The Authenticity Mandate

A Leader’s Guide to Truth Literacy and Verification Technology

LAST UPDATED: April 24, 2026 at 3:51 PM

The Authenticity Mandate

GUEST POST from Art Inteligencia


The Executive Summary: Why Truth is the New Alpha

As we navigate the complexities of 2026, we have moved past the novelty of generative AI and straight into a crisis of Experience Integrity. In an era where agentic AI can simulate human empathy and synthetic media can fabricate history in real-time, the landscape of leadership has fundamentally shifted. We are no longer just managing information flows; we are the primary stewards of reality for our customers and employees.

The Erosion of “Shared Reality”

The explosion of synthetic media is no longer a technical curiosity—it is a systemic business risk. When the phrase “seeing is believing” becomes obsolete, the friction between a brand and its audience increases exponentially. For leaders, this means moving beyond reactive fact-checking toward a proactive stance on digital provenance. If your stakeholders cannot trust the pixels, they cannot trust the promise behind them.

The Trust Premium: Truth Literacy as a Core Requirement

Truth Literacy has graduated from a niche digital skill to a foundational pillar of organizational agility. In today’s marketplace, there is a measurable “Trust Premium.” Organizations that can demonstrably verify their digital footprint earn a level of loyalty that traditional marketing spend can no longer secure. This literacy must permeate every department—from the experience designers in CX to the compliance officers in Legal.

The Stakes: From Hallucinations to Liability

The cost of inaction is no longer theoretical. We are witnessing the rise of CX Betrayal—the specific psychological break that occurs when a user realizes their interaction was built on an unverified, synthetic foundation. Beyond the erosion of brand equity, the regulatory environment now places the burden of proof squarely on the enterprise. Unverified automated decisions and AI-driven hallucinations are no longer just “technical bugs”; they are significant liabilities that can impact the bottom line and board-level stability.

The Verification Spectrum: Provenance vs. Detection

To effectively manage digital integrity, leaders must distinguish between two fundamentally different approaches: proving the truth and catching the lie. This “Verification Spectrum” defines how organizations validate the media they produce, consume, and distribute.

Provenance: The Digital Birth Certificate

Provenance focuses on the origin and history of a piece of content. Rather than trying to guess if an image is “fake,” provenance allows us to see exactly where it came from and what has happened to it since.

  • C2PA Standards: The Content Authenticity Initiative (CAI) and the C2PA standard provide the technical foundation for “Content Credentials.” These are cryptographic layers embedded in the file—a nutrition label for digital media—that show the camera used, the software that edited it, and any AI enhancements applied.
  • Radical Transparency: For the audience, provenance replaces suspicion with certainty. It moves the burden of proof from the user’s eyes to the asset’s metadata.

Detection: The Digital Polygraph

While provenance works for new content, detection is the necessary “defense” against the billions of existing unverified assets. Detection uses AI to monitor AI, looking for the tell-tale signs of synthetic manipulation.

  • Artifact Analysis: Modern detection engines hunt for biological inconsistencies—such as unnatural blood flow in skin (photoplethysmography) or mismatched reflections in pupils—that are difficult for generative models to perfect.
  • The Arms Race: Leaders must understand that detection is a moving target. As synthetic models improve, detection artifacts disappear, necessitating a shift toward multi-layered “defense-in-depth” strategies that look for behavioral anomalies rather than just visual ones.

Watermarking and Fingerprinting

These technologies serve as the connective tissue between provenance and detection.

  • Invisible Watermarking: Embedding durable, imperceptible signals into content that can survive compression, cropping, or screenshots. This allows brands to “claim” their official communications even when they are reshared in low-trust environments.
  • Digital Fingerprinting: Creating a unique mathematical hash of a file to track its distribution and detect unauthorized tampering or “vibe-coding” by third parties.

Building a Truth-Literate Culture

Technology alone cannot solve the trust crisis. True organizational resilience requires a fundamental shift in how your workforce perceives and interacts with information. Building a “Truth-Literate” culture means moving beyond passive skepticism—which often leads to cynicism and paralysis—toward active verification.

Upskilling for the “Post-Truth” Workplace

In a world where high-fidelity fakes are ubiquitous, we must equip our teams with the cognitive tools to navigate ambiguity. This isn’t just about training people to spot deepfakes; it’s about fostering a mindset of “Zero-Trust Content.”

  • Critical Inquiry: Teaching employees to evaluate the source, the medium, and the intent behind every interaction.
  • The Cost of Speed: Encouraging a “pause” in decision-making when dealing with high-stakes digital assets, ensuring that the pressure for real-time response doesn’t bypass necessary verification protocols.

Operationalizing Veracity: Truth as a Workflow

Verification must move from an afterthought to a core component of the content lifecycle. Whether it is a marketing campaign, a CEO’s internal video address, or an HR training module, truth must be “baked in” from the start.

  • Verification Checkpoints: Integrating automated and human-in-the-loop verification steps into your creative and communications pipelines.
  • Provenance-First Creation: Standardizing the use of tools that automatically generate content credentials at the moment of creation, ensuring your internal assets are “born authentic.”

Closing the Governance Gap

The most significant risk to an organization is often the lack of alignment between departments. Truth Literacy requires a unified front that bridges the traditional silos of Legal, IT, and Customer Experience (CX).

  • The Unified Policy: Developing a clear, cross-functional charter on how your organization uses synthetic media, how it discloses that usage, and how it responds to “synthetic attacks” on the brand.
  • Stakeholder Alignment: Ensuring that the Legal team understands the technical capabilities of provenance, while the CX team understands the ethical boundaries of AI-driven engagement.

The Verification Landscape: Leading Companies and Startups

For leaders to move from awareness to action, it is essential to understand the vendor ecosystem. The market for “Truth Tech” is currently bifurcating into two distinct categories: Shields (technologies that detect and block synthetic threats) and Certificates (technologies that prove an asset’s authentic origin).

The following table outlines the key players and the specific organizational challenges they address:

Category Key Players What They Solve
Enterprise Provenance Adobe (CAI), Truepic, Microsoft Implementing “Content Credentials” to provide an immutable history of edits and origins for digital assets.
Deepfake Detection Reality Defender, Sentinel, Pindrop Real-time analysis to detect synthetic audio and video in high-stakes environments like banking and media.
Strategic Verification NewsGuard, Factmata Providing “Trust Scores” and contextual intelligence for data sources and information cycles.
Forensic Integrity Attestiv, Sensity AI Authenticating photos and videos for insurance, legal, and forensic applications where evidence tampering is a risk.
Authentication Infrastructure Digimarc, Sony Invisible digital watermarking and sensor-level verification at the point of capture (e.g., in cameras).

Choosing Your Partners

When evaluating these vendors, leaders should not look for a “silver bullet” but rather a defense-in-depth strategy. A robust truth infrastructure requires both a “hardened” creation process (provenance) and an “intelligent” perimeter (detection).

  • Interoperability: Ensure the technology adheres to open standards like C2PA, so your verified assets are recognized across the global digital ecosystem.
  • Scalability: Look for solutions that can integrate directly into your existing CMS, CRM, and communication platforms without adding significant latency to the user experience.
  • Ethical Alignment: Partner with companies that prioritize user privacy and the ethical use of metadata, ensuring that in your quest for truth, you do not compromise human agency.

The Strategic Roadmap: Moving from Reaction to Resilience

Transitioning an organization from a state of reactive skepticism to one of proactive resilience does not happen by accident. It requires a structured, phased approach that aligns your technical capabilities with your cultural values. This roadmap provides the high-level steps necessary to secure your “Experience Integrity.”

Phase 1: The Audit—Assessing Your Vulnerability

Before you can defend your truth, you must understand where it is most likely to be attacked. This phase involves a comprehensive assessment of your “Truth Surface Area.”

  • Identifying Friction Points: Mapping the customer and employee journeys to identify where unverified information could cause the most damage (e.g., automated customer support, financial reporting, or executive communications).
  • The “Shadow AI” Audit: Understanding how your teams are currently using generative tools and identifying where synthetic content is being created without provenance or oversight.

Phase 2: The Infrastructure—Hardening the Foundation

Once the vulnerabilities are mapped, the focus shifts to building the technical and procedural “shields” that will protect the organization.

  • Standardizing Provenance: Adopting open standards like C2PA across your content creation stack. This ensures that every official asset your organization produces carries an immutable “Birth Certificate.”
  • Vendor Selection: Curating a stack of verification technologies—choosing the right mix of detection and provenance tools that integrate seamlessly with your existing infrastructure.
  • The “Stable Spine” of Data: Ensuring your internal data repositories are audited and secure, serving as the “Single Source of Truth” that feeds your agentic AI models.

Phase 3: The Disclosure Policy—The Transparency Standard

The final phase is about setting the standard for how you interact with the world. In an age of synthetic reality, radical transparency is your greatest competitive advantage.

  • Explicit Disclosure: Establishing clear guidelines for when and how you disclose the use of AI or synthetic enhancements. This builds trust by removing the “guessing game” for the user.
  • The Incident Response Playbook: Developing a specific protocol for responding to “synthetic attacks”—such as deepfakes of leadership or spoofed brand assets—ensuring your team can move from detection to debunking in minutes, not days.
  • Continuous Learning: Treating Truth Literacy as a living capability, with regular updates to training and technology as the AI landscape continues to evolve.

Conclusion: Leading with Integrity

As we look toward the horizon of the next decade, one thing is certain: technology will continue to accelerate our ability to create convincing illusions. However, while technology can verify data, only leaders can verify intent. In the end, Truth Literacy is not just a technical hurdle to clear—it is a human-centered commitment to the people we serve.

The Human Element in a Synthetic World

We must remember that every data point and every digital asset represents a touchpoint with a human being. When we invest in verification technology, we aren’t just protecting a file; we are protecting the sanctity of the human experience. As leaders, our role is to ensure that as our tools become more “agentic” and autonomous, they remain tethered to our core human values of honesty and transparency.

The Competitive Edge of the Authentic

The future belongs to the “Real.” In a marketplace flooded with infinite, low-cost fakes, authenticity becomes the ultimate luxury good and the most durable competitive advantage. The brands that win in 2026 and beyond will be those that can definitively prove their “realness.” By adopting the strategies of provenance, building a truth-literate culture, and leading with radical transparency, you aren’t just avoiding a crisis—you are capturing the highest possible market share of human trust.

Stay curious, stay skeptical where necessary, but above all, stay human. The architecture of the future is built on the foundations of truth we lay today.

Frequently Asked Questions

1. What is the fundamental difference between content provenance and deepfake detection?

Think of provenance as a digital birth certificate; it uses standards like C2PA to cryptographically prove where an asset came from and how it was edited. Detection, on the other hand, is like a digital polygraph; it uses AI to analyze existing content for “artifacts” or inconsistencies that suggest it was synthetically generated. Provenance focuses on proving the truth, while detection focuses on catching the lie.

2. Why is “Truth Literacy” considered a business imperative rather than just a technical skill?

In an era of “Experience Integrity,” a brand’s value is tied directly to its perceived authenticity. If a customer realizes they’ve been misled by an unverified synthetic interaction—what I call CX Betrayal—the trust is broken permanently. Truth Literacy ensures that leaders and teams can identify these risks, protecting the organization from reputational damage and legal liability.

3. How can an organization begin adopting C2PA standards today?

The first step is a Truth Surface Audit to identify where you create and distribute high-stakes content. From there, you should adopt tools from providers like Adobe or Microsoft that already support “Content Credentials.” By embedding these manifests into your assets at the point of creation, you ensure your official communications are “born authentic” and verifiable across the global digital ecosystem.

Disclaimer: This article speculates on the potential future applications of cutting-edge scientific research. While based on current scientific understanding, the practical realization of these concepts may vary in timeline and feasibility and are subject to ongoing research and development.

Image credits: ChatGPT

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People Are Always the Hardest Part

People Are Always the Hardest Part

GUEST POST from Mike Shipulski

The toughest part of all things is the people part.

Hold on to being right and all you’ll be is right. Transcend rightness and get ready for greatness.

Embrace hubris and there’s no room for truth. Embrace humbleness and everyone can get real.

Judge yourself and others will pile on. Praise others and they will align with you.

Expect your ideas to carry the day and they won’t. Put your ideas out there lightly and ask for feedback and your ideas will grow legs.

Fight to be right and all you’ll get is a bent nose and bloody knuckles. Empathize and the world is a different place.

Expect your plan to control things and the universe will have its way with you. See your plan as a loosely coupled set of assumptions and the universe will still have its way with you.

Argue and you’ll backslide. Appreciate and you’ll ratchet forward.

See the two bad bricks in the wall and life is hard. See the other nine hundred and ninety-eight and everything gets lighter.

Hold onto success and all you get is rope burns. Let go of what worked and the next big thing will find you.

Strive and get tired. Thrive and energize others.

The people part may be the toughest part, but it’s the part that really matters.

Image credit: Pixabay

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You Chose the Top 10 Customer Service Brands

You Chose the Top 10 Customer Service Brands

GUEST POST from Shep Hyken

We live in a world where 76% of customers say they will switch to a competitor if they know they will receive a better customer experience. Understanding which brands consistently win their customers’ hearts and wallets and why isn’t just interesting—it’s essential knowledge that will help you stay competitive.

Each year I survey more than 1,000 U.S. consumers for my annual customer service and CX research. The “audience” mirrors the U.S. population demographics for age, gender, ethnicity, geography and more. We learn about their likes, dislikes, expectations and more when it comes to customer service and customer experience (CX). One of my favorite questions to ask each year is, “When you think of customer service, what are your favorite companies?”

We ask each person to name their three favorites. Many of these brands you would expect to be on this list. For the research report, we listed the top 25 brands. For this article, I’m sharing the top 10. In addition to listing the brands, I’ve shared a few sentences about why these brands are loved by consumers. These lessons show us what our customers want, not just from these brands, but from any brand or company, including yours.

And here’s a disclaimer. This is a “people’s choice” list. You may or may not agree with the choices, but you can’t argue with the numbers. Furthermore, many of these brands have shown up on the list year after year.

So, with no further ado, let’s start with No. 10 and work our way to No. 1 for 2025!

No. 10 – Home Depot

Customers appreciate the friendly service and help from employees who are knowledgeable about tools, paint and building supplies. Home Depot customers appreciate how employees guide them to the right solution and sometimes even share helpful tips. Here’s my tip, based on personal experience. When you have a project, look for an older employee. They often have the experience and wisdom you’re looking for. The lesson: Friendly employees empowered with knowledge create confidence for customers, and confidence builds loyalty.

No. 9 – AT&T

Customers value AT&T’s nationwide coverage, international packages and helpful support, whether in stores or over the phone. Many mention the responsiveness of employees who work to resolve issues quickly. The lesson: In a competitive industry, fast response and reducing friction can win over customers.

No. 8 – Verizon

“Can you hear me now?” Those five words have been part of Verizon’s marketing campaign since the early 2000s. It means Verizon customers can trust its products. In addition, it has reliable service and knowledgeable support teams. Its staff consistently provides clear answers and helps customers make sense of plans, devices and upgrades. The lesson: Reliability plus clarity equals trust, and trust creates the confidence that brings customers back.

No. 7 – Google

I did a Google search and asked, “How many Google searches are there per day? The answer is more than 13 billion! While Google is known for its search engine, it also has many products such as Gmail, YouTube, Google Maps and many others. While much of the experience is self-service, the technology itself delivers convenience that feels effortless. The lesson: Sometimes the best service is making things so easy that customers don’t even need to ask for help.

No. 6 – Costco

Customers love the value (low prices) and quality that Costco delivers through its membership program with generous return policies and an in-store experience that includes friendly and helpful employees. They’ve built a reputation for standing behind what they sell. The lesson: Customer-friendly policies send a powerful message: we’ve got your back.

No. 5 – Chick-fil-A

“It’s my pleasure!” is the phrase the brand’s founder, Truett Cathy, asked employees to use instead of “You’re welcome.” It symbolizes commitment to hospitality. Customers consistently rave about the friendliness of its employees. Even though it is considered to be a fast-food restaurant, it has proven that consistently friendly service—not to mention delicious chicken—wins the hearts of customers. The lesson: A smile and a genuine expression of “my pleasure” can transform ordinary transactions into extraordinary experiences.

No. 4 – Apple

Customers value not only the products but also the support, especially through the Genius Bar and the knowledgeable employees at its retail stores. Employees are trained to explain, teach and solve problems in a way that makes technology approachable. The lesson: Knowledgeable employees who can make the complicated simple remove customers’ fears and replace them with confidence.

No. 3 – Target

Customers want a clean shopping environment with employees who are helpful and approachable. The brand even refers to its customers as guests. That, combined with smooth checkouts and easy returns, is why Target ranks high. The recent news about the DEI rollback can’t be ignored, but Target recognizes this, and its new CEO has announced how they plan to win back customers. The lesson: Customers appreciate friendly employees, an easy shopping experience and convenience in the form of traditional shopping, curbside pickup and same-day delivery options.

No. 2 – Walmart

Customers love the convenience of thousands of locations and low prices. Approximately 90% of Americans live within 10 miles of a Walmart store. That’s convenience, and when you combine that with low prices, you have a winning combination. While you may not find an employee in every aisle (one of the ways Walmart keeps prices down), when you do interact with Walmart employees, they are friendly and helpful. The lesson: Low prices get customers in the door, but an overall positive customer experience that includes friendly employees helps bring customers back.

No. 1 – Amazon

It should not be a surprise that Amazon is ranked No. 1. Often, in my customer service keynote speech, I ask the audience to yell out their favorite company to do business with. I hear Amazon more than any other. Customers love its unmatched convenience. It is open 24/7, has fast delivery and easy returns. It is the ultimate company when it comes to removing friction from the buying experience. The lesson: Easy wins. Make doing business with your company simple, fast and reliable, and customers will reward you with repeat business and loyalty.

Final Words

You may or may not agree with the brands on this list. I was even surprised that a couple of them ended up in the top 10, but this wasn’t my list. It’s a people’s choice list. My comments about each of these brands are based on research, personal experience and informed opinion. Feel free to share your comments, as well as your opinion of other companies you would add to the list.

This article was originally published on Forbes.com.

Image Credit: Shep Hyken

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Aesthetics – Part Two

Aesthetics - Part Two

GUEST POST from Geoffrey A. Moore


From The Cambridge Dictionary of Philosophy entry on Aesthetics

Philosophy of art has also dealt with the nature of taste, beauty, imagination, creativity, representation, expression, and expressiveness; style; whether artworks convey knowledge or truth; the nature of narrative and metaphor; the importance of genre; the ontological status of artworks; and the character of our emotional responses to art.

This is in essence a laundry list of the things I find compelling about esthetics, and in this essay, I plan to dig into each one of them.

Taste

Here’s how the Oxford English Dictionary defines taste relative to esthetics:

OED: 8. The sense of what is appropriate, harmonious, or beautiful; esp. discernment and appreciation of the beautiful in nature or art; spec. the faculty of perceiving and enjoying what is excellent in art, literature, and the like.

Note the struggle here to insert an analytical capability into a pre-linguistic experience. Sense is pre-linguistic, discernment and appreciation are post-linguistic, and faculty is an attempt to unify the two as an analytical skill. In my view, esthetic experience is a two-step process, where sense governs step 1, and discernment governs step 2. This is directly analogous to Coleridge’s primary and secondary imagination, the former coming up with innovations, the latter imposing shape and form upon them. Provided we maintain a disciplined separation between the two steps, we can indeed call this a faculty.

This begs a bigger question, however. How does the pre-linguistic capability of sense recognize what is appropriate, harmonious, or beautiful in the first place? What is the connection between the external and the internal?

Beauty

This is as close as we are going to get to the external pole of esthetic experience, the thing that causes the impact on the internal pole, our conscious self.

OED: 1. Such combined perfection of form and charm of coloring as affords keen pleasure to the sense of sight.

OED: 2. That quality or combination of qualities which affords keen pleasure to other senses (e.g. that of hearing), or which charms the intellectual or moral faculties, through inherent grace, or fitness to a desired end.

Look how out of its depth the OED is here! It is forced to use the word charm twice to invoke little more than inexplicable magic. It is not that I disagree with the word, but what the hell does it mean? OK, let’s ask the OED again:

OED: 3. Any quality, attribute, trait, feature, etc., which exerts a fascinating or attractive influence, exciting love, or admiration.

OK, I agree that beauty has charm, but that does not explain its force, it only labels it. Why is beauty charming? What is it that is fascinating or attractive, exciting our love or admiration?

At the material level, with visual arts, the consensus is that it is due to a combination of color and form that strikes us as harmonious, another word that I agree with but that also seems mystical. But here I think we can make a connection with the experience of mindfulness by asserting that the harmony involved in both experiences is the same. That would suggest that beauty is a spiritually refreshing experience, that it homeostatically returns us to a state of well-being. One virtue of this notion is that it makes it easy to bridge to other arts, like music, where form and color are not the active ingredients, but venturing out and returning to a state of well-being is still in play.

To be fair, for some at least, well-being itself may also be a mystical term, foreshadowing the possibility of an infinite regress of definitions as the analytical intellect struggles to engage with ineffable experiences, but I am willing to stop here and say, from a Darwinian perspective, it makes sense to me that homeostasis is real and relatively prevalent, that it is core to well-being, and that evolution would select for experiences that reinforce it as conferring competitive advantage in human affairs.

Imagination and Creativity

Both these topics extend far beyond the domain of esthetics and the philosophy of art and, if pursued at length, will lead us far off-topic. Within the domain of esthetics, both terms communicate admiration for the ingenuity of the artists who have in some way surprised us with their work. Surprise itself is an integral part of esthetic experience which we will address subsequently.

What we want to investigate here is the presence of the artist in the esthetic experience. In one sense, the artist is not present. We experience the artwork in their absence. But as we engage with multiple works from the same artist, we develop a sense of their style, their values, their topics of interest, and the like. We say things like, “I love Dylan,” or “I can’t stand Proust,” and both statements serve to summarize our esthetic experiences of their work. Where this goes awry, in my view, is when we drag the artist out onto center stage, creating a cult of personality—not a bad thing in itself necessarily, but outside the bounds of esthetics.

Representation, Expression, and Expressiveness

This collection of three terms manifests a tug of war between the Enlightenment and Romanticism about where to anchor the esthetic experience. The Enlightenment focuses on representation as the interaction between the art object, the experiencing subject, and the world at large, positioning art as a subject-object experience that upon absorption reshapes our subject-world experience. In this context, the role of esthetics is to critique the art in relation to the world—how well does the art represent the world to us, and how much has it changed our perception of things? The artist is not directly part of this equation.

By contrast, in the Romantic esthetic, the artist does take center stage. Art is positioned as a subject-object-subject experience, the artifact bridging between the artist and us rather than us and the world. Expression refers to what the artist puts into the artifact, and expressiveness refers to how much of that comes out of the experiencer’s end. For Romantics, this is at the heart of the esthetic experience. For followers of the Enlightenment, it is more of a distraction. They are looking for a solo experience that centers them with respect to the world at large, not a dialectic experience that destabilizes that relationship.

Style

Style is a secondary attribute of esthetics in that one can have style without esthetics, as with a cartoon, as well as esthetics without style, as with a natural landscape. That said, for the Romantics, with their focus on artistic expression, style does indeed “maketh the experience.” It serves as a bridge into the artist’s vision of the world, a way of seeing and being that can be transformative for the experiencer. For the Enlightenment, on the other hand, style is more of a societal asset. It has classic roots in proportion and harmony, attributes that are taken to transcend individual experience, understood instead as autonomously real. Both of these traditions make style more central to art than it was taken to be in the Early Modern period. At that time poetry was said to “teach and delight,” with commentators calling out style—the Elizabethans would have said rhetoric—as one of the chief sources of delight. Indeed, there were handbooks galore about how one could decorate one’s writing and speech with beautiful figures. This represents an early stage of playful euphoria when vernacular languages were displacing Latin across the entire spectrum of European culture.

Today, while all three of these views are still in play, contemporary criticism is often more interested in a fourth—style as a medium for communicating subtext, a mechanism for teasing nuances out of the more overt dimensions of the artwork. Juxtaposition of seemingly unrelated elements reframes our experience of what otherwise would be familiar and taken for granted. The work engages the experiencers’ analytical facilities in the midst of the fantasy experience, a distancing effect that makes them both participant and observer at the same time, accentuating their perception of irony, a cornerstone of the modern esthetic.

Do artworks convey knowledge or truth?

Although this question is intended to help us learn more about art, it introduces two very elusive concepts of its own, namely knowledge and truth, so we need to tread carefully. Nonetheless, the question is a valid one, and we owe it an answer.

To the degree that knowledge and truth are understood to consist of language-enabled statements, the answer is no, artworks do not convey either one. This is the Enlightenment’s position, one that caused it to turn to the concept of taste instead. By contrast, to the degree that knowledge and truth are conceived to transcend language-enabled understanding, meaning that they can reside beyond the scope and ken of reason, then the answer is yes. This is Romanticism’s claim, one that called it to substitute art for religion as a portal to spiritual experience.

Both these positions, however, are unsatisfactory. To be fair, the Enlightenment self-corrected itself in part by directing attention to the sublime, something that since antiquity had always been conceived as transcending reason. But at the end of the day, that did not open any new path to incorporating esthetic experience into one’s overall understanding of the world. The barrier of taste stood firmly in the way. The Romantics, by contrast, embraced transcendence wholeheartedly. Its problem was that it could not access it reliably. That is, neither nature nor art is able to consistently evoke the spiritual refreshment that Romantics value so highly. One is left in a state of anticipation, broken by occasional inspirational moments, but how and when they come at some times and not at others is a mystery. Indeed, the whole claim is a mystery, one that is hard to reconcile with any claims to knowledge or truth.

Contemporary culture, specifically the post-modern wing, dodges these issues by calling into question the reality of both knowledge and truth. Pragmatically, this is just a mistake. The reason we have words for both knowledge and truth is that they represent forces at work in the world that are relevant to our strategies for living. The fact that they are hard to come to grips with does not warrant dismissing them altogether. With that in mind, let us return to our original question: do artworks convey knowledge or truth?

Set aside the incidental communication of information that might accompany an esthetic experience, and focus instead on the experience itself. An external force has, with your permission, taken possession of your faculties and is manipulating your mind to its own ends. This force can be extraordinarily effective at creating belief. Whether that belief represents knowledge or truth cannot be determined from within the experience. Once the experience is over, we can analyze our memory of it, and in that context determine if it warrants being called “justified true belief,” which is philosophy’s gold standard for defining knowledge.

The nature of narrative and metaphor

Narrative and metaphor are two of humanity’s superpowers. Narrative is our most ubiquitous problem-solving tool. Each step in a story implies a cause-and-effect relationship that then can be tested by analytics for credibility. That’s the core function of criticism. Similarly, metaphor is one of our most ubiquitous innovation tools. Each instance proposes a strategic correlation between apparently dissimilar domains, whereby the tactics that have proven successful in the first domain are implicitly applied to address unsolved problems in the second. Again, this too must be tested, either by analytics or experiment.

In this context, what are the esthetic dimensions of narrative and metaphor? What makes for a good story or a good metaphor? I would vote for an experienced tension between expectations and fulfillment which both surprises and enlightens. In narrative, think of Sir Gawain and the Green Knight. What we expect is going to happen in that final encounter and what actually does happen is both surprising and enlightening. Similarly, with respect to metaphor, think of Ezra Pound’s “In a Station of the Metro”:

The apparition of these faces in the crowd:

Petals on a wet, black bough.

In this most industrial of situations, we are surprised and enlightened to find a kind of beauty we thought belonged only in nature.

The importance of genre

To the degree that surprise and enlightenment are core to esthetic experience, genre somewhat surprisingly takes center stage. It sets audience expectations through its established conventions. If it is a comedy, we know that our protagonists will be OK in the end; if it is a tragedy, they will not. To the degree that a given work of art fulfills our expectations, we are pleased but not enlightened. Indeed, if there are no deviations at all—what is often called the domain of stock response—we are likely to get bored and maybe even offended. At the other end of the spectrum, if the work refuses to provide any signals as to genre, we typically ignore it as we have not been invited to participate. However, when a work of art creates expectations and then deviates from them as it unfolds, we can experience a variety of reactions—intrigue, annoyance, doubt, curiosity, and others. The point is, it has engaged us. We are having an esthetic experience whether we like it or not.

Genre creates the bulk of its expectations around beginnings and endings, the former inviting us to open up our minds to engage with and be manipulated by an external force, the latter to bring that experience to a close and initiate any reflections we may have about it. The extent to which art invades our privacy is extraordinary, and so it is natural that we have developed defenses against it. Genres offer an implied contract with respect to what is within bounds and what is off limits. This allows us to prepare ourselves for what is to come, including the option of excluding it altogether (I do not watch horror movies, for example).

Norman Holland gave us a great acronym for understanding this relationship: DFT, which stands for Defense, Fantasy, and Transformation. My contribution is to add an E to it, making it DEFT, where E stands for Expectation. The esthetic experience, in other words, unfolds through four stages, as follows:

  1. Defense. Because art is inherently intrusive—indeed, manipulative—we all have psychological defenses against letting it in. The function of movie trailers, book covers, and online reviews is to get us to take down our defensive barrier and let this particular artwork in. We should keep in mind that this is a relatively rare occurrence. Most shows we do not watch. Most books we do not read. Most museums we do not attend.
  2. Expectation. The way art gets past our defenses is by using genre signals to create an expectation of getting an experience we would like. We know we are being “sold,” but we also are looking for experiences of some sort, and so we are potentially willing to “buy.”
  3. Fantasy. This is the pay-off, the essence of the esthetic experience. The term applies most directly to fiction where we internally imagine scenes based on nothing more than words we are reading. But visual and performative arts also enlist our imaginations, personalizing our experiences such that no two are identical, not even when we are the experiencer both times. These experiences are so intimate and engaging that we have developed an entire discipline to help us interpret them. It is called criticism.
  4. Transformation. Transformation is the business of criticism. We seek to extract from the residue of our fantasy experience ideas that we can incorporate into our strategy for living. We do this both through reflection and conversation, but regardless of the mode, the only evidence we have is our memories of the fantasy experience, and every one of those memories is unique, not only in place (whose memory) but also in time of recall (because memories change every time they are reexperienced). Nonetheless, we persist because these memories are now part of who we are, and if we fail to understand them, we fail to understand ourselves.

Genre participates directly in each of the four steps above, helping bypass our defenses (hey, it’s just an action movie), creating expectations (and it’s from the Marvel universe), teeing us up for fantasy (the viewing experience in which we let the movie take over our mind), and triggering a transformation conversation when it is over (I think Iron Man may need some counseling, or maybe I do).

The ontological status of artworks

Art consists of artifacts whose primary purpose is to deliver an experience as opposed to accomplishing a task. Typically, they do so by engaging the imagination of the participant in a fantasy shaped through either a sensory stimulus (painting, sculpture, dance, music, and the like) or a language act (stories, poetry, novels, and the like) or a combination of the two (plays, films, opera, and the like). We assign these artifacts a special status because we evaluate them not only on their craft but also on the quality of the experiences they evoke. Assessing that quality, its impact, and the contribution that craft makes to it is the purpose of esthetics.

The realm of esthetics extends well beyond the fine arts. In contemporary culture, for example, cuisine has taken center stage, for even as it performs a utilitarian task, it also creates emotional experiences of considerable force, particularly when tied to family, ethnic, or personal traditions. Proust’s Madeleine is a famous psychological example, but today the focus is more on cultural ties, where esthetics helps promote cross-cultural connections that can reinforce social cohesion. Similar esthetic circles form around cars and personal attire, really any field of life where identity binds itself to experiences that go beyond utility. The dialog is typically a mixture of the practical and the esthetic, the two fusing into a kind of expertise that goes viral on digital media, which brings us to our last topic.

The character of our emotional responses to art

One way to characterize our responses to art is in relation to our emerging knowledge of how our brains actually work. Our consciousness resides in the neocortex, that part of the brain we see from the outside that looks something like a cauliflower. The neurons in the neocortex are optimized to perform two functions:

  1. Engage with the things and events that are happening around us and initiate appropriate responses to them, and
  2. Imagine how such things and events might be different, and what such differences might lead to in terms of alternative responses.

It turns out that the very same neurons that perform function 1 also perform function 2, which makes for some interesting implications:

  • Each function trains the other one. That is, experience in the world feeds the imagination with material to work on, and imagined experiences expand the repertoire of alternatives our engagement function can draw upon.
  • Because the exact same neurons are used in both cases, the functions are mutually exclusive, meaning you can’t engage with the world when you are imagining, and you can’t imagine things when you are engaging with the world.

These implications cast important light on two elements of our response to art. The first is that we are drawn to it naturally. That is, evolution favors constructive use of imagination, and imagination is enhanced by engaging with art. Esthetics in this context investigates the specifics of the attraction itself, what elements in the art motivate us to attend to it, and the impact the experience has on our ability to engage with the world thereafter.

The second point, that we cannot both imagine and engage at the same time, speaks to the question of whether there is a specific attitude one must take in order to appreciate art. The answer is, yes, but it is totally involuntary. The notion that one must train oneself to adopt the appropriate attitude is yet another example of the analytical intellect overstepping its bounds. Analysis is fundamental to Transformation, but it has no role in Fantasy.

Our emotional responses to art touch all four phases of the esthetic experience. That is, our Defense against art we don’t like is driven by an emotional rejection we often are unable to explain. In contrast, our Expectation that some art will please us is driven by desires we are only too willing to explain. Regardless of our expectations, our Fantasy experience is highly varied with respect to emotion, which often correlates with how much or how little we value the art in question. Finally, our Transformation experience seeks to assess the impact of whatever emotion we did experience when recollected in tranquility.

That’s what I think. What do you think?

Click here to Read Part 1 if you missed it

Image Credit: Pexels

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Which of the Nine Innovation Roles do you play? (A Quiz)

Which of the Nine Innovation Roles do you play? (A Quiz)

by Braden Kelley

Too often we treat people as commodities that are interchangeable and maintain the same characteristics and aptitudes. Of course, we know that people are not interchangeable, yet we continually pretend that they are anyway — to make life simpler for our reptile brain to comprehend.

I’m of the opinion that all people are creative, in their own way. That is not to say that all people are creative in the sense that every single person is good at creating lots of really great ideas, nor do they have to be. I believe instead that everyone has a dominant innovation role at which they excel, and that when properly identified and channeled, the organization stands to maximize its innovation capacity. I believe that all people excel at one of Nine Innovation Roles, and that when organizations put the right people in the right innovation roles, that your innovation speed and capacity will increase.

The Nine Innovation Roles as a concept were introduced in my bestselling book Stoking Your Innovation Bonfire and people have always asked me if I had a quiz people could take to see what their primary and secondary roles are and my answer has always been NO, until now, when thanks to Claude I’ve been able to create one for the world to enjoy. I think it turned out pretty well and I’ve embedded it here in this article and also create a Nine Innovation Roles Quiz sub-page for it live on in perpetuity.

I hope you enjoy it!

Discover Your
Innovation Role

Answer 20 questions to uncover where you add the most value in any innovation effort. Based on Braden Kelley’s Nine Innovation Roles framework.

Question 1 of 20 0%
Question 1

The Nine Innovation Roles

If you’re not familiar with the Nine Innovation Roles, they are:

Nine Innovation Roles Revolutionary

1. Revolutionary

The Revolutionary is the person who is always eager to change things, to shake them up, and to share his or her opinion. These people tend to have a lot of great ideas and are not shy about sharing them. They are likely to contribute 80 to 90 percent of your ideas in open scenarios.

Nine Innovation Roles Conscript

2. Conscript

The Conscript has a lot of great ideas but doesn’t willingly share them, either because such people don’t know anyone is looking for ideas, don’t know how to express their ideas, prefer to keep their head down and execute, or all three.

Nine Innovation Roles Connector

3. Connector

The Connector does just that. These people hear a Conscript say something interesting and put him together with a Revolutionary; The Connector listens to the Artist and knows exactly where to find the Troubleshooter that his idea needs.

Nine Innovation Roles Artist

4. Artist

The Artist doesn’t always come up with great ideas, but artists are really good at making them better.

.

Nine Innovation Roles Customer Champion

5. Customer Champion

The Customer Champion may live on the edge of the organization. Not only does he have constant contact with the customer, but he also understands their needs, is familiar with their actions and behaviors, and is as close as you can get to interviewing a real customer about a nascent idea.

Nine Innovation Roles Troubleshooter

6. Troubleshooter

Every great idea has at least one or two major roadblocks to overcome before the idea is ready to be judged or before its magic can be made. This is where the Troubleshooter comes in. Troubleshooters love tough problems and often have the deep knowledge or expertise to help solve them.

Nine Innovation Roles Judge

7. Judge

The Judge is really good at determining what can be made profitably and what will be successful in the marketplace.

.

Nine Innovation Roles Magic Maker

8. Magic Maker

The Magic Makers take an idea and make it real. These are the people who can picture how something is going to be made and line up the right resources to make it happen.

.

Nine Innovation Roles Evangelist

9. Evangelist

The Evangelists know how to educate people on what the idea is and help them understand it. Evangelists are great people to help build support for an idea internally, and also to help educate customers on its value.

So, which one(s) resonate most with you? Want to find out if you’re right? Take the quiz!

Free Stuff

If you go to the main Nine Innovation Roles page you’ll find all kinds of free downloads and sub pages, including:

  1. Nine Innovation Roles pages in Spanish, Portuguese, French and Swedish (and I’m always happy to give credit and link to anyone willing to translate them into other languages)
  2. Nine Innovation Roles card design to download for printing with adMagic (or your vendor)
  3. Nine Innovation Roles downloadable presentation
  4. Nine Innovation Roles team worksheet
  5. Nine Innovation Roles introductory video to use in workshops
  6. This Nine Innovation Roles Quiz!

Keep innovating!

Click here to access your Nine Innovation Roles freebies

Image Credits: Braden Kelley, Google Gemini

Why an AI Soft Landing Might Look Like Victorian England

LAST UPDATED: April 18, 2026 at 3:29 PM

Why an AI Soft Landing Might Look Like Victorian England

by Braden Kelley and Art Inteligencia


The Mirage of the Post-Scarcity Utopia

For decades, the prevailing narrative surrounding artificial intelligence has been one of a post-scarcity “Star Trek” future. The logic was simple: as machines took over the labor, the dividends of automation would be harvested by the state and redistributed via Universal Basic Income (UBI), freeing humanity to pursue art, philosophy, and leisure.

The AI Promise vs. The Fiscal Reality

However, this utopian vision ignores the gravity of The Great American Contraction. As we approach 2026 and beyond, the friction between exponential technological growth and a $37 trillion+ national debt (with a $2 trillion annual budget deficit) creates a structural barrier to redistribution. When the tax base of human labor erodes, the math for a livable UBI simply fails to compute.

The Victorian Hypothesis

If UBI is a mathematical and political impossibility fueled by corporate and human greed, we must look toward an alternative “soft landing.” This hypothesis suggests a vertical restructuring of society. As AI drives the cost of production and the demand for goods into a deflationary spiral, the purchasing power of the remaining “employed elite” will skyrocket.

The result isn’t a horizontal distribution of wealth, but a return to a Neo-Victorian social hierarchy. In this reality, the new digital gentry will use their outsized wealth to employ a massive “servant class” to maintain stately homes and personal lives, creating a world where status is defined by the human labor one can afford to command.

Neo-Victorian Hypothesis Infographic

The Great American Contraction: Why UBI is a Non-Starter

The conversation around the transition to an AI-driven economy often treats Universal Basic Income as an inevitability — a safety net that will naturally catch those displaced by the silicon wave. However, this assumes a level of fiscal elasticity that no longer exists. We are entering The Great American Contraction, a period where the traditional levers of government spending are restricted by the sheer weight of historical obligation and systemic greed.

The Debt Ceiling of Compassion

With a national debt exceeding $37 trillion, a $2 trillion budget deficit and rising interest rates, the federal government’s “room to maneuver” has effectively vanished. A livable UBI requires a massive, consistent tax base. As AI begins to hollow out the middle class, the very tax revenue needed to fund such a program disappears. To fund UBI under these conditions would require a level of sovereign borrowing that the global markets simply will not support, leading to a reality where the government cannot afford to be the savior of the displaced.

The Greed Variable

Even if the math were more favorable, the human element remains a constant. Corporate interests, focused on margin preservation and shareholder value, are unlikely to support the aggressive taxation required to fund a social floor. In the race to the bottom of production costs, the primary goal of the “winners” in the AI revolution will be wealth concentration, not social equity. The political willpower to force a massive transfer of wealth from AI-profiting corporations to the idle masses is a historical outlier that we should not count on repeating.

The Velocity of Displacement

Finally, the speed of the AI transition is its most disruptive feature. Legislative bodies move in years, while AI cycles move in weeks. By the time a political consensus for UBI could be formed, the economic floor will have already fallen out. This lag time creates a vacuum that will be filled not by government checks, but by a desperate search for subsistence, setting the stage for the return of the domestic labor economy.

The Deflationary Paradox: Collapse of Demand and Cost

In a traditional economy, unemployment leads to recession, which usually leads to stagflation or managed recovery. However, the AI-driven “soft landing” introduces a unique mechanical failure: the Deflationary Paradox. As AI and advanced robotics permeate every sector, the labor cost of producing goods and services begins to approach zero, but the pool of consumers capable of buying those goods simultaneously evaporates.

The Production Floor Drops

We are witnessing the end of the labor theory of value. When an AI can design, a robot can manufacture, and an automated fleet can deliver a product without a single human touchpoint, the marginal cost of production hits the floor. In a desperate bid to capture the dwindling “active” capital in the market, companies will engage in a race to the bottom, causing the prices of physical and digital goods to deflate at a rate unseen in modern history.

The Demand Vacuum

While cheap goods sound like a boon, they are a symptom of a deeper rot: the Demand Vacuum. As the middle class is hollowed out, the velocity of money slows to a crawl. The economy shifts from a mass-consumption model to a precision-consumption model. Most businesses will fail not because they can’t produce, but because there are no longer enough customers with a paycheck to buy, even at rock-bottom prices.

The Purchasing Power of the “Remaining”

This is where the Victorian shift begins. For the small percentage of Americans who retain their income — the innovators, the orchestrators, and the entrepreneurs — this deflationary environment is a golden age. Their dollars, fixed in value while the cost of everything else drops, suddenly possess exponential purchasing power. When a gallon of milk or a digital service costs mere pennies in relative terms, the “wealthy” find themselves with a massive surplus of capital that cannot be spent on “things” alone. This surplus will naturally be redirected toward the one thing that remains scarce and high-status: the dedicated service of another human being.

The New “Stately Home” Economy

As the Deflationary Paradox takes hold, we will see a fundamental shift in the definition of luxury. In the pre-AI era, luxury was defined by the acquisition of high-tech gadgets or rare goods. In the Neo-Victorian era, where machines produce goods for nearly nothing, “luxury” will pivot back toward the human-centered experience. Status will no longer be measured by what you own, but by whose time you command.

From Software to Service

For the “In-Group” — those entrepreneurs and specialized leaders still generating significant revenue — capital will lose its utility in the digital marketplace. When software is free and manufactured goods are commoditized, wealth seeks the only remaining friction: human presence. We will see a massive migration of capital away from Silicon Valley “platforms” and toward the local domestic economy. The wealthy will stop buying more “things” and start buying “lives” — the total dedicated attention of house managers, chefs, valets, and tutors.

The Modern Manor

This economic shift will be physically manifested in the return of the Stately Home. These won’t just be houses; they will be complex ecosystems of employment. Large estates will once again become the primary employer for local communities. As traditional corporate offices vanish, the residence becomes the center of both social and economic power. These modern manors will require extensive human staffs to cook, clean, maintain grounds, and provide security — services that, while technically possible via robotics, will be performed by humans as a deliberate signal of the owner’s immense “effectively wealthy” status.

The Return of the Domestic Professional

Perhaps the most jarring aspect of this transition will be the class of worker entering domestic service. We are not talking about a traditional blue-collar service shift, but the “Victorianization” of the former middle class. Displaced white-collar professionals — accountants, teachers, and middle managers — will find that their highest-paying opportunity is no longer in a cubicle, but in managing the complex domestic affairs, private education, and logistics of the new digital aristocracy. It is a “soft landing” in name only; while they may live in proximity to grandeur, their survival is entirely tethered to the whims of their employer.

Socio-Economic Stratification: The Two-Tiered Reality

The inevitable result of the “Victorian Soft Landing” is the formalization of a rigid, two-tiered social structure. Unlike the 20th century, which was defined by a fluid and expanding middle class, the post-contraction era will be characterized by extreme polarization. The economic “missing middle” creates a vacuum that forces every citizen into one of two distinct realities: the Digital Gentry or the Dependent Class.

The Corporate and Government Gentry

A small percentage of Americans — likely less than 10% — will remain tethered to the engines of primary wealth creation. This “In-Group” consists of high-level AI orchestrators, strategic entrepreneurs, and essential government officials who maintain the infrastructure of the state. Because their income is derived from high-margin automated systems while their cost of living has plummeted due to deflation, they possess a level of functional wealth that rivals the landed gentry of the 19th century. To this group, the “Great Contraction” is not a crisis, but a refinement of their dominance.

The Dependent Class

For those outside the digital fortress, the reality is stark. Without a national UBI to provide a floor, the majority of the population becomes the “Dependent Class.” Their economic utility is no longer found in the marketplace of ideas or manufacturing, but in the marketplace of personal service. In this neo-Victorian landscape, you either work for the companies that own the AI, work for the government that protects it, or you work directly for the individuals who do.

The Choice: Service or Scarcity

This stratification reintroduces a primal power dynamic into the American workforce. When the cost of basic survival (food and shelter) is low due to deflation, but the opportunity for independent income is zero, the wealthy gain total leverage. The “soft landing” is, in truth, a forced labor transition. Those who are not “useful” to the gentry — either as specialized labor or domestic support — face the grim reality of the Victorian workhouse era: they must find a patron to serve, or they will starve in a world of plenty.

Experience Design in the Neo-Victorian Era

Experience Design in the Neo-Victorian Era

From the perspective of experience design and futurology, the shift toward a Victorian-style social structure will fundamentally alter the aesthetic of status. In a world where AI can generate perfect, flawless goods and digital experiences at zero marginal cost, “perfection” becomes a commodity. Status, therefore, will be redesigned around human friction and intentional inefficiency.

The Aesthetic of Inequality

We will see a move away from the sleek, minimalist “Apple-esque” design of the early 21st century toward a more ornate, human-heavy luxury. Experience design for the elite will emphasize things that AI cannot authentically replicate: the slight imperfection of a hand-cooked meal, the presence of a uniformed gatekeeper, and the physical maintenance of vast, non-automated gardens. Architecture will pivot back to “human-centric” layouts—designing spaces not for efficiency, but to accommodate the movement and housing of a live-in staff.

Designing for Disconnect

The most challenging aspect of this new era will be the Experience of the Invisible. Designers will be tasked with creating systems that allow the Digital Gentry to interact with their environment without acknowledging the vast economic disparity surrounding them. This involves “Social UX” — designing layers of intermediation where the “Dependent Class” provides the comfort, but the “Gentry” only interacts with the result. It is a return to the “back-stairs” architecture of the 19th century, modernized for a digital age.

The UX of Survival

For the majority, the “User Experience” of daily life will be one of Hyper-Personal Patronage. Navigation of the economy will no longer be about interfaces or platforms, but about the “UX of Relationships.” Survival will depend on the ability to design one’s persona to be indispensable to a wealthy patron. In this reality, human-centered design takes on a darker, more literal meaning: the human becomes the product, the service, and the infrastructure all at once.

Conclusion: Preparing for the Retro-Future

The “Soft Landing” we are currently engineering is not the one we were promised. As the Great American Contraction forces a collision between astronomical debt and the deflationary power of AI, the middle-class dream of a subsidized leisure class is evaporating. In its place, we are seeing the blueprints of a Retro-Future — a world that looks forward technologically but moves backward socially.

A Call for Human-Centered Transition

If we continue to view innovation solely through the lens of efficiency and margin preservation, the Victorian outcome is not just possible — it is inevitable. We must realize that without a radical redesign of how we value human contribution beyond mere “market productivity,” we are simply building a more efficient feudalism. True Experience Design must now focus on the social fabric, or we risk creating a world where the only “innovation” left is finding new ways for the many to serve the few.

Final Thought: The Soft Landing Paradox

We must be careful what we wish for when we ask for a “seamless” transition. A landing that is “soft” for the Digital Gentry is one where the friction of poverty and the noise of the displaced have been successfully silenced by the return of the servant class. History doesn’t repeat, but it does rhyme — and right now, the future sounds remarkably like 1837. The question is no longer if AI will change our world, but whether we have the courage to design a future that doesn’t require us to retreat into our past.

Frequently Asked Questions

Why would prices deflate if the economy is struggling?

In this scenario, AI and robotics drive the marginal cost of production toward zero. Simultaneously, massive job displacement creates a “demand vacuum.” To capture what little liquid currency remains, companies must drop prices drastically, leading to a reality where goods are incredibly cheap but income is even scarcer.

How does this differ from the 20th-century middle class?

The 20th century was defined by a “horizontal” distribution where many people owned moderate assets. The Neo-Victorian model is “vertical.” The middle class disappears, replaced by a tiny, hyper-wealthy elite (Digital Gentry) and a large class of people who provide them with personalized human services (the Servant Class).

Isn’t UBI a more logical solution to AI displacement?

While logical in theory, the “Great American Contraction” hypothesis suggests that high national debt and corporate prioritisation of margins make a livable UBI politically and fiscally impossible. Without a state-funded floor, the market defaults to the oldest form of social safety: personal patronage and domestic service.

EDITOR’S NOTE: This is a visualization of but one possible future. I will be publishing other possible futures as they crystallize in my mind (or as you suggest them for me to explore).

Image credits: Google Gemini

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Google Gemini to clean up the article, add images and create infographics.

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Ideas Are Validated Forwards Not Backwards

Ideas Are Validated Forwards Not Backwards

GUEST POST from Greg Satell

In 2007, our media company in Ukraine completed its IPO and would soon be valued at $100 million. For a rough and tumble organization that, just a few years before, was a relatively small business, it was exhilarating. We had big plans and were eager to execute them. It was a “damn the torpedoes, full speed ahead” moment.

We also had an innovative strategy that we thought was a clear winner — a bet on Ukrainian language media. Although the Russian language was dominant at the time, we thoroughly researched the idea and found that a large part of the market said they preferred Ukrainian. To grab the opportunity, we launched three major brands in a year.

It was a disaster. Although the first launch was cause for concern, we were moving so fast the other two were too far along to stop. Then the 2008 global financial crisis hit and we were soon struggling to stave off bankruptcy. It was a brutal lesson. You can research an idea, but you never really know what you have until you’ve actually tested it in the marketplace.

The Rule Following Paradox

The Philosopher Ludwig Wittgenstein famously wrote, “no course of action could be determined by a rule, because every course of action can be made out to accord with the rule.” He meant that every rule is subject to some interpretation and, given varying contexts, interpretations are bound to vary.

That’s essentially what happened to us. We did our research and combed through all the evidence. Television and advertising was, by law, in Ukrainian and not Russian. Consumer surveys consistently showed that a significant portion of the Ukrainian public preferred Ukrainian language media. There were plenty of signs that we were on to something.

Given that analysis, our course seemed clear. We should not only launch Ukrainian language products, we should proceed at a rapid pace so that we could move out ahead of the pack. Surely, once competitors saw how big the opportunity was, they would pounce and our opportunity would be squandered.

Except that there was no opportunity. We weren’t acting on facts, but our interpretation of them and that interpretation was horribly, drastically wrong. To make matters worse, all this was happening as the Ukrainian media market was hitting its peak and the world was about to head off a cliff into the worst financial crisis since the Great Depression.

Survivorship Bias

Business school professors and consultants gain fame—not to mention large fees—when they are able to define a novel concept or success factor. If you are able to isolate one thing that organizations should do differently, you have a powerful product to sell. A single powerful insight can make an entire career, which is probably why so many cut corners.

For example, in their study of 108 companies, distinguished INSEAD professors W. Chan Kim and Renée Mauborgne found that “blue ocean” products, those in new categories without competition, far outperform those in the more competitive “red ocean” markets. Their book, Blue Ocean Strategy, was an immediate hit, selling over 3.5 million copies.

Bain consultants Chris Zook and James Allen’ book, Profit from the Core, boasted even more extensive research encompassing 200 case studies, a database of 1,854 companies, 100 interviews of senior executives and an “extensive review” of existing literature. They found that firms that focused on their ”core” far outperformed those who strayed.

It doesn’t take too much thinking to start seeing problems. How can you both “focus on your core” and seek out “blue oceans”? It betrays logic that both strategies could outperform one another. Also, how do you define “core?” Core markets? Core capabilities? Core customers? While it’s true that “blue ocean” markets lack competitors, they don’t have any customers either. Who do you sell to?

Yet there is an even bigger, more insidious problem called survivorship bias. Notice how “research” doesn’t include firms that went out of business because there were no customers in those “blue oceans” or because they failed to diversify outside of their “core.” The data only pertains to those that survived.

The Problem With Case Studies

The gold standard for research is randomized, double blind trials in which some of the subjects receive some sort of intervention, a control group gets a placebo and no one, not even those conducting the study, know which subjects are in which group. This design minimizes the chance of bias affecting results.

Yet this type of design is impractical for studying real businesses that are competing in the marketplace. So researchers largely depend on case studies in which participants are interviewed after the fact. These can be helpful in that they offer first-person perspectives of events and their context, but have obvious problems.

First, much like in Wittgenstein’s rule-following paradox, a lot is left up to interpretation. There are rarely more than a half-dozen people interviewed and they tend to be insiders. We almost never hear from competitors, customers or lower level employees. Then the researchers themselves bring their own biases to what they see and hear.

There are also issues with survivorship bias. Clearly, key players will be much more forthcoming about successes than failures. So we tend to hear about strategies that worked when, for all we know, those same strategies may have failed in other organizations and other contexts. There’s simply no real way for us to know.

Incidentally, researchers did a series of case studies on our company and I was struck by how much they depended on who was interviewed. While there wasn’t anything factually wrong, a different sample of perspectives would have led to very different interpretations.

Adopting A Bayesian Strategy

Traditionally, strategy has been seen as a game of chess. Wise leaders survey the board of play, plan their moves carefully and execute flawlessly. That’s always been a fantasy, but it was close enough to reality to be helpful. Organizations could build up sustainable competitive advantage by painstakingly building up bargaining power within the value chain.

Yet as Mike Tyson pointed out, “everybody has a plan until they get hit.” We can research and plan all we want, but the real world is a messy place. The facts, as we see them, are really just interpretations of the data we have available to us. Invariably, there are other data we’re not seeing and, even that which we have in front of us, can be interpreted in multiple ways.

That’s why we need to take a more Bayesian approach to strategy, in which we don’t pretend that we have the “right strategy,” but endeavor to make it less wrong over time. As Rita Gunther McGrath has put it, it’s no longer as important to “learn to plan” as it is to “plan to learn.” We need to be more iterative, see what works and change course as needed.

Today, instead of thinking about strategy as a game of chess, we’d do better to envision an online role-playing game, in which you bring certain capabilities and assets and connect with others to go on quests and discover new things along the way. Unlike chess, where everyone knows that their objective is to capture the opponent’s king, we need to expect the rules to change over time and adapt accordingly.

— Article courtesy of the Digital Tonto blog
— Image credit: Unsplash

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Liberated to Care – How AI Can Restore Humanity in Healthcare

Liberated to Care - How AI Can Restore Humanity in Healthcare

GUEST POST from Kellee M. Franklin, PhD.

Heapy has long been a quiet force in the evolution of healthcare design – not with grand pronouncements, but with deep, thoughtful work that reshapes how we experience care. For decades, they have approached hospitals and clinics not as static buildings, but as living ecosystems – places where healing does not happen despite the surroundings, but because the space was designed to make it possible.

Their work goes beyond sustainability in the traditional sense – energy efficiency, material choices, LEED certifications – though they lead there, too. What sets Heapy apart is their commitment to human sustainability: designing spaces that support not just the planet, but the people within them. Clinicians. Patients. Families. The entire care team.

They understand that a healing environment is not just about clean lines and natural light – though those things matter. It is about creating places that reduce stress, prevent burnout, and foster connection. Spaces that are flexible enough to adapt to a pandemic, yet intimate enough to embrace the ailing or comfort a grieving family.

And they do this not in isolation, but in partnership – with providers, communities, vendors, and innovators who recognize that the future of healthcare is not only about smart technologies, but about deep human intention. It is not just what we build, but why – and for whom.

It was in that spirit last week, I had the honor of serving as the keynote speaker at Heapy’s Symposium on Sustainability in Healthcare, hosted in the beautiful “Queen City” of Cincinnati, Ohio – a gathering of dreamers and designers from across industries, all united by a shared belief: that the future of care must be human-centered.

It was in that room, surrounded by industry pioneers, who see beyond efficiency and into empathy, that the vision for a different kind of healthcare took shape – not as a distant ideal, but as a gentle uprising already underway.

We have spent decades optimizing a system that was not built to heal. It was not built for people at all. It is a machine – and both patients and caregivers are just trying to survive it.

We have chased speed, throughput, and cost-cutting – as if care were an assembly line. But in the rush to do more, faster, we have lost something irreplaceable: the human connection that lies at the heart of healing.

Clinicians drown in documentation; their eyes fixed on screens instead of faces. Patients feel like data points, shuffled through impersonal workflows. And hospital administrators, well-meaning as they are, focus on numbers that measure activity, not meaning.

But what if we stopped trying to make the machine run faster – and started asking: How might we build something entirely different? Not a smarter system, but a human one?

Not a system that grinds, but one that breathes. Not one that manages, but cares.

That is the future we are stepping into – not as a distant dream, but as a calm, determined shift, unfolding from the electricians who wire our buildings to the executives who shape our boardrooms. Not a future where technology replaces humanity, but one where it finally sees us – amplifies us – and reminds us why we are here.

And this future – the heart of healing — rests on four pillars, championed by forward-thinking organizations like The American College of Healthcare Executives (ACHE): liberating clinicians, designing for resilience, committing to learning, and personalizing care.

Automation in Healthcare

Liberating Clinicians: Letting Humans Be Humans

Imagine a clinic where the doctor looks at you – not at a screen. Where nurses spend their shifts at the bedside, not buried in charts. Where the administrative load does not fall on the shoulders of those already stretched thin – like patients juggling multiple portals, passwords, and fragmented records.

That is not fantasy. It is the promise of AI as an ally, not an agitator.

We are already seeing systems where AI stealthily handles prior authorizations, drafts clinical notes, and surfaces critical data – not to replace clinicians, but to free them. Early adopters report not just time savings, but better patient outcomes. But the real win? Time. Time to listen. Time to notice. Time to care.

Because healing is not transactional. It is relational. It lives in the pause, the eye contact, the hand on the shoulder. And when we automate the mechanical, we make space for the meaningful. The metric should not be how many patients we see – but how deeply we see them.

Designing for Resilience: Spaces that Adapt, Not Just Endure

Now picture the places where care happens.

Too often, they feel like relics – rigid, impersonal, built for a world that no longer exists. The next generation of healing environments must be different. They must be resilient, not just in structure, but in spirit.

We need hospitals that can withstand storms – literal and metaphorical. That can scale during surges, pivot during pandemics, and adapt to the rapid pace of change. Modular walls. Flexible rooms. Infrastructure that evolves.

But resilience is not just about durability – it is about humanity.

It is peaceful zones for staff to decompress. Natural light in every patient room. Wayfinding that feels intuitive, not clinical. It is designing for emotional endurance as much as physical strength.

Because burnout is not just caused by workload – it is shaped by environment. A space that feels cold, chaotic, or dehumanizing wears people down. One that feels calm, connected, and cared for – even in a crisis – helps them endure.

So let us stop building facilities and start creating healing ecosystems. Places that support not just survival, but the fullness of life – where healing and wholeness go hand-and-hand.

Committing to Lifelong Learning: Growing…Together

Even the smartest tools and strongest walls will not matter if we do not equip people with the knowledge, skills, and supportive environment they need to grow.

That is why ongoing education is not just a nice-to-have – it is non-negotiable. But not the kind of training that feels like a box to check. We need learning that is alive, adaptive, and human-centered.

Leaders, clinicians, and designers need to understand not just how to work with AI – but why it matters to their work. It is not about compliance – it is about curiosity. Not just in operating it but partnering with it. We need safe spaces to experiment, explore, grow – and yes, even fail. No innovation happens without change – and no meaningful change happens without real learning.

Micro-learning modules. Peer mentorship. Protected time for reflection. These are not luxuries – they are lifelines of learning and innovation.

And when leaders model learning – when they say, “I don’t know, let’s figure it out together” – they signal that growth matters more than perfection.

Because the future of care is not about mastering technology – it is about forming partnerships. With each other. With patients. With tools that extend our capacity, not replace our judgment.

Transforming Care

Personalizing Care: Seeing the Person, Not the Problem

Finally, imagine care knows you.

Not in a surveillance way – not data hoarded, but wisdom shared. AI that can tailor treatments plans, adjust room settings, and anticipate needs – always with consent, transparency, and control.

This is not about efficiency. It is about dignity.

It is remembering the patient’s name. Honoring their preferences. Adapting to their story. Adjusting to their situation. The most powerful curative is still human attention – and AI can help us focus it.

We are already seeing systems where AI personalizes everything from medication timing to discharge planning – not to automate empathy, but to boost it.

Because when care feels seen and heard, the healing penetrates deeper.

Five Actions for Leaders: From Vision to Practice

So, what can leaders do – right now – to turn this vision into reality?

  1. Redesign Workflows Around Human Dignity: Stop measuring success by speed. Reengineer processes to reduce burnout and restore time for true connection. Use AI to handle the mechanical – documentation, scheduling, billing – and let it also surface critical insights, flag at-risk patients, and streamline workflows so clinicians can focus on what they do best: medicine. Measure moments of care, not mouse clicks – and allow AI to illuminate what truly matters: patient healing and well-being.
  2. Co-Create with Frontline Teams: No more top-down rollouts. Invite nurses, doctors, and support staff into the design of every new tool, space, workflow, and policy. – and use AI to elevate their voices, not override them. Imagine AI that analyzes frontline feedback in real-time, surfaces hidden pain points, and co-generates solutions alongside those who know the work best. Ask: Does this help you provide better care? Their lived experience, supported by intelligent insight, guide what gets built – because the best solutions do not emerge from closed boardroom doors, but from the open collaborative hands and hearts within the community of care.
  3. Build Spaces that Breathe: Invest in modular, adaptable infrastructure – but go further. Design for emotional resilience: tranquil zones, natural light, intuitive layouts, and AI-enhanced environments that respond to human needs in real-time. Imagine rooms that adjust lighting and temperature based on patient stress levels, or corridors that guide staff to moments of respite between high-pressure tasks. A healing space is not just durable – it is humane, alive with invisible intelligence that supports the whole-person: mind, body, heart, and spirit.
  4. Champion Learning as an Act of Care: Make continuous education protected time, not an afterthought. Offer micro-learning, peer mentorship, and collaborative spaces – and harness AI as a dynamic learning partner. Imagine intelligent systems that surface personalized insights, adapt to individualized learning styles, and guide clinicians through real-time decision support that doubles as on-the-job training. When leaders model curiosity and embrace AI not just as a tool, but as a catalyst for growth and innovation, they create cultures where learning is ongoing and invigorating.
  5. Personalize Without Surveillance: Use data to deepen trust, not erode it. Implement AI that personalizes care – predicting needs, tailoring environments, and adapting support – but always with consent, transparency, and patient control. Let personalization mean dignity: remembering a name, honoring a preference, adapting to a story, adjusting to a changing situation, and above all, putting people, not patterns, at the center.

A Future That Feels Human, Beautifully Imperfect

This is not about replacing the system. It is about reimagining it.

From one that manages people to one that sees them.

From one that measures output to one that values presence.

From one that optimizes speed to one that honors slowness – personal focus, deep listening, and the easy moments of connection that no algorithm can replicate.

The tools are here. The insights are clear. The question is no longer can we – but will we?

Will we choose efficiency – or humanity?

Will we build systems that merely function – or ones that truly heal?

The answer lies not in technology, but in where we choose to place our attention – and our intention.

As a Triple Negative Breast Cancer survivor, I have felt firsthand how cold and mechanical care can be – and how profoundly a space can either deepen that pain or help heal it. I have also seen how systems can exhaust the very people meant to deliver care. But I hold onto a belief: healing begins when we return to our humanity. From designers and clinicians to administrators and patients, each of us plays a vital role in co-creating a whole-health environment where care is not just delivered, but genuinely experienced.

And perhaps the most revolutionary act in healthcare today might just be this: to care, deeply, as beautifully imperfect humans – and to let everything else serve a universal truth – one rooted in compassion, true connection, and shared humanity.

Image credits: Kellee M. Franklin

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The Consumption Collapse – When the Feedback Loop Bites Back

Why the Great American Contraction is leading to a crisis of demand and a re-imagining of the American Social Contract.

LAST UPDATED: April 17, 2026 at 3:58 PM

The Consumption Collapse - When the Feedback Loop Bites Back

GUEST POST from Art Inteligencia


The Ghost in the Shopping Mall

In our previous exploration, The Great American Contraction,” we identified a fundamental shift in the American story. For the first time in our history, the foundational assumption of “more” — more people, more labor, and more expansion — has been inverted. We discussed how the exponential rise of AI and robotics is dismantling the traditional value chain of human labor, moving us from a nation of “doers” to a necessary, albeit smaller, elite class of “architects.”

However, as we move closer to the two-year horizon of the next United States Presidential election, a more insidious shadow is beginning to fall across the landscape. It is no longer just a crisis of employment; it has evolved into a crisis of consumption. This is the “Feedback Loop of Irrelevance.”

The logic is as cold as the algorithms driving it: As increasing numbers of knowledge workers and service providers are displaced by autonomous agents, their disposable income evaporates. When people lose their financial footing, they spend less. When they spend less, the revenue of the very companies that automated them begins to shrink. To protect their margins in a declining market, these companies are forced to cut back even further — often doubling down on automation to reduce costs — which in turn removes more consumers from the marketplace.

We are witnessing the birth of a deflationary death spiral where corporate efficiency threatens to cannibalize the very markets it was designed to serve. Over the next 24 months, this cycle will redefine the American psyche and set the stage for an election year unlike any we have ever seen.

It is time to look beyond the immediate shock of job loss and examine the structural integrity of our economic operating system. If the “Old Equation” of labor-for-income is a sinking ship, we must decide what happens to the passengers before we reach the horizon of 2028.

The Vicious Cycle of Automated Austerity

The transition from a growth-based economy to a Great Contraction is not a linear event; it is a recursive loop. As AI adoption accelerates, we are witnessing a phenomenon I call “Automated Austerity.” This is the process where short-term corporate gains from labor reduction lead directly to long-term market erosion. The cycle progresses through four distinct, overlapping phases:

Phase 1: The First Wave Displacement

We are currently seeing the replacement of both low-skilled physical labor and high-skilled knowledge work by autonomous systems. This isn’t just about factory floors; it’s about the “Architect” roles we once thought were safe. As companies replace $150k-a-year analysts with $15-a-month compute tokens, the immediate impact is a massive surge in corporate profit margins.

Phase 2: The Wallet Effect

The friction begins here. Displaced workers initially rely on savings or severance, but as those dry up, the “gig economy” safety net is nowhere to be found — because AI is already performing the freelance writing, coding, and administrative tasks that used to provide a bridge. Disposable income doesn’t just dip; for a significant percentage of the population, it vanishes. This causes a sharp contraction in discretionary spending.

Phase 3: The Revenue Mirage

This is the trap. Companies that automated to save money suddenly find their top-line revenue shrinking because their customers (the former workers) can no longer afford their products. The efficiency gains are real, but the market size is artificial. We are entering a period where companies may be 100% efficient at producing goods that 0% of the displaced population can buy.

Phase 4: The Secondary Contraction

Faced with shrinking revenues, boards of directors demand even deeper cost-cutting to protect investor dividends. This leads to a second, more desperate wave of layoffs, further reducing the tax base and consumer spending power. This feedback loop creates a Deflationary Death Spiral that traditional monetary policy is ill-equipped to handle.

“When you automate the consumer out of a job, you eventually automate the business out of a customer.” — Braden Kelley

Over the next two years, this cycle will move from the periphery of Silicon Valley to the heart of every American household, forcing a radical re-evaluation of how we distribute the abundance that AI creates.

Vicious Cycle of Automated Austerity

The Two-Year Horizon: 2026–2028

As we navigate the next twenty-four months, the gap between traditional economic indicators and the lived reality of American citizens will become a canyon. We are entering a period of Economic Bifurcation, where the distance between those who own the “compute” and those who formerly provided the “labor” creates a new social stratification.

The Rise of the ‘Hollow’ Recovery

Expect to hear the term “efficiency-led growth” frequently in the coming months. Wall Street may remain buoyant as AI-integrated corporations report record-breaking margins per employee. However, this is a hollow success. While the stock market reflects corporate optimization, our Alternative Economic Health Measures—like the Genuine Progress Indicator (GPI) — will likely show a steep decline. We are becoming a nation that is technically “wealthier” while the average citizen’s ability to participate in that wealth is structurally dismantled.

The Shift from ‘Doer’ to ‘Architect’ Burnout

The “Great American Contraction” is not just about those losing roles; it is about the immense pressure on those who remain. The survivors — the Architect Class — are tasked with managing sprawling AI ecosystems. This creates a new kind of cognitive load. By 2027, I predict we will see a peak in “Technological Burnout,” where the speed of AI-driven change outpaces the human capacity to design for it. This is where Human-Centered Innovation becomes a survival skill rather than a corporate luxury.

The Mindset of Survivalist Innovation

As the feedback loop of shrinking revenue intensifies, we will see American citizens taking radical actions to decouple from a failing labor market. This includes:

  • Hyper-Localization: A resurgence in local bartering and community-based resource sharing as a hedge against the volatility of the automated economy.
  • The ‘Off-Grid’ Digital Economy: Individuals utilizing open-source AI models to create value outside of the traditional corporate gatekeepers, leading to a “shadow economy” of peer-to-peer services.
  • Consumption Sabotage: A psychological shift where citizens, feeling irrelevant to the economy, consciously reduce their consumption to the bare essentials, further accelerating the contraction.

This period will be defined by a search for meaning in a post-labor world. The American citizen of 2027 is no longer asking “How do I get ahead?” but rather “How do I remain relevant in a world that no longer requires my effort to function?”

The Survivalist Innovation Framework

Beyond GDP: New Vitals for a Contracting Economy

As the “Old Equation” fails, the metrics we use to measure national success are becoming dangerously obsolete. In a world where AI can drive productivity while simultaneously hollowing out the consumer class, GDP is no longer a compass; it is a rearview mirror. To navigate the next two years, we must shift our focus to alternative economic health measures that prioritize human vitality over transactional velocity.

1. The Genuine Progress Indicator (GPI)

Unlike GDP, which counts the “cost of cleaning up a disaster” as a positive, the GPI factors in income inequality and the social costs of underemployment. As we move toward 2028, we must demand a GPI-centered view of the economy. If AI-driven efficiency creates wealth but destroys the social capital of our communities, the GPI will show we are regressing, providing a much-needed reality check to “hollow” stock market gains.

2. The U-7 ‘Utility’ Rate

Standard unemployment figures (U-3) are increasingly irrelevant. We need a U-7 ‘Utility’ Rate to track those who are “technologically displaced”—individuals whose roles have been absorbed by algorithms or whose wages have been suppressed to the point of working poverty. This metric will highlight the Architect Gap: the growing number of people who have the capacity for high-value human contribution but lack access to the compute resources required to compete.

3. The Social Progress Index (SPI)

The goal of an automated economy should be to improve the human condition. The SPI measures outcomes that actually matter: Access to advanced education, personal freedom, and environmental quality. By 2027, the SPI will be the most honest indicator of whether the Great Contraction is a managed transition to a better life or a chaotic collapse of the middle class.

4. Value of Organizational Learning Technologies (VOLT)

We must begin measuring the “Agility Score” of our nation. VOLT measures how effectively we are using AI to solve complex problems rather than just replacing workers. A high VOLT score paired with a low SPI suggests we are building a “learning machine” that has forgotten its purpose: to serve the humans who created it.

“A high-GDP nation with a crashing Social Progress Index(SPI) is merely a failed state in a gold tuxedo.”

The political battleground of the next two years will be defined by a new set of metrics similar to these (but likely different). The 2028 election will not just be a choice between candidates, but a choice between maintaining the illusion of growth or designing a system of sovereignty for the American citizen.

The Localized Pivot

The Sovereign Tech-Stack & The Localized Pivot

As the “Feedback Loop of Irrelevance” continues to shrink traditional income, we are witnessing a radical grassroots response: The Localized Pivot. When the macro-economy fails to provide value to the individual, the individual stops providing value to the macro-economy and turns inward to their community.

The Rise of the ‘Personal AI’ Infrastructure

By 2027, the barrier to entry for sophisticated production will vanish. We will see a surge in “Sovereign Tech-Stacks” — individuals and small collectives using localized, open-source AI models to run micro-manufactories, automated vertical farms, and peer-to-peer service networks. This is Innovation as a Survival Tactic. These citizens are essentially “unplugging” from the hollowed-out corporate ecosystem and creating a shadow economy that traditional GDP cannot track.

From Global Chains to Hyper-Local Resilience

The contraction of consumer spending will lead to the death of the “long supply chain” for many goods. In its place, we will see the rise of Regional Circular Economies. AI will be used not to maximize global profit, but to optimize local resource sharing. Imagine community AI agents that manage local energy grids or coordinate the bartering of skills — human-centered design at its most fundamental level.

The ‘Architect’ of the Commons

In this phase, the “Architect” role I’ve discussed previously becomes a civic one. These are the individuals who design the systems that keep their communities thriving while the national revenue shrinks. They are the ones building the Human-Centered Guardrails that ensure technology serves the neighborhood, not the shareholder. This shift represents a move from Global Consumerism to Local Sovereignty.

“When the national economic engine stops fueling the household, the household must build its own engine, or it dies.” — Braden Kelley

This localized movement will be the wild card of 2028. It creates a class of “Un-Architected” citizens who are no longer dependent on the federal government or major corporations, creating a profound tension for any political candidate trying to promise a return to the ‘Old Equation’.

The Road to 2028: The Politics of Human Relevance

As we approach the next Presidential election, the political discourse will undergo a seismic shift. The traditional “Left vs. Right” battle lines over tax rates and social issues will be superseded by a more existential debate: The Individual vs. The Algorithm. The 2028 election will likely be the first in history centered entirely on the consequences of a post-labor economy.

The ‘Humanity First’ Tax and Sovereign Solvency

The most contentious issue will be how to fund a shrinking state as the labor-based tax system collapses. We will see the rise of the “Compute Tax” — a proposal to tax AI tokens and robotic output rather than human hours. This isn’t just about revenue; it’s about sovereign solvency. When companies reinvest profits into compute rather than wages, the “Economic OS” crashes. Expect candidates to run on a platform of Universal Basic Everything (UBE) — providing the results of automation (healthcare, housing, and energy) directly to the people as the tax base from labor vanishes.

The Compute Tax

The Death of Traditional Immigration Debates

As I noted in our initial look at the Contraction, the old argument about immigrants “taking jobs” or “filling gaps” is dead. In 2028, the focus will shift to “Strategic Talent Acquisition.” The debate will center on how to attract the world’s few remaining irreplaceable “Architect” minds while managing a domestic population that is increasingly surplus to the needs of capital. This will create a strange political alliance between protectionists and humanists, both seeking to shield human value from digital devaluation.

Mindset and Likely Actions of the Citizenry

By the time voters head to the polls, the American mindset will have shifted from aspiration to preservation. We are likely to see:

  • The Rise of ‘Neo-Luddite’ Activism: Not a rejection of technology, but a demand for “Human-Centered Guardrails” that prevent AI from cannibalizing the last remaining sectors of human connection.
  • The Search for Non-Monetary Meaning: A surge in candidates who focus on “Quality of Life” metrics rather than fiscal growth, appealing to a class of people who no longer derive their identity from their “job.”
  • Algorithmic Populism: Politicians using AI to personalize fear and hope at scale, creating a feedback loop where the technology used to displace the worker is also used to win their vote.

The central question of the 2028 election will be simple but devastating: “What is a country for, if not to support the thriving of its people — even when those people are no longer ‘productive’ in a traditional sense?” The winner will be the one who can design a new social contract for a smaller, more resilient, and truly innovative nation.

Conclusion: Designing a Thrivable Contraction

The Great American Contraction is no longer a theoretical “what-if” for futurists to debate; it is an active restructuring of our reality. As the feedback loop of automated austerity begins to bite, we are discovering that a country built on the relentless pursuit of “more” is fundamentally ill-equipped to handle the arrival of “enough.”

The next two years will be a period of intense friction as our legacy systems — our tax codes, our education models, and our social safety nets — grind against the frictionless efficiency of the AI era. We will see traditional economic metrics fail to capture the quiet struggle of the consumer, and we will watch as the 2028 election turns into a referendum on the value of a human being in a post-labor world.

But contraction does not have to mean collapse. If we shift our focus from transactional velocity to human vitality, we have the opportunity to design a new version of the American Dream. This new dream isn’t about the quantity of jobs we can protect from the machines, but the quality of the lives we can build with the abundance those machines create. It is about moving from a nation of “doers” who are exhausted by the grind to a nation of “architects” who are inspired by the possible.

“The goal of innovation was never to replace the human; it was to release the human. We are finally being forced to decide what we want to be released to do.” — Braden Kelley

The road to 2028 will be defined by whether we choose to cling to the wreckage of the growth-based model or whether we have the courage to embrace a smaller, smarter, and more human-centered future. The contraction is inevitable, but the outcome is ours to design.

STAY TUNED: On Tuesday my friend Braden Kelley (with a little help from me) is publishing an article featuring one hypothesis for what an AI SOFT LANDING might look like.

Image credits: Google Gemini

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Entrepreneurial Efforts Must Fit with the Brand

Entrepreneurial Efforts Must Fit with the Brand

GUEST POST from Mike Shipulski

To meet ever-increasing growth objectives, established companies want to be more entrepreneurial. And the thinking goes like this – launch new products and services to create new markets, do it quickly and do it on a shoestring. Do that Lean Startup thing. Build minimum viable prototypes (MVPs), show them to customers, incorporate their feedback, make new MVPs, show them again, and then thoselaunch.

For software products, that may work well, largely because it takes little time to create MVPs, customers can try the products without meeting face-to-face and updating the code doesn’t take all that long. But for products and services that require new hardware, actual hardware, it’s a different story. New hardware takes a long time to invent, a long time to convert into an MVP, a long time to show customers and a long time to incorporate feedback. Creating new hardware and launching quickly in an entrepreneurial way don’t belong in the same sentence, unless there’s no new hardware.

For hardware, don’t think smartphones, think autonomous cars. And how’s that going for Google and the other software companies? As it turns out, it seems that designing hardware and software are different. Yes, there’s a whole lot of software in there, but there’s also a whole lot of new sensor systems (hardware). And, what complicates things further is that it’s all packed into an integrated system of subsystems where the hardware and software must cooperate to make the good things happen. And, when the consequences of a failure are severe, it’s more important to work out the bugs.

And that’s the rub with entrepreneurship and an established brand. For quick adoption, there’s strong desire to leverage the established brand – GM, Ford, BMW – but the output of the entrepreneurial work (new product or service) has to fit with the brand. GM can’t launch something that’s half-baked with the promise to fix it later. Ford can come out with a new app that is clunky and communicates intermittently with their hardware (cars) because it will reflect poorly on all their products. In short, they’ll sell fewer cars. And BMW can’t come out with an entrepreneurial all-electric car that handles poorly and is slow off the start. If they do, they’ll sell fewer cars. If you’re an established company with an established brand, the output of your entrepreneurial work must fit with the established brand.

If you’re a software startup, launch it when it’s half-baked and fix it later, as long as no one will die when it flakes out. And because it’s software, iterate early and often. And, there’s no need to worry about what it will do to the brand, because you haven’t created it yet. But if you’re a hardware startup, be careful not to launch before it’s ready because you won’t be able to move quickly and you’ll be stuck with your entrepreneurial work for longer than you want. Maybe, even long enough to sink the brand before it ever learned to swim. Developing hardware is slow. And developing robust hardware-software systems is far slower.

If you’re an established company with an established brand, tread lightly with that Lean Startup thing, even when it’s just software. An entrepreneurial software product that works poorly can take down the brand, if, of course, your brand stands for robust, predictable, value and safety. And if the entrepreneurial product relies on new hardware, be doubly careful. If it goes belly-up, it will be slow to go away and will put a lot of pressure on that wonderful brand you took so long to build.

If you’re an established brand, it may be best to buy your entrepreneurial products and services from the startups that took the risk and made it happen. That way you can buy their successful track record and stand it on the shoulders of your hard-won brand.

Image credit: Slashgear.com

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