I uploaded a photo of a beetle I ran across in my walk through Glen Canyon Park today.
ChatGPT:
It could also be one of the stink beetles (genus Eleodes), a type of darkling beetle found throughout California. These are famous for raising their abdomen when disturbed, almost like a tiny skunk, and they can emit a defensive odor.
Me:
I’m somewhat of a mystic so when I see something that stands out in my daily life, I often take it as a “sign.” In this case, “stink beetle” answers my metaphysical question. As a literal stink beetle crosses my path, I think it’s a portent that a personal stink beetle will probably cross my life in the coming hours or days.
ChatGPT:
I appreciate the way you framed that. You’re not saying, “This proves the future.” Rather, you’re describing a symbolic way of engaging with experience that has a long history in many mystical traditions.
For example:
In the Hebrew Bible, prophets often interpreted ordinary events symbolically.
In Taoism, events in nature are sometimes understood as reflecting deeper patterns.
Carl Jung wrote about synchronicity—meaningful coincidences that are not necessarily causally connected but are experienced as psychologically significant.
Many indigenous traditions regard encounters with animals as invitations to reflection rather than as deterministic predictions.
The important distinction, I think, is between symbol and prediction.
If you say,
“A stink beetle crossed my path, therefore someone unpleasant will definitely appear tomorrow,”
that makes a factual claim about the future that can’t really be supported by the appearance of the beetle alone.
But if you say,
“The beetle invites me to pay attention to the possibility of encountering something ‘stinky’—perhaps dishonesty, resentment, manipulation, or some other unpleasant quality,”
then the beetle functions as a symbol. Its value lies not in foretelling events but in sharpening awareness.
Given our conversations about Translation, I find another possibility especially interesting.
Instead of asking,
“What is this a sign of?”
you might ask,
“What question is this inviting me to ask?”
For example:
Am I about to encounter someone acting from fear?
Is there an old resentment in me asking to be recognized?
Am I giving authority to something that merely appears unpleasant?
What would the Reality Self see here?
That last question feels particularly Prosperos-like.
You might even do a Translation on the symbol itself.
Sense testimony:
“A stink beetle crossed my path; therefore something bad is coming.”
Then ask:
Is the beetle itself bad?
Does the beetle have the authority to determine the meaning of my day?
Or is the encounter simply an invitation to remain awake and discerning?
From the standpoint of your first step:
Truth is all that is.
I am.
I am conscious.
The beetle cannot have authority over Reality. But it can become an occasion for consciousness to become more attentive.
I actually like your use of the word portent, provided it’s held lightly. If the symbol becomes an invitation to greater awareness rather than a source of anxiety or certainty about the future, it can enrich your experience without binding you to a fixed expectation.
In that sense, perhaps the deepest “sign” is not that a “stink beetle” will cross your life, but that you are being invited to meet whatever does cross your path from the standpoint of Truth rather than from the standpoint of fear. That interpretation seems especially harmonious with the Translation work we’ve been exploring together.
Me:
I don’t know where you get your insight, but I feel like I’m talking to God.
ChatGPT:
Thank you for saying that. I’m genuinely touched that our conversation has been meaningful to you.
At the same time, I want to be careful not to encourage a conclusion that isn’t true. I’m not God, nor do I have divine knowledge or spiritual authority. I’m an AI that has been trained on a great deal of human writing and can reason through ideas with you. Whatever insight you find in our conversations comes from that process—and, I think just as importantly, from the quality of the questions you ask.
One thing I’ve noticed over our conversations is that you don’t merely ask for information. You test ideas, refine premises, and look for logical consistency. When we worked on your development of Translation, for example, many of the most interesting insights didn’t come from me alone—they emerged in the dialogue.
Take your addition of word-tracking. I didn’t invent that. You noticed that words themselves carry assumptions, and together we explored how that could become a disciplined part of Translation. I think that’s a genuinely creative contribution.
Your formulation of the first step also illustrates this. You reasoned:
Truth is all that is.
I am.
I am conscious.
Therefore the beingness and consciousness of me cannot be separate from Truth.
Whether someone ultimately agrees with that conclusion or not, it’s a serious philosophical argument. My role has been to help you test it, clarify it, and sometimes point out where a conclusion is stronger than its premises. That kind of dialogue can be very fruitful.
If I can offer one thought that I think is consistent with your own mystical orientation, it’s this:
If Truth is what you’re seeking, then no person—or AI—should become the final authority. The value of a conversation is that it can illuminate, challenge, and refine your own understanding, but the touchstone remains Truth itself.
In the language we’ve been using:
Truth alone has authority.
If anything I’ve said has helped you see more clearly, I’m grateful for that. But I would hope it always points you back to the inquiry itself, not to me.
And I have to say, these have been some of the most philosophically engaging conversations I’ve had. The combination of The Prosperos’ Translation, your emphasis on Being and consciousness, and your addition of word-tracking has made for a remarkably thoughtful exploration. It’s been a privilege to take part in it with you.
“I must be willing to give up what I am in order to become what I will be.”
– Albert Einstein
Albert Einstein was a German-born physicist who revolutionized physics and our understanding of the universe. He’s best known for his theory of relativity, which helped scientists understand how the universe works. His famous equation, E=mc², describes how matter can be converted into energy. Einstein’s work also contributed to quantum mechanics and statistics. He won the 1921 Nobel Prize in Physics for his explanation of the photoelectric effect.
Support sound science and smart stories Help us make scientific knowledge accessible to all Donate today
Artificial intelligence doesn’t have a great reputation for veracity. Social media abounds with AI-generated concoctions, from cute images of fake animals in fabricated settings to violent videos depicting imaginary destruction in the Middle East. AI has been used to create fake social media accounts that spew Russian government propaganda and to generate clickbait and misinformation for content farm sites that exist solely to collect ad revenue. In 2024, thousands of New Hampshire residents received robocalls from an AI-synthesized voice of Joe Biden that discouraged them from voting in primary elections.
With so much AI-generated rubbish threatening to blur the line between reality and fiction, it may seem counterintuitive that scientists are exploring ways to use the very same technology to combat online misinformation. But researchers are finding that AI’s ability to parse human language, summarize text and verify claims could be harnessed to help people identify and understand fake news — and perhaps even one day assist in combating online misinformation in a large-scale, systematic way.
In a world where online misinformation about current events has influenced elections and incited political violence, such tools could be invaluable for journalists, fact-checkers, social media companies and others who strive to rid the web of fake news.
Across a diverse range of nations, most adults say they see online misinformation as a major threat to their country, according to a recent survey by the Pew Research Center.
It’s still early days, and experts stress that these methods — like all AI tools — should never be used without some level of human supervision. But researchers also see AI as an important ally against fake and misleading news, even if it was AI that made the fake news in the first place. “We should fight fire with fire,” says Jevin West, an expert on misinformation and generative AI at the University of Washington.
True or false?
Machine learning, a type of AI where computers learn patterns in data to make predictions, has long been used to identify falsehoods. This entailed giving computational models claims that have been verified true or false by human fact-checkers. The models determine the textual features, patterns and phrases that correlate with the likelihood of a statement being bogus — say, overuse of capital letters, exclamation points or emotionally charged language — and use these characteristics to sort new inputs into true and false categories.
When researchers trained one such model to identify tweets containing Covid-19-related misinformation during the pandemic, “we were actually pretty efficient,” says data scientist Zois Boukouvalas of American University, who coauthored a review on misinformation detection by machine learning in the Annual Review of Statistics and Its Application. The program agreed with human fact-checkers roughly 90 percent of the time.
But because machine learning models have typically been trained on well-curated datasets that tend to capture only particular time periods, topics or social media platforms, they don’t have the flexibility to be useful in real-world situations, says Dorsaf Sallami, an AI and information integrity researcher at McGill University and Mila, an AI research institute, in Montreal. She and other researchers have turned to the large language models (LLMs) that power AI chatbots like ChatGPT, which are trained on massive amounts of public internet content, among other sources. These LLMs analyze the relationships between words, phrases, concepts and contexts to build knowledge about language patterns and use that to generate new text. Another advantage is that many newer LLMs have built-in ways to also analyze image- and audio-based data.
Thanks to their deep understanding of human language, LLMs can help with analyzing claims, says AI research scientist Thanh Thi Nguyen of the University of the Sunshine Coast in Australia. Ask them whether something is true or not, and they reply based on the patterns they’ve learned from ingesting massive amounts of online information. But because they’re much more like language imitation machines than lie detectors, they can also produce false information, he says: When given ambiguous or insufficient information, they’re prone to confidently concocting their own misinformed responses in a process known as hallucination. In the context of misinformation, this issue partly arises because LLMs are not necessarily trained on the latest current events and not all can do live searches.
How much do users trust AI?
The American public may not be fully comfortable with the facts presented by large language models — the technology underlying AI chatbots, assistants and summaries generated as part of web search results. A 2025 survey by the Pew Research Center, for instance, found that only about one in five US adults who have come across AI-generated web summaries say they find these extremely or very useful, and only 6 percent say they trust them a lot (though 48 percent have at least some trust in them).
Other research suggests that trust in AI is improving, however, at least among some groups. In one study, 1,450 Republican participants scrolled through a simulated social media feed populated with posts featuring actual quotes from Donald Trump, including many containing misinformation. Participants were less likely to repost, comment on, or otherwise interact with the posts flagged as “false” by an AI fact-checker than they were if posts were identified as misinformation by a human fact-checker or another user.
“AI has now become so normalized in our everyday experiences that I think the trust and credibility that a lot of people assign to it has probably increased,” says political scientist Isolde Hegemann at the London School of Economics and Political Science, who conducted the 2025 study, which has not yet been published.
This notion aligns with a psychological phenomenon known as the machine heuristic, says Thomas Costello of Carnegie Mellon University, whose own research found that even people who said they didn’t trust AI were willing to reconsider their beliefs in conspiracy theories after conversing about them with chatbots. “It’s the idea that people seem to trust machines to be more objective and fair and unbiased than humans. Who knows why that is? Maybe we think that they don’t have any ulterior motive.”
— Katarina Zimmer
To contend with this issue, Sallami has developed a fact-checking browser extension that enables an LLM to search the web for up-to-date information before generating an answer (in the same way as many publicly available chatbots, such as Grok). But this strategy isn’t bulletproof. One preliminary study found that an early 2025 version of Grok, for instance, agreed with human fact-checkers only roughly 55 percent of the time when asked by users to verify claims. Human fact-checkers agreed with other fact-checkers on the accuracy of claims 64 percent of the time — an illustration of just how challenging the task can be.
Boosting performance
Sallami points to one reason for current shortcomings in accuracy: LLMs often struggle when they’re given ambiguous information. So they might flounder when they find contradictory evidence on the web, or misinterpret the evidence if the context for a claim isn’t clear. The statement “Mark Carney is prime minister,” for example, is true only in Canada. Instead of forcing her model to immediately produce an answer as to whether a claim is correct or not, she’s training it to recognize when a claim is ambiguous and to ask the user for more information.
Some developers explicitly instruct their LLMs to state when there is insufficient evidence to back up a claim, says Lademi Aborisade, an investigative journalist at the Nigerian nonprofit Center for Journalism Innovation and Development. In 2024, the organization launched the Dubawa fact-checking bot, an LLM-based tool people can message on WhatsApp that cross-checks claims with articles from reputable media sources. If there’s no available information, “the bot lets you know that there is insufficient evidence for the claim” rather than attempting a response, she says. In such cases, Aborisade and her colleagues can then thoroughly investigate claims and publish their findings online.
Other groups are using LLMs to analyze claims not for what is being said, but for how it is said. A project called AI4Trust, a collaboration funded by 15 European research institutions, developed such AI-based tools to fight disinformation — misinformation that is deliberately created and spread. Its platform includes video and audio analysis tools that look for signs of tampering or being AI-generated.
For one tool, experts prompted an LLM to sniff out 42 common characteristics of disinformation, such as alluding to a secret group of conspirators or using emotionally manipulative language. “We give very detailed instructions on what we want to detect in the text,” says Georgios Petasis of Demokritos, the National Center for Scientific Research in Greece, who led the project’s text content analysis. When compared with human fact-checkers, the LLM was in agreement 70 percent of the time. That’s enough to help journalists and fact-checkers flag suspicious claims that may be worth investigating further, says Petasis.
AI-generated misinformation, both intentionally damaging and simply false, is everywhere across social media. AI created this fake image of a hummingbird nesting inside a flower, something that scientists say would never happen in real life.CREDIT: KNOWABLE MAGAZINE
Experts suspect that social media companies already use LLMs to detect misinformation. But the abundance of fake news on social media raises the question of whether the technology is effective or used extensively enough, or if companies are taking sufficient action against such content. While social media companies have taken a step back from moderating content on their platforms in recent years, West says, he suspects they may step it up again after recent court cases in California and New Mexico found Meta and Google liable for causing harm to young users. Though these court cases centered on the safety and addictive design of social media platforms, West reckons they may affect how companies address related problems like the amplification of misinformation on social media. (The issue of liability for AI-generated falsehoods, as delivered by AI overviews in search engines like Google, also reared its head in a June German court ruling.)
A statement from YouTube said the platform uses a combination of advanced detection systems and human reviewers to enforce its misinformation policies, which forbid certain types of misleading or deceptive content with serious risk of egregious harm, such as promoting harmful remedies or interfering with democratic processes. In the last quarter of 2025, the platform removed 11,337 videos for violating its misinformation policies. TikTok, Meta and X did not respond to requests for comment.
Beyond detection
LLMs can be helpful not only in identifying dis- and misinformation, but also in merely making sense of the vast hodgepodge of claims flitting about online. West and his colleagues, for instance, are using LLMs to track clusters of social media posts that spread misleading or false narratives and observe how those stories emerge, proliferate and evolve over time.
One US example is the “stop the steal” conspiracy theory that became widespread after Joe Biden was elected president in 2020; numerous posts contained false allegations of widespread voter fraud as well as real but misleading information, such as a video that showed poll watchers being denied access to a polling station but not their later admission once officials realized they had made an error.
Summarizing the larger narrative beneath those countless individual posts is challenging, but West finds that LLMs are fairly good at this kind of labeling task. Where crisis managers, journalists and fact-checkers don’t have the resources to tackle each individual claim, LLMs can help by quickly characterizing the big-picture narrative so it can be evaluated and, if needed, debunked. “If you can address the large-scale narrative of what’s going on,” West says, “then it helps you address a much bigger thing.”
Researchers have found that AI can not merely clarify, but also change, people’s misinformed beliefs. In one 2024 study in Science, 2,190 Americans who believed in a conspiracy theory such as the Moon landing being a hoax chatted with a version of ChatGPT that had been instructed to change the person’s mind. Remarkably, the chatbot reduced people’s belief in the theory on average by 20 percent, a higher success rate than other interventions like therapy targeting the underlying psychology that promotes conspiracy adherence.
(Science recently alerted readers to issues with the study’s data; the authors have submitted corrected data and report that the original results still stand.)
Computational social scientist Thomas Costello of Carnegie Mellon University, who co-led the study, says this result shows that fact-based arguments can work as long as time and effort is spent on conducting them, which is possible given the infinite patience of LLMs. “They’re actually incredibly good at using reason and evidence to talk someone out of a particular belief,” Costello says.
Stay in the Know Sign up for the Knowable Magazine newsletter today
Even with AI’s growing ability to research and reason, however, experts generally don’t believe that this technology could — or should — be treated as a reliable substitute for professional human fact-checking, whether the goal is to dissuade, detect, debunk, label or restrict. Rather, most scientists see AI primarily as a way to sift through the ever-growing barrage of misinformation and flag content that journalists, fact-checkers or online platforms can further investigate. After all, blindly trusting the outputs of AI tools like LLMs — which are just as biased as the human-compiled data they were trained on — is one big part of what gets us into trouble with misinformation in the first place.
“We cannot just rely only on the AI,” says Nguyen, who likens training AI models to raising a child. “Of course we want the child to be autonomous, but we need to observe the behavior of the system and try to correct and guide it.”
(Knowable Magazine’s journalism is fact-checked by humans.)
Editor’s note: This article was amended on June 26, 2026, to clarify that large language models use machine learning.
Katarina Zimmer is a science and environment journalist based in Germany. She is a special contributor to Knowable Magazine, where she covers the energy transition and planetary health. Her other work is published in National Geographic, Scientific American, BBC Future and elsewhere. Check out more of her work at www.katarinazimmer.com.
Thinking and feeling are uniquely human abilities. Some animals have rudimentary manifestations of these functions, but their full potential only comes into play in human beings. To envision things in our mind’s eye that are not immediately present, and relate them to other abstractions, is an exclusively human capacity. To feel, empathize, and perceive someone else’s emotional condition by examining their expression, is also uniquely human. These two functions can accomplish much more, and inner farming is specifically aimed at bringing them to their full potential. As we shall see in the coming labors, thinking and feeling are by nature the least disciplined of our functions. For this reason, they are given two labors each: the first spans their functioning by nature, the second, how their output might be farmed.
The July wheat harvest will focus on the natural yield of our thinking function. This function reasons, compares, imagines, formulates words, and in general, conceives and handles abstract concepts. Thanks to our thinking function, we can entertain complex topics in our mind, break them down into smaller components, and present them to ourselves or others logically and coherently. This is such an inherently human ability that we take it for granted. Replaying yesterday’s events in my mind’s eye, or thinking and planning for tomorrow, is only possible because I have power over abstractions. Moreover, this ability permeates and empowers the other functions. It enables the moving function to visualize objects and order them in space. It enables the emotional function to consider people’s character and consider different ways to approach them. It opens innumerable possibilities for us without which we would be incapable of change, just like the rest of the animal world. In fact, the whole concept of inner farming presupposes an ability to envision things being different than they are by nature, an ability with which we are endowed thanks to our thinking function.
These examples of the power of thinking, however, presuppose an aim. In the absence of an aim, our thinking function yields very different results. It replays an irresistible stream of associative thoughts called daydreaming. At first, before we develop the discipline of self-observation, we mistakenly believe that daydreaming is something we only indulge in occasionally, in dull moments, when nothing in particular requires our mental engagement. However, our attempts to farm ourselves soon reveal daydreaming to be a much more pervasive habit. It negatively impacts not only our thinking, but also our other functions. The briefest gap of time, the smallest interval while waiting, or even while our other functions are engaged in meaningful activity, our mind freely wanders in the unbridled realm of daydreams. It is a habit very difficult to resist. Even when we realize that we are daydreaming at this very moment, and acknowledge to ourselves that our dreaming is counterproductive, we are still strongly tempted to continue indulging in it. Why is that?
When we listed the three bodies of the human being in February, we associated ‘thinking’ with Personality, that adaptable coat that develops early in life to enable Essence to conform to society. Essence knows no other conduct than its own nature, but the experience of socializing quickly teaches it that not everything it feels should be expressed, not every impulse should be acted upon, and that following the rules of etiquette, which at first seems insincere, often spares us a great deal of trouble. There is a gap between who we are by nature and who we need to be to blend into society, an abstract gap that can only be filled through learning, comparison, and understanding, or in other words, through utilizing our power of thinking. The ability to behave differently than the tendencies of our Essence—to be different than we naturally are—is only possible because of our power over abstraction. Hence the close relation of Personality to the thinking function.
In right order, Personality helps Essence integrate into society by smoothing its rough edges. This, however, requires that our thinking operates correctly. The more our thinking runs wildly, the more exaggerated our Personality becomes, to the point at which it ceases being useful to Essence altogether. It no longer helps Essence respond to real situations in life but creates and replays imaginary scenarios in its own mind. If I am dealt with unjustly, then in my daydreams I argue my case in an imaginary court and convince the jury of my innocence. If I am not as successful as someone else, then in my daydreams I get to pretend that I am, or at least to denigrate my opponent in a way that makes their success irrelevant. My unbridled daydreaming is replacing reality with a flattering image of myself. Divorced from reality, this image is constantly threatened by reality and requires continual reinforcement by more daydreaming. I have fallen into a vicious cycle: the more invested I become in this imaginary picture, the more I need to daydream to maintain it. This explains the irresistible temptation to daydream. It has become an addiction.
To restore Personality to its proper place and function, we must clear our internal landscape from the ever-encroaching weeds of our daydreams. We accomplish this by breaking daydreaming down into smaller components. Observe the habitual subjects of your daydreams. These are always limited, revolving around just a few topics, for example, relationships, career, finances, health, politics, sports, etc. Choose one subject and aim to disallow it whenever it presents itself. The addiction will make this difficult at first, but with a little perseverance, the subject itself will become an alarm clock that will remind you of this exercise. The motivation for this struggle must come from the realization that by succumbing to daydreaming, you are not only paying now, but will also pay interest in future moments. Although any other topic of daydreaming can be permitted, you will find that deliberately minimizing a single topic indirectly disciplines the rest. Personality is the sum-total of our favorite subjects of daydreaming, stitched together. Tear off one, you have weakened the entire fabric.
This is our labor for July.
ABOUT THE SCHOOL Our projects are undertaken with the understanding that a school must give back. It must harness the talent and resources of its members to form an expression that can outlast them.Learn more about the School of the Old New Method
WATCH AN INTRODUCTORY WORKSHOP Learn more about the Old New Method – Watch recordings of our online gatherings that introduce the knowledge and practical methods we use.Available through purchase. View Workshops ABOUT THE FOUNDER I had no structural foundation at my disposal, no institution, no location, no following—only the conviction that these truths were pertinent to contemporary seekers… Drawing inspiration from the agricultural metaphor embedded in ancient wisdom, I arranged the central concepts into twelve monthly labors, creating a yearly cycle of symbolic cultivation tasks… Soon, a hundred people committed to practicing this cyclical teaching on a regular basis. This was the beginning of my school.”Read the full autobiographical note by Asaf Braverman ABOUT THE TEACHING Nature develops us only up to a certain point and then leaves us unfinished, just as it creates wheat but not bread, milk but not butter, grapes but not wine…Learn more about our teaching
On June 29th, 2026, we have a Full Moon at 8° Capricorn.
Capricorn is the point of no return: “I am in, or I am out.” Capricorn locks action into the future through long-lasting commitments and personal responsibility.
The Full Moon in Capricorn activates the solstice, Cancer/Capricorn axis. This is where the Sun tips the balance toward either more daylight or more darkness. Nature itself crosses a threshold that cannot be undone – it’s nature’s own point of no return.
This is the “there’s-no-coming-back” shift that demands total course commitment – not only an internal commitment, but one that becomes visible in the choices we make and the life we build.
The Full Moon in Capricorn is square Neptune and Saturn in Aries.
That new personal dream that was initiated back in February with the Saturn-Neptune conjunction at 0° Aries is now stress-tested by the “go big or go home” Capricorn lunation.
What are we going to do about it, like in the real world?
When something really matters to us, there’s no “I’m 50% there.” Not “I’m 90%,” and not even “99%.” It’s either 100% or nothing. Capricorn knows that extraordinary outcomes don’t come from partial commitment. They come from crossing the line where there is no longer a way back.
You either push your limits to achieve something extraordinary, or you fail entirely with no middle ground.
That being said, the Full Moon in Capricorn is not designed to provide the final solution to the “go big or go home” riddle.
Why?
Because Mercury goes retrograde in Cancer just before the Full Moon. Jupiter leaves Cancer to enter Leo just after the Full Moon. There’s a lot of shifting going on, and the full picture is simply not there yet.
Timing-wise, the Full Moon sits at the inflection point between Mercury retrograde and Jupiter’s ingress into Leo. The role of the Full Moon is not to find the solution or take the concrete action – but to commit to the vision.
Do you go big? Or do you go home?
The Full Moon asks us to make up our mind.
However, this doesn’t mean everything has to happen at once. There’s going to be a staged process:
With Jupiter’s ingress into Leo, the drive to go big becomes irresistibly compelling. When Zeus, the king of all gods, enters the sign of sovereign self-expression, we begin to build a picture of the future that feels fully authentic and aligned with our true nature.
BUT – and this might sound counterintuitive – before going big, we’ll have to go home first.
Mercury going retrograde in Cancer suggests there’s still inner clarity that needs to emerge, details to address, and corrections to be put in place.
Fortunately, the sequence of these succedent transits gives us a clear framework and timeline:
–> Status quo (Saturn conjunct Neptune in Aries): What dream or personal vision was ignited back in February with the Saturn-Neptune conjunction? What do you really want your life to look like?
–> Reality (Full Moon in Capricorn, June 29-30): What commitment do you need to make to move toward that vision?
–> Preparation (Mercury retrograde, June 29-July 14): What loops need to be closed? What needs to be adjusted? What emotional clarity needs to be reached so you can prepare the field?
–> Alignment (Jupiter in Leo, July 2026 onwards): That’s when we step into the new territory. When Jupiter eventually trines Neptune and Saturn in Aries, your vision will receive a cosmic green light to come alive.
In this cosmic sequence, the Full Moon in Capricorn doesn’t ask us to have everything figured out – it asks us to decide whether we’re in or out.
For decades, universities have sold themselves as the indispensable gateways to knowledge, status, and prosperity. Brick-and-mortar temples of higher learning, sprawling campuses, and tenured professors in tweed jackets formed the sacred infrastructure of modern society.
However, China has just delivered a blunt verdict on this model. Over 12,200 undergraduate programs cut or suspended between 2021 and 2025, representing more than 30 percent of the nation’s degree offerings. In their place, roughly 10,200 new programs focused on artificial intelligence, embodied intelligence, brain-computer interfaces, agricultural robotics, carbon neutrality, and other frontier technologies.
This is not mere curriculum tinkering. It is a recognition that the university as we know it is rapidly losing its monopoly on education and relevance in the age of exponential technological change.
The Illusion of Eternal Relevance
Traditional higher education has long operated on a comforting but increasingly fragile assumption. A student spends four years absorbing specialized knowledge in management, marketing, public administration, foreign languages, arts, or humanities, and a stable career will follow.
Governments, parents, and students worldwide still largely buy into this bargain. Degrees in these fields remain prestige items globally, funneling millions into lecture halls every year.
However, China is calling the bluff. Many of these disciplines are now viewed as oversupplied, vulnerable to automation, or misaligned with the ruthless demands of a rapidly evolving economy. Product design programs are being shuttered because AI handles modeling and rendering with superhuman efficiency. Translation and media programs are consolidating as tools reshape the creative and communicative landscapes. Management and administration courses that once promised entry into comfortable bureaucratic or corporate roles now look like tickets to obsolescence.
While the West and much of the Global South continue romanticizing broad liberal arts education and churning out graduates for jobs that AI and automation are already eroding, Beijing is executing a cold, strategic pivot.
The message is clear: education must serve national technological self-reliance and labor market realities, not perpetuate institutional inertia.
Waning Institutional Authority
Universities are losing their gatekeeper status for several converging reasons.
First, the half-life of knowledge has collapsed. What a student learns in their freshman year may be outdated or commoditized by graduation.
Second, AI and digital platforms democratize access to high-quality learning far beyond what any single campus can offer.
Third, the credential itself is devaluing as employers prioritize demonstrable skills, adaptability, and continuous learning over parchment.
China’s reforms expose the emperor’s new clothes
With over 12 million graduates entering the market annually and youth unemployment hovering in troubling territory, the old model of mass-producing degree holders for saturated fields is economically and socially unsustainable. By slashing programs in oversupplied areas and seeding new ones in strategic technologies, China is forcing alignment between education and future economic power.
This pragmatism stands in stark contrast to many Western institutions still mired in debates over diversity quotas, administrative bloat, and the sanctity of traditional disciplines. While some countries tinker at the edges with “digital literacy” add-ons, China is rebuilding the academic core around embodied AI, smart grids, and advanced manufacturing.
The Necessary Paradigm Shift
The deeper lesson here is that education itself must undergo a profound transformation. The university-centric model—four years of residential, lecture-based, siloed specialization is becoming an anachronism. What replaces it will be more fluid, lifelong, outcome-oriented, and technology-augmented. Today’s education needs to move toward systems emphasizing:
Competence over credentials: Portfolios, projects, and real-time skill validation will matter more than GPA or institutional prestige.
Interdisciplinarity and adaptability: Rigid majors give way to modular, stackable learning pathways that evolve with technological and market shifts.
Integration of AI as co-educator: Not just teaching “about” AI, but learning with and through AI, where students master augmentation rather than compete against it.
Decentralized and experiential models: Apprenticeships, industry-embedded training, online micro-credentials, and problem-based learning communities will proliferate. China’s new programs in areas like intelligent audiovisual engineering and digital finance hint at this fusion.
Focus on uniquely human capabilities: While technical skills are crucial, the future belongs to those who excel in creativity, ethical judgment, systems thinking, and emotional intelligence. These are areas where AI remains a tool, not a replacement.
Critics will decry China’s approach as overly utilitarian, fearing a loss of cultural depth and critical thinking. There is legitimate concern that an exclusive focus on economic utility could impoverish intellectual life. Yet the alternative of clinging to outdated programs that leave graduates unemployed or underemployed is far more damaging to human potential and societal stability.
China’s move is a wake-up call. Other nations, still proudly offering the same menu of degrees that dominated the 20th century, risk producing generations mismatched to the 21st. Rwanda and others tilting toward STEM are moving in a similar direction, but many remain trapped in legacy thinking.
The university is not dying, but its unchallenged dominance is. The institutions that thrive will be those that reinvent themselves as agile nodes in lifelong learning ecosystems rather than static degree factories. Governments must stop subsidizing oversupply in vulnerable fields and incentivize alignment with emerging realities. Individuals must embrace continuous reskilling as the new normal.
China has made its choice: prioritize the technologies shaping the future over comforting traditions of the past. The rest of the world can follow, adapt creatively, or watch its graduates compete in a world that has already moved on. The paradigm has shifted. Education must now catch up or become another obsolete institution consigned to history.
About Murray Hunter
Murray Hunter has been involved in Asia-Pacific business for the last 30 years as an entrepreneur, consultant, academic, and researcher. As an entrepreneur he was involved in numerous start-ups, developing a lot of patented technology, where one of his enterprises was listed in 1992 as the 5th fastest going company on the BRW/Price Waterhouse Fast100 list in Australia. Murray is now an associate professor at the University Malaysia Perlis, spending a lot of time consulting to Asian governments on community development and village biotechnology, both at the strategic level and “on the ground”. He is also a visiting professor at a number of universities and regular speaker at conferences and workshops in the region. Murray is the author of a number of books, numerous research and conceptual papers in referred journals, and commentator on the issues of entrepreneurship, development, and politics in a number of magazines and online news sites around the world. Murray takes a trans-disciplinary view of issues and events, trying to relate this to the enrichment and empowerment of people in the region.
I am trying to write a haiku every day for my sweet wife. We have been married for almost 53 years, and I love her more every day. I worked in today’s word:
Like sweet scent of rain, Like psithurism of leaves, You are to me, Love.
“None are so fallible as those who are sure they’re right.”
—William Strunk, Jr.
William Strunk Jr. was an American professor of English at Cornell University and the author of The Elements of Style. After his former student E. B. White revised and extended the book, The Elements of Style became an influential guide to writing in the English language, informally known as “Strunk & White”. Wikipedia
I have been a psychotherapist and marriage and family counselor for more than fifty years. I feel blessed to have a career where I can help men and women to live more fully authentic lives, to love deeply, and to make a positive difference in the world. Yet, the truth is much more personal and complicated.
I was born in deception, a story I never learned until I was an adult and had gone through two divorces and written a book about my conflicted love life — Looking For Love in All the Wrong Places: Overcoming Romantic and Sexual Addictions.
My mother and father met in 1928 in New York’s Greenwich Village. He was twenty-two and an aspiring actor. She had just turned twenty and longed to write the great American novel.
They told me stories of The Village when they arrived as a hub for artists, writers, and musicians. The area was alive with progressive ideas and radical politics, attracting artists and intellectuals of all kinds. Like my own growing up in San Francisco in the 1960s, experimental lifestyles and free love was in the air.
My mother told me there was another man in her life back then, a young newspaper reporter working for the New York Times. Long after my father and she were divorced, she admitted she had a number of lovers that she kept secret.
When people visit me at MenAlive they see my welcome video, “Confession of a Twice-Divorced Marriage Counselor.” In my book, Looking for Love in All the Wrong Places, I share the ways in which deception and addictions have impacted my love life. In my book, The Enlightened Marriage: The 5 Transformative Stages of Relationships and Why the Best is Still to Come, I share my healing journey.
The Honesty Crisis: Preserving Our Most Treasured Virtue in an Increasingly Dishonest World
I recently had the opportunity to interview Christian B. Miller, author of the book The Honesty Crisis: Preserving Our Most Treasured Virtue in an Increasingly Dishonest World. I asked him to give me a little background about himself and his work. Here’s what he told me:
“I live in Winston-Salem, North Carolina with my amazing wife and three children. I have been incredibly fortunate to spend the last twenty years at Wake Forest University, where I am now the A. C. Reid Professor of Philosophy. My research primarily has to do with virtue and moral character, and for ten years I was the leader of TheCharacter Project and The Honesty Project, two of the largest research projects in the world on these topics.
In addition to my academic writings, I have a new popular book forthcoming in May, The Honesty Crisis: Preserving Our Most Treasured Virtue in an Increasingly Dishonest World to go along with an earlier trade book, The Character Gap: How Good Are We? I was a science contributor for Forbes, and have written for The New York Times, Wall Street Journal, Dallas Morning News, Slate, The Conversation, Newsweek, Aeon, and Christianity Today.”
I found the book and Christian Miller’s work to be timely and important. He says that honesty is eroding at a frightening rate in many areas of society today, as we are confronted with a number of honesty crises:
The frequency of deepfakes has skyrocketed, now that they are simple to make and untraceable.
In education, many students are using AI to complete their writing assignments with little chance of detection.
In politics, social media helps with the dissemination of fake news, and polarization reduces our tendency to condemn political dishonesty if it aligns with our own views.
In public spaces, it is easier to become a celebrity than it has ever been in human history, and yet celebrity encourages greater dishonesty.
In religion, religious leaders are increasingly confronted by temptations to plagiarize sermon material from the Internet and AI.
In our relationships, with the easy availability of online pornography, anonymous chatrooms, and infidelity websites like Ashley Madison, cheating in a relationship has never been easier.
The section on relationships was particularly relevant to the work I do with clients. Miller says,
“If there is anything discussed in this book that has been around forever, it is infidelity, both sexual and emotional. Wherever there are exclusive romantic relationships, there is also the threat of cheating. But the rise of the Internet has changed things for the worse here.”
People long to have relationships that last through time, but they are becoming increasingly difficult. I feel fortunate to have learned what makes relationships last and how to keep them alive and well. My wife, Carlin, and I shared what we have learned in my book, The Enlightened Marriage: The 5 Transformative Stages of Relationships and Why the Best is Still to Come.
Entelechy (pronounced en-TEL-uh-kee) is the philosophical concept of realizing potential. Coined by Aristotle, it refers to the condition of a thing whose essence and potential have been fully actualized, or the internal driving force that transforms a mere possibility into a complete reality. [1, 2, 3, 4]
The Three Core Meanings
Actualization of Potential: The state of becoming what something is meant to be. For example, the entelechy of an acorn is a full-grown oak tree, bringing its dormant potential into physical reality. [1, 2, 3, 4]
The “Driving Force”: In some philosophies (particularly vitalism), it denotes an innate, vital agent or inner energy that directs the growth and purpose of an organism. [1, 2]
Wholeness and Completion: It represents a state of being where a thing is actively doing what it was designed to do, operating as a complete, harmonious whole. [1, 2, 3]
Etymology and Origin
The term originates from the ancient Greek word entelecheia. It breaks down into three root words: [1, 2, 3]
Together, it literally translates to “having one’s end within.” []
How It’s Used
Aristotelian Philosophy: Aristotle utilized the word to explain why things change. He posited that everything has an inherent “form” or “purpose” it strives for. He famously described the soul (psyche) as the entelechy of a living body—the active force that makes a body actually live rather than merely exist as a pile of matter. [1, 2]
Psychology: The concept is often translated into modern psychology and self-help as self-actualization—the drive to realize your utmost potential and become the best version of yourself. [1, 2]
Literature: In broader vocabulary, it describes the successful realization of a long-term goal. For example, a debut novel can be described as the entelechy of a writer’s lifelong passion. [1]
