensive Statement about Total AI Impact

Rerum Novarum (Latin: “Of New Things”) is an encyclical issued by Pope Leo XIII in 1891 that addressed the social and economic problems caused by the Industrial Revolution for workers and laid the foundation for modern Catholic social teaching.

To the extent that Pope Leo XIV’s encyclical Magnifica Humanitas is modeled on Rerum Novarum, we might also apply some of the same observations which can be made about the earlier document. 

An argument can be made that the encyclical focused on people in their role as workers, not in their role as consumers, arguably an issue that remains relevant today whenever policymakers talk about what is “good for working people.”  

People occupy multiple economic roles simultaneously:

• Workers (selling labor)

• Consumers (buying goods and services)

• Producers/owners (running businesses or owning capital)

• Citizens/community members (experiencing social and environmental effects). 

The Industrial Revolution affected each role differently, often creating losses in one dimension while generating gains in another. By extension, the same will probably be true for the concerns of Magnifica Humanitas. 

The Industrial Revolution created enormous increases in productivity, which led to:

• Lower prices for goods

• Greater product availability

• Rising real incomes over time

• Improved transportation and communication

• Longer life expectancy (eventually)

• Better housing, nutrition, and health outcomes (over the long run).

But as often happens, losses are concentrated and obvious while benefits are diffuse and hard to measure. 

Losses were concentrated among some worker segments, such as weavers, blacksmiths, coach drivers or other craftsmen whose jobs were automated.

But the same people often benefited as well. 

Consumer Benefit	Examples
Lower prices	Clothing, household goods, food transport
Greater variety	Previously unavailable products
Better quality	Standardized manufactured goods
Improved access	Railroads connected markets
Rising purchasing power	Real wages eventually increased

What was bad for some textile workers as producers often became beneficial for nearly everyone as consumers, a recurring pattern in economic change: losses are concentrated; gains are widespread and diffuse. 

The losers know exactly who they are. The beneficiaries are nearly everyone.

Even if long-run outcomes were positive, some occupations and generations bore significant transitional costs.

Industrial regions often prospered while other regions declined, with the negative effects you would expect on particular communities.

Consider the Industrial Revolution as creating two simultaneous realities:

Role	Typical Effect
Worker in disrupted industry	Often negative
Consumer	Usually positive
Entrepreneur	Often strongly positive
Society as a whole	Strongly positive over the long run

A handloom weaver in 1810 might be worse off as a producer but better off as a consumer. His or her children or grandchildren might eventually be substantially better off in both roles.

This framework will almost certainly be true of AI as well. 

The question is not simply whether AI helps or hurts "workers." People are simultaneously:

• Workers whose tasks may be automated or augmented

• Consumers who may receive cheaper and better services

• Investors whose retirement savings may benefit from productivity growth

• Citizens affected by broader economic changes.

The historical evidence supports the proposition that Industrial Revolution benefits ultimately became widespread and enormous, while many of the costs were concentrated among particular occupations, regions, and generations. The caveat is that for those who bore the costs, the losses were often severe, immediate, and personally significant even when society as a whole became much richer.

Magnifica Humanitas follows a similar pattern to Rerum Novarum. The warnings are stark; there is danger of dehumanization. The document does not address the almost-certain advantages and upside, anymore than did Rerum Novarum. 

As a moral argument about preserving human dignity and values, Rerum Novarum “succeeded.” But people are workers and consumers; creators or products as well as those who use them. 

The document did not address those aspects, being concerned solely with the impact of industrial production on people as workers. 

Magnifica Humanitas follows the same pattern, warning about dehumanizing AI impacts. The document does not attempt to assess the broad AI impact that might also be socially quite positive. 

The use of the term “tower of Babel” (Genesis 11:1–9) provides some insight to the framing. In Catholic theology, the passage is a warning about human pride and disregard for human dependence on God. 

So as with Rerum Novarum, Magnifica Humanitas seeks to guide action in terms of stewardship of technology to serve human ends and dignity. 

It is not a comprehensive statement about AI’s overall impact.

A View of AI that is Neither Left Nor Right

The encyclical about artificial intelligence Magnifica Humanitas, as with all encyclicals since 1891, is going to be misinterpreted using a left-right political framework that reflects the views of readers more than the author.

Catholic social encyclicals since Rerum Novarum (1891) are not predominantly "liberal" nor "conservative" in a modern political sense, though that sometimes is the implication some draw. 

Instead, Catholic social teaching is a consistent body of teaching that deliberately rejects mapping onto left-right categories, emphasizing principles such as:

• human dignity

• the common good

• subsidiarity (decision making as decentralized as possible)

• solidarity

• universal destination of goods. 

The critiques are balanced: unchecked individualism and unrestrained capitalism ("liberalism" in the classical sense) and collectivism or socialism all are said to be problems. 

Catholic social teaching strongly affirms the natural right to private property, for example, as a necessary condition for human freedom, creativity and flourishing. But the principles also include subordinating such rights to use in service of the common good. 

The issue of restraint on compulsion is implicit. Rights to private property are foundational, as a check on a monolithic state usurping all power. But also implicit is the need to voluntarily share resources. 

In other words, private property rights support subsidiarity, the principle that higher authorities should not usurp functions that lower-level bodies (individuals, families, local associations) can perform effectively.

On the other hand, Catholic social teaching also warns against greed, hoarding or political policies that prevent the sharing of outputs. 

Rerum Novarum often is characterized as a seminal document addressing the rise of industrial production. Hence the clear defense of the right to form labor unions. 

But Rerum Novarum also condemned socialism and supported the right of private property ownership, since ownership incentivizes responsibility, creativity, and foresight. 

Without the right to own property, people become dependent wards of the state. Property enables personal initiative and autonomy, which subsidiarity protects. 

Pius XI further formalized subsidiarity in Quadragesimo Anno (1931): higher bodies must not absorb what lower ones can do, as this violates justice and dignity. 

Likewise, Pope John Paul II in Centesimus Annus (1991) reaffirmed that private property maintains "the scope needed for personal and family autonomy" and extends human freedom.

So the balance: Property rights are legitimate, but also a form of stewardship for the common good.

That, in turn, is rooted in a Christian anthropology that views the human person as created in God's image:

• Free

• Responsible

• Creative

• Social.

Interpretations labeling them as "liberal" usually reflect selective readings by contemporary observers, missing the deliberate equilibrium. 

Pope John Paul II in Laborem Exercens, Sollicitudo Rei Socialis and Centesimus Annus: 

• affirmed labor's priority over capital in dignity

• critiqued Western liberal capitalism's excesses

• also criticized Marxist collectivism. 

Centesimus Annus was more open to markets and enterprise but insisted they serve the common good, not as ends in themselves. 

It was interpreted by some as pro-market and by others as critical of capitalism.

Popes Paul VI, Benedict XVI and Francis) also addressed development, peace and protection of the  environment (Laudato Si'), and globalization with similar critiques of materialism, inequality, and ideological extremes.

Magnifica Humanitas updates the tradition for AI. 

It calls for:

• ethical oversight

• regulation focused on human dignity

• the common good

• protecting work/inequality. 

It warns against power concentration (by tech firms or states), biases, job displacement, and treating AI as autonomous, while affirming technology's potential when subordinated to humanity. It invokes subsidiarity (local/intermediary roles, not top-down imposition) and solidarity.

This is not straightforward "AI regulation = liberal" paradigm. 

It supports intervening where markets or tech risk harming dignity, but within a framework upholding private initiative, property (including intellectual), and rejecting total state control or anti-human technocracy.

Selective emphasis is the issue. Media, academics, and activists often highlight critiques of inequality, markets, or corporate power (sounding "left") while downplaying defenses of life, family, religious freedom, subsidiarity, and private property (more "conservative" or traditional).

In polarized “Western” environments, support for unions, welfare elements, or regulation gets labeled "liberal," ignoring the Church's simultaneous opposition to abortion, euthanasia, gender ideology, and excessive statism.

The tradition is transpolitical: how well do policies serve the human person made in God's image? But encyclicals are not policy blueprints.

Catholic social teaching is neither liberal nor conservative. It challenges assumptions about autonomous individualism, materialism and ideological utopias, from the standpoint of protecting human dignity against dehumanizing forces.

It is an affirmation of human creativity, freedom and responsibility. But clearly not an endorsement of any political platforms.

How Zero User Interface Might Work

OpenAI is said to be working on a smartphone optimized for language models, something that might be called a " Zero User Interface" model, where the app-centric mobile environment becomes an agentic experience.

Zero UI represents a fundamental departure from screen-centric interaction, using voice, gesture, sound and biometric signals instead of graphical user interfaces or touchscreens, for example. 

It would represent a fundamental shift in how people interact with technology, much as earlier efforts have focused on form factors including glasses, pins or watches.

Instead of forcing users to navigate complex folder structures and discrete app icons, the device becomes an assistant that understands intent and executes tasks across the digital ecosystem on the user’s behalf, perhaps often without the use of a screen-based interface.

In a smartphone optimized for local language models, the interface moves from "command-based" (where the user clicks icons to trigger features) to "intent-based" (where the user describes the desired outcome).

Traditional UI forced users to know where to click and what to configure, for example. Zero UI systems shift from telling the computer what to do to specifying what outcome is wanted.

Instead of building a spreadsheet to assess customer churn, the user says “show me users who are likely to churn in the next seven days.”

Then the followup prompt might be “recommend the best channel to reach them.”

Without screens, feedback mechanisms become critical. Haptic vibrations in wearables or auditory cues must replace visual confirmations, for example.

• Unified OS-Level Intelligence: Rather than individual apps handling their own data and logic, the LLM acts as a central system service. It can perceive the current state of the device, understand the content on screen, and perform actions—such as sending messages, adjusting settings, or pulling data from services—without the user needing to manually open specific applications.

• Dynamic, Just-in-Time UI: Instead of a static home screen, the device generates interfaces on the fly. If you say, "Show me my budget for this week," it doesn't just open a banking app; it generates a concise, readable summary view tailored to your request, allowing you to act on the information immediately.

• Contextual Awareness: The system learns your routines, habits, and preferences. It becomes predictive—anticipating that you might want your calendar organized after a meeting or that you need specific controls available while you are driving—without needing explicit prompts.

• 
  

Without a visual display, the interface relies on glanceability, ambience, and human-centric feedback. 

Input/Output Method	Function
Natural Language (NLP)	Your primary "cursor." You speak, and the model understands nuance, intent, and tone.
Haptic Feedback	Provides non-intrusive alerts. A subtle tap could mean a notification, while a sustained pulse could confirm an action was successfully completed.
Ambient Audio/Chimes	Uses spatial audio and varied tones to provide system status or confirm understanding, reducing the need for constant verbal confirmation.
Gestural Recognition	Using cameras or proximity sensors to interpret hand movements (e.g., a "stop" motion to pause audio, or a "flick" to dismiss a notification).
Ambient LEDs/Light	Subtle light patterns can convey status or urgency, offering a "glanceable" way to understand system states without a full text-based interface.

The greatest hurdle: how do you know what the device can do if there are no menus or icons to guide you?

Successful "Zero UI" devices solve this by:

• Proactive Suggestions: The device doesn't wait to be asked; it learns to surface options when they are contextually relevant (e.g., "Would you like me to book your usual ride home?").

• Conversational Guidance: The AI acts as a guide, periodically informing the user of its capabilities or asking clarifying questions to narrow down intent, effectively "training" the user through natural conversation.

• Standardized Rituals: Just as we learned to "pinch to zoom" on smartphones, screenless devices will likely develop a set of universally understood physical gestures or verbal commands that serve as the "navigation system" of the future.

The idea is to present functions as a fluid, intelligent collaborator, not a collection of app silos, with the objective of minimizing the friction between your intent and the digital outcome.

No Supplier Likes Customer Concentration, But Sometimes It Cannot be Helped

Customer concentration in the hyperscaler segment is practically unavoidable, when a handful of customers represent such a large percentage of the market. 

In 2025, four hyperscalers (Amazon, Google, Microsoft, Meta) represented as much as 70 percent of all capital investment in the technology business, for example. 

Amazon, Google, Meta, and Microsoft control a massive portion of the world's total computing infrastructure, particularly in artificial intelligence. Together with Oracle, these hyperscalers own over 66 percent of global AI compute capacity.

source: Epoch AI 

To be sure, some suppliers (especially those which historically sell to enterprises, mid-market or small business) might not be as dependent on those few customers. 

Still, for some products (graphics processing units, high-performance memory and accelerators, for example), there are just a few big volume buyers. 

And as much as any supplier might wish to reduce reliance on just a few customers, that is hard to do in markets where a handful of buyers dominate:

• Google: Dominates the single-largest share of pure AI compute, holding about 25 percent of global capacity. While rivals rely on Nvidia, Google’s capacity is largely driven by its proprietary Tensor Processing Units (TPUs). In the broader public cloud infrastructure market, Google Cloud holds approximately 14 percent market share

• Microsoft: Holds an estimated 21 percent share of the global cloud infrastructure market. Through massive deployments of Nvidia GPUs and its strategic partnership with OpenAI, Microsoft accounts for an outsized share of enterprise AI workloads in the cloud

• Amazon (AWS): Leads the global cloud computing market with 28 percent market share. While historically focused on broad, general-purpose enterprise computing, Amazon is rapidly scaling its proprietary AI chips (Trainium and Inferentia) to capture a larger portion of specialized AI computing workloads

• Meta: Operating the largest internal compute footprint, Meta owns an estimated 10 percent of the world's total AI compute. Unlike the others, Meta's compute is largely dedicated to internal workloads, such as powering the massive recommendation algorithms for Facebook and Instagram, alongside its proprietary AI models. 

So, like it or not, customer concentration in some parts of the AI value chain is unavoidable. There are only a few “whales” on the buyer side. 

And some might argue there are similar few whales in the anchor tenant category as well. Consider the role OpenAI and Anthropic play as anchor customers for the hyperscaler compute “as a service” providers. 

source: The Information 

I Don't Know How This Changes, But it Has to Do So

In a survey two researchers  conducted in April 2025, they found that 37 percent of Americans reported having had a political breakup, mostly with friends.

That is horrific. It means the tolerance and respect for political differences a democracy might require has been widely abandoned by a significant percentage of citizens. 

 

source: Mertcan Güngör , Peter Ditto 

Of those who reported political breakups, 62 percent had a breakup with a friend (23 percent of the full sample), 40 percent with a family member (15 percent of the sample), 29 percent with a coworker (11 percent of the sample), and 10 percent with a romantic partner (4 percent of the sample), the researchers report. 

Most (56 percent) reported losing more than one kind of relationship (21 percent of the sample). 

In another survey we conducted a week before the 2024 election, 69 percent of breakups happened with a friend; 20 percent happened with a family member, five percent with a romantic partner and two percent with a co-worker. 

Most of us might instinctively recognize that political polarization can weaken a democracy because it turns fellow citizens into enemies. 

In healthy democracies, opposing sides are seen as political adversaries to compete against and at times to negotiate with.In deeply polarized democracies, the other side comes to be seen as an enemy needing to be vanquished.

The danger then is that legitimate policy compromise comes to be seen instead as moral failure. So polarization then leads to, and rewards, extreme positions. And that makes compromise much more difficult, if not impossible. 

Such polarization also erodes trust in government and leaves urgent issues unresolved, as the different factions cannot find common ground. Worse, it leads to violence. 

As for me, I have no choice but to reject polarization. That doesn’t mean accepting a “squishy middle” between the extreme positions of either dominant party. It does mean rejecting the idea that either party any longer has the “best interests of the nation” uppermost and consistently in mind.  

Is Anthropic Worth More than OpenAI?

Anthropic has raised $65 billion in Series H funding led by Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital, valuing the company at $965 billion post-money, a level that exceeds some estimates of OpenAI valuation of $852 billion.  

The round was co-led by Capital Group, Coatue, D1 Capital Partners, GIC, ICONIQ, and XN. Significant investors in this round include AMP PBC, Baillie Gifford, Blackstone, Brookfield, D.E. Shaw Ventures, DST Global, Fidelity Management & Research Company, General Catalyst, Insight Partners, Jane Street, Lightspeed Venture Partners, MGX, NTTVC, NX1 Capital, Situational Awareness LP, T. Rowe Price Associates, Inc., T. Rowe Price Investment Management, Inc., and Temasek. It also includes $15 billion of previously committed investments from hyperscalers, including $5 billion from Amazon.

Strategic infrastructure partners Micron, Samsung, and SK hynix also were part of the round. 

Nobody knows whether artificial intelligence is truly a financial bubble, or, if it is, when it bursts. Comparisons to the internet bubble are made and also dismissed, but at least so far, the sometimes-parabolic moves continue.

Much hinges on perceptions of future value. 

And at least so far, nobody wants to fall behind.