Microsoft May View AI As a Super App
June 4, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
One of the simplest tricks in debate has a bunch of names. Game players like to say “pop up a level” or just “level up, dude.” Those with exposure to the rigors of traditional indexing say, “Just put it in a different cluster.” Silicon Valley types infused with the zeitgeist of incomprehensibility offer, “Do the meta play.” A rose by any other name still smells like an old age home on Sunday morning.
A great thinker wonders if a rose is actually a cat. Perhaps he can sell this concept and make lots of money? Thanks, MidJourney. Good enough.
The concept is that one has a thing and one wants to make that thing appear more profound, new, zippier, or imbued with qualities a person unfamiliar with “level upping” does not understand, see, or comprehend.
I want to point to an example described in “Exclusive: Microsoft Is Building a Super App That Combines Coding, Chat, and Other Copilot AI Tools.” (I like the exclusive part because by my count there are about a dozen outfits building super apps; however, as a dinobaby, I am generous. I think the “exclusive” is that no other big time real business news outfit has ever reported on Microsoft doing the clustering play or the “pop up a level, dude” tactic.)
Be that as it may, the “exclusive” write up reports:
The software giant is working on a one-stop shop that would connect its GitHub Copilot coding assistant, Copilot chat function, Copilot Cowork tool, and a new agentic workflow capability internally named Autopilot into a single app, according to two sources familiar with the project, who spoke on the condition of anonymity to discuss a platform that hasn’t yet been released.
Yep, a meta-app that will deliver a “cohesive product.” Isn’t this an admission that after three years of AI innovation, users of Microsoft software, hardware, and services are generally confused about what Copilot does what and how. The effort to data has caused a number of Microsoft users to want a way to turn off AI everything in Microsoft “experiences.” Some third parties have been paid big bucks to make the Copilot thing more obedient. But for most users, AI has begun to morph from “gee, this is cool” to “gee, this is a bit of a problem.”
The write up continues:
There may also be a toggle function for a user to go back and forth between their personal and enterprise 365 Copilots. A user will still be able to access their Copilots outside of the super app.
If this statement is indeed true, doesn’t this suggest that Microsoft is just foolin’? There will be many Copilots, not a single super app like the ones available from a Chinese outfit or from the alleged criminal Pavel Durov of Telegram and VKontakte fame. I won’t mention the others because then I will be revealing some of my upcoming lecture for the cyber fraud folks in Virginia in a few weeks. Some of my information, in my dinobabyish opinion, is indeed “exclusive.”
How lost in AI weirdness is Microsoft? May I suggest that this statement from the Fortune article helps answer the question? Here you go:
Microsoft in the past year has undergone one of the largest corporate reshuffles in its history that has included a string of high-profile departures and reorgs throughout its businesses. In April, it announced its first-ever employee buyout offer, aimed at its most long-tenured employees. At next week’s Build conference, Microsoft AI Chief Executive Mustafa Suleyman is expected to unveil new proprietary AI models. Suleyman, who once led consumer Copilot, has focused on models since the restructuring in March.
This is not recalibration in my view. This is scrambling and then trying to figure out how to put the eggs back in their shells.
Can Microsoft level up? Will the company survive the other super app developers? Will there be a reframing of the Microsoft AI strategy that includes security, defense against open source options, and the predatory instincts of Googzilla-type organizations in the US and from — yes, it is really true — other countries?
Confident in your answer? Hit those prediction markets.
Stephen E Arnold, June 4, 2026
Good Enough AI May Not Be Good Enough
June 4, 2026
Rest Of World explains something that we all knew: “The Agentic Divide: Why “Good Enough” AI Isn’t Enough To Survive The New Economy.” What this means is that many AI chatbots are being released and some are better than others. That is to be expected, but no one expected there to be chatbot inequality and its economic consequences.
Chatbots are expected to take on monotonous tasks thus freeing up employees for other work. A problem, however, is that most chatbots still fail at basic facts and Big Tech companies are still launching agents to handle more complex tasks. Here is what will happen:
“As AI agents become more integrated into the economy, companies and entities that deploy them will benefit disproportionately compared to those that cannot, Nick Srnicek, a senior lecturer in digital economy at King’s College London, told Rest of World. ‘We will see new inequalities of access, scale, quality and trust: divides between those who have agents and those who don’t; those who have good agents and those who have bad agents; those who have many agents and those who have few agents; and those who can trust their agents and those who cannot,’ he said.”
China and Singapore apparently introduced frameworks to regulate AI to focus on accountability and safety. Chinese local governments are boasting single-employee companies that rely on AI chatbots. India is even embracing AI to cut costs and scale quicker.
Better chatbots are already advancing companies, saving them money, and advancing in the markets. Another problem is that if governments and companies rely on chatbots, they can be canceled at anytime without notice. There are also security concerns:
Matthew Sharp, a research affiliate at the Oxford Martin AI Governance Initiative [said]:
‘The same infrastructure can become a surveillance layer if the data flows, defaults, and oversight are wrong,” Sharp said. “The safeguards around consent, purpose limitation, auditability, and political independence would need to be real, not merely architectural.’”
My fear is that “good enough” is the new standard of excellence. A race to dumbing down. Outstanding.
Whitney Grace, June 4, 2026
Telegram AI: A Coocoon Sort of Emerging
June 3, 2026
Telegram has continued to nudge its AI initiative forward. Unlike the infrastructure approach taken by US big AI tech outfits (BAITs in my lingo), Telegram has designs on a cheaper approach. The company wants to rent AI compute from data centers with unused cycles. Telegram Notes takes a look at the approach in a new article titled “The Telegram’s Cocoon AI: Not Yet Mature.” (“Mature” is a more sophisticated way of suggesting that the AI initiative is not yet aloft.) The company continues to make strategic and tactical shifts. Some of these are more dramatic that renting cycles; for example, dumping the TONcoin “name” for the original Telegram crypto called “GRAM.” Telegram is definitely an interesting organization.
Stephen E Arnold, June 3, 2026
Google AI: Speed Means Googlers Do Not Know What Is Happening to Users
June 3, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
I just read “Gemini User Hits 5-hour Usage Cap after a Single Prompt, Google Responds.” The article explains that the many changes to Google’s smart services are not understood by users or Googlers. Remarkably the article explains that no one knew AI usage limits would cause prompts to fail. Plus the write up includes a stunning quote from a Googler; to wit:
“Yikes, let us take a look!”
Okay, but it is clear from the story, that Googlers just released changes. No one took a “look.” Isn’t this interesting? Let me share some thoughts about why unintended consequences are rarely considered and why those involved in online products and services don’t bother to do what I would call “real work.”
Thanks, Midjourney. Good enough.
Don’t get me wrong. I understand the management problem. When I was in high school, I took classes at the University of Illinois. The lead professor (Dr. Shattuck, if I recall correctly) told us, “You are exceptional.” Who cared? We were living in a dorm, not a parent within miles. Then when I was talking with a smooth operator at the blue chip consulting firm, Ron Something said, “You are one in 10,000.” Both of these people were in the cow herd waste output business. I think the Google does the same thing. I had the thrill of being in a meeting at the Big Dog of Search when one senior manager said, “Here’s our GLAT.” I looked at the weird green document and replied, “It looks like the SAT. What is it?” The Googler laughed and said, “Some people who want to work here have to take the test because we’re Google.”
Yeah, right. In each of these cases, the people desperately want to convince themselves that they are gifted, the blessed ones, or psychologically off the norm. What happens in each of these “organizational constructs” that blend self-delusion with a task and those involved in the task is the following:
People do their think. These individuals know they are special. Therefore, just do it. One person with whom I worked at an outfit in Columbus, Ohio, loved the word “decider.” These people are deciders. What’s the result of an organization of deciders? Here are some characteristics:
- Most people in the organization have no idea what the other person in the adjacent cube or chair is doing.
- The rarely attentive middle managers whether in person or in some hippy dippy digital form like a Slack or a Zoom don’t know what questions to ask. Consequently, only a big win or a catastrophic screw up captures their attention. Most of the time, modern managers are clueless and “don’t have time” to be enriched by clues.
- The leadership of the organization floats weirdly in a bubble which blocks most negative or unpleasant inputs. Thus, most “leadership” slips into or actively embraces the “I’m special” thought process. Rules and social norms are not that important.
The Google craziness is not localized in Google. It exists, to greater and lesser degrees, at the BAIT outfits (BAIT is my lingo for big AI tech). These firms want to make the rules for everyone else. Most of them operate as if they were sovereign powers. This explains the disdain Elon Musk seems to display to the French judiciary’s criminal charge against X.com/Grok and why Meta’s cooperation with UK authorities is not exactly a priority when one’s firm is struggling in the AI World Cup.
The result, if my analysis is accurate even if based on my personal experiences, are situations like the one described in the article. The same approach has manifested itself in Microsoft’s crawfishing on some of its AI initiatives. The key point I want to make is that these type of management methods are now the norm. Whether it is the hapless owner of a Dodge RAM truck or a person who buys no name ear buds from an Amazon-type vendor, the new management methods virtually guarantee problems for a client, customer, or user.
Whom can one blame? Sorry. There is no one. The failure to do the basics of a “good job” have been displaced by the idea that superior individuals exist, can make decisions in a vacuum or a small circle of contacts, or just don’t care due to incentives. I am not blaming anyone, not even the surprised Google AI wizard. Welcome to the datasphere circa 2026. I am glad I am old.
Stephen E Arnold, June 3, 2026
Surveillance Pricing Is Dynamic
June 3, 2026
What an outstanding idea? Put an app on a customer’s mobile device. Allow the user to opt in for special offers and automatically allow tracking. Combine these cute ideas with digital shelf pricing and what do you get?
One answer is a Ph.D. making videos called “They Call It Dynamic Pricing. It’s Surveillance Pricing.” As a YouTube video that explains how something works in Corporate America. El is a good presenter. But she does point out that when people watch a price change in real time, some folks get edgy.
Brick and mortar retail is the definition of competition. Most US big-time retail outfits want to extract the most profit possible from their customers. One way they ramp up the competition and increase their bottom dollar using surveillance pricing-a form of dynamic pricing.
Dynamic pricing once meant cutting the cost of paying humanoids to put little printed stickers on shelves with dog food. No more. Just feed in the parameters and let the digital tags respond. What happens when the system in a Kroger-type store “recognizes” a humanoid known to buy premium products?
The prices change according to that “customer’s” personal data: browsing history, location, purchasing behavior, etc. That’s why you see digital price tags everywhere in stores these days. Automatgically retailers can change prices or let a smart algorithm do the boosting. Scripps News published “Maryland Becomes First State To Pass Bill Banning ‘Surveillance Pricing.’”
The Protection From Predatory Pricing Act was passed in Maryland in April 2026. Governor Wes Moore will sign the bill into law. Retailers who violate the law will be met with deceptive trade practices fines and lawsuits.
“ ‘Marylanders deserve to know that the price they see on the shelf is the price they will pay at the register,’ Moore said in January. ‘Our administration is laser-focused on protecting Marylanders from skyrocketing costs. At a time when Marylanders are already stretched by the rising cost of groceries, housing and everyday necessities, we must ensure that new technologies are not used to drive up the bill for working families.’”
It wouldn’t be a big deal if that meant people got lower prices based on their data, but we know that’s not what will happen. Prices will be jacked up and supply and demand are no longer part of modern economics. Maryland, I salute you. My hunch is that the big corporates will win and Maryland’s attempt to make one facet of modern life less dystopian will flame out.
Whitney Grace, June 3, 2026
AI: The Political Tool on Steroids
June 3, 2026
Dictators and other authoritarian bad actors use whatever tools they can for propaganda. Propaganda is an extremely powerful way to shape people’s minds. It’s only gotten more powerful with the advent of social media and now AI algorithms. Vox reports that there are new and exciting ways the manipulate people with AI: “The Hidden Way Dictatorships are Shaping What AI Tells You.”
Here’s an alarming fact: more than a billion people turn to chatbots for advice and information, erotica, robot-plagiarism, and other stuff. ChatGPT has 900 million weekly users.
As more people use AI chatbots, they will be able to shape how people perceive information and society. They’re already changing how people perceive things. The biggest fear is how bad actors could use AI chatbots for propaganda:
“This has generated fears about chatbots’ potential to spread state propaganda. Such anxieties generally center on the prospect of major AI labs consciously designing their LLMs to favor pro-regime perspectives while suppressing dissident ones. And there is some basis for this worry: The Chinese AI company Deepseek programmed its model to evade discussion of the Tiananmen Square massacre and other topics inconvenient to the Chinese Communist Party.”
How are governments responding to AI? I shudder to think.
Whitney Grace, June 3, 2026
Traditional Consulting: Becoming Just Less Average
June 2, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
I have an AI bias. My personal experience with different smart software systems is what I would call “mostly average.” Somewhere along the line, I learned about research that demonstrated the obvious. Run the same query set against a group of AI models. Run the queries every couple of weeks. At the end of six months. Look at the outputs. The person who explained this research to me wanted me to tell him what the test showed. I said, “Good enough similar outputs.” He looked at me and asked, “How did you know? Did you read the study?” I said, “The methods produce a good enough because that’s how the math works.”
An AI-centric management consulting firm learns a painful lesson. The work was just good enough but not good enough to prevent immediate termination. Thanks, MidJourney. You are indeed good enough.
I encountered this “good enough” when we worked on some projects for a then-famous enterprise search system based on Bayesian statistics. Train up the system, ask queries, and watch the precision and recall diminish over time. Re-train the system and one can observe the same degradation. Why? The answer is that Bayesian and Bayesian-related methods “drift.” Users have novel problems, but the model is not aware of the user’s context and how the words or other symbols operate in the unknown context. Therefore, the outputs have to converge. This is the engine of drift.
I thought about this “drift” and the convergence to the mean when I read “How AI Threatens the Giants of Consulting.” (Heads up: The story sits behind the weird orange newspaper’s paywall. Don’t complain to me. Just subscribe.) The article is interesting, but it did not touch upon this “good enough” angle, nor did it explain where the “value” comes from when hiring a blue-chip consulting firm. That’s okay. To an outside observer, one sees AI replacing a certain type of employee at a blue chip consulting firm. The obvious impact is staffing, billing, and how the work is completed.
The write up makes some good points; for example:
- Blue chip firms developed a system to scale to handle big projects. The write up does not explain what scale means in a large, global study on a volatile topic. Let me add some color: Low tier and mid tier consulting firms struggle, even with AI, to handle certain types of projects. AI would not be particularly helpful in the study of world economic change I worked on years ago. Consultants had to interview individuals in specific institutions and use that information to inform other components of the research project spanning a dozen countries. AI can do some things, but it cannot do this type of knowledge work. Maybe some day? But today to pull this original research off, one has to work for a blue chip outfit.
- AI makes it seem that anyone can set up, market, operate, and avoid litigation by become a next-generation consultant. Okay, maybe. Let me put in my two cents: Setting up an AI centric consulting firm or boutique and staying in business are two different things.
- Today’s consulting firm clients demand fee linked to outcomes, not just hours on time sheets. My observation: That’s true for certain engagements and certain types of firms. However, blue chip firms once enjoyed client repeat business in the 80 to 85 percent range. This means that the blue chip firms capture a client and can bill equivalent fees and present the invoice any way the client requires. A job for a Fortune 50 CEO may be a single line item: “Consulting services for April 2026, $2.4 million.” A government job uses pay grades, hours, engineering change orders or scope changes to generate an invoice in line with he funds appropriated for a project. For a very large client of a blue chip firm, a project can be buried in another on-going project for that firm and described as “research.” Billing has been flexible for as long as the industry has existed.
- AI enabled firms can be fleeter of foot and more like a Cirque du Soleil act. My view: If an engagement requires speed and agility, find a firm that has specific strengths. Blue chip consulting firms, even when AI enabled, have specific, proprietary systems and methods. Sure, a blue chip consultant can jump to another firm, but that transplant has to learn the specific systems and methods at the different consulting firms. Most of the consulting firm’s recipes contain quite specific ingredients in appropriate proportions. Most of this stuff is not taught in MBA school. Feel, style, and selection of ingredients are unique to each firm. That’s why clients of blue chip firms lock in on one or two blue chip firms for the majority of their high end consulting work. The firm delivers the dish the client likes without surprises.
What the article suggests is that the world of blue chip consulting will be roiled yet again. I don’t agree. Blue chip consulting firms did not become blue chip by being “good enough.” Delivering a report anyone can do with a prompt says more about the client’s expectations and the firm doing the work than relevant information about a blue chip firm.
The blue chip consultants have been affected by the corrosive effect of online information and modern technology. Modern business produces winners and losers. That means that firms disappear, get acquired, or decide to merge. The same forces apply to Web search and to the US auto industry.
There are what I call azure chip consulting firms or mid tier outfits. LinkedIn runs ads when one of the better known mid tier firms says it wants to hire an expert in technology X or business sector Y. These firms take work that is too small to be of interest to the blue chip firms. In Manhattan one can hire a research firm to do a study. The firm does okay work, and its clients usually don’t know the difference between what a blue chip firm would have delivered and what the mid tier outfit delivered. Mid tier consultancies have always been cheaper.
There are outfits like Gerson Lehrman-type outfits who “rent” former blue chip consultants to companies working on a budget. These organizations have been around for years and have not killed the blue chip consulting firms. My hunch is that these rental agencies will be able to deliver more value because the individual experts they rent will avail themselves of AI to make a one hour Zoom meeting more useful.
The idea that AI will light the fire of lower cost, AI consulting firms is accurate. However, most of these will not survive. That’s because start ups, regardless of business sector, fail at a rate that would make moms, friends, and clueless family offices sick to their stomachs.
I think the article is interesting. I am not sure that the angle of attack is matched to how the management consulting business operates and has operated for more than a century. I think Booz, Allen fired up in 1917 or so with a project for Sears (may it rest in peace).
AI is a tool. Management consultants are knowledge value professionals who use tools. A tool provides something of use to a skilled user. By itself, the tool does not do much of anything. It’s the know how that produces a hierarchy with the best performers at the top and the wanna-bes at the bottom. AI is good enough right now for some things. I am not convinced it is good enough for context sensitive, fast changing, dynamic things.
Stephen E Arnold, June 2, 2026
Google Showers Cash on Consultants: The “Useless” Professionals Are Important Now
June 2, 2026
While Google is cutting costs by firing employees, it is also spending $750 million to fund a Cloud Next 2026 endeavor. This is meant to advance its partners’ development of agentic AI applications, making this the largest single partner investment in history. According to The Next Web’s story: “Google Puts $750 Million Behind The Consultants It Needs To Close The Cloud Gap.” the firing of the money canon signals the start of another AI race.
The AI death match will shift from selling cloud infrastructure to financing systems integrators and consultancies that deploy Google AI. Agentic AI will create a $1 trillion global market and Google wants to own a large portion of it by making its partners the main delivery channels.
Here are more details about the fund:
“The fund is not a venture capital vehicle. It is a mix of credits, co-investment capital, training subsidies, and go-to-market funding designed to get the world’s largest consulting firms building agents on Google’s platform rather than on Microsoft Azure or AWS. The economics explain the urgency: for every dollar a customer spends on Google Cloud, partners capture up to $7.05 in services revenue, meaning the consultancies are not just a distribution channel but a multiplier of Google’s own cloud consumption. Google now counts more than 2,900 services partners, with a 400% increase in new partner entries over the past year and a 250% increase in partner-influenced revenue. The fund is a bet that accelerating the partner ecosystem is the fastest route to closing the market share gap with AWS and Azure.”
Google’s individual partners have added their own money to the fund. Accenture is expanding its Gemini practice and has already built more than 450 agents on Google Cloud. Deloitte has more than one hundred agents on and said the company made the largest investment in Google. KPMG said they’ll allot $100 million to the project, while PwC has $400 earmarked for Google Cloud. NTT Data and Cognizant have 5000 engineers working on agents specifically for healthcare, financial services, and manufacturing.
Google is investing this money with their partners in order to beat Microsoft in the enterprise. Microsoft has a structural advantage with Office 365 and it also happens to be distributed to Fortune 500 companies that Google wants to make their own. Sure, AWS is also a rival to Google, but Microsoft is the outfit the Googlers want to supplant.
Google knows it can run the world. Will the world go along with this McKinsey-inspired big idea? Eric Schmidt, the former CEO of Google, tried to talk about AI in a recent graduation address. He probably said Googley things amidst the boos. Is that a harbinger of Google’s AI vision?
Whitney Grace, June 2, 2026
The AI-Adept Humanoid Gets the Job
June 2, 2026
The downside of AI is being shown on a daily basis and we know humans won’t be entirely placed by robots soon. There is a way that AI, however, might come for your job says Science Daily’s article: “AI Won’t Replace You But Someone Using AI Might.” The University of Vaasa in Finland conducted a study about AI and it shows that the algorithms are keeping people more engaged with their work.
The study came from the doctoral dissertation of Zhe Zhu, who explored how AI tools are affecting and influencing work place. The researcher focused the study on organizational decision making and the human side of AI adoption. Zhu found that the concerns about AI replacement inspired employees to learn new skills to use AI more effectively on their jobs.
Using AI is a careful balancing act:
“According to the research, trust plays a major role in determining whether AI helps or harms employees and organizations. Workers who trust AI too much may accept inaccurate information without questioning it, while employees who distrust the technology completely may overlook its potential advantages. Zhu argues that organizations must carefully manage this balance as AI becomes part of everyday workflows.”
Zhu discovered that AI adoption depending more on how organizations implement it. Zhu said:
“ ‘Organizations should follow a strategic roadmap to align the technology with their goals and build ecosystems with industry and academic partners. My research proposes an eight-step framework that guides organizations in moving from experimentation toward a more integrated and purposeful use of GenAI.’”
New jobs will appear while old jobs disappear. Employees that adapt to the new technology and embrace the new career paths will find that they continue to have work, while others who shun the AI revolution will be left behind in the dust.
Whitney Grace, June 2, 2026
The AI – Catholic Church Issue
June 1, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
The New York Times published a short summary of five encyclicals. It is good to know that the NYT knows how to research the history of Papal actions. The story is paywalled, so paying, not praying, will reveal the truth. But the five encyclicals did not get to what I think is the crux of the matter or X marks the real spot.
Galileo Galilei makes it clear that he was very confused about the planets revolving around the sun and most of his other heretical thinking. House arrest made more sense to him than being burned at the stake. Thanks, Venice.ai. Good enough after three tries.
Not surprisingly, the Magnifica humanitas statement emphasizes guardrails, global regulation, and protection of humanoids. Anthropic’s “statement” was, and I summarize:
- Guardrails. Check
- Regulation. Check
- Protect humanoids. Check.
I interpreted the encyclical differently, probably because I worked on my graduate degree at Duquesne University (a Jesuit institution which like the idea of guardrails, regulation, and protection for humanoids. Believe it or not, I taught a couple of classes a requirement of my waived tuition, but I did get some money each month so I could enjoy a truly lavish lifestyle in Pittsburgh, Pennsylvania.)
The write ups about the encyclical did not talk about three interesting church actions. I will not talk about the Inquisition, but, please, keep that in mind if you doubt that the Catholic Church can take steps to clarify the thinking of certain of the church faithful.
I want to offer three examples of what happened when the tech bros did not line up with the Catholic Church.
First, Copernicus came up with the idea that lecturing and writing about his idea that the planets revolved around the sun deserved broad dissemination. The Church just grumbled but in 1616, that pot boiler De revolutionibus orbium coelestium was added to the Index of Forbidden Books.
Second, Galileo Galilei was into the Copernican concept. In 1633, he was tried by the Inquisition an found guilty. Galileo did the pragrmatic thing. He said, “I am sorry, very, very sorry.” The Church placed him under house arrest until he died.
The third example is one that calculus students don’t know much about. The Church determined that infinitesimals and by extension infinity bumped into Aristotelian philosophy. Those “teaching” about infinity were able to find jobs as farmers or buskers in Padua. Math bumped into this problem for decades until other issues pushed infinitesimals into an infinintely small segment of Catholic dogma.
My view of the encyclical about AI is, therefore, based on these historical actions. Thus, several observations can be offered:
- The Catholic Church can take direct and indirect action to suppress or cause information change
- Some of the methods tolerated by the Church involve indirect (house arrest) and direct (Iron maidens, heated fireplace pokers, etc.) to help individuals free their minds from certain thoughts
- The encyclical can spawn other statements that will be disseminated not by the Zuck-type or Telegram-type services. The message will be delivered to about 1.5 billion people. These indivdiuals with log on to the Zuck-type or Telegram-type services and comment about the Church message.
Net net: The Pope’s encyclical is a significant document and highly visible action. Additional communications and manifestations of the Pope’s guidance can be implemented with surprising ease and speed.
Stephen E Arnold, June 1, 2026
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