Category Archives: Design

How to Design a Horrible, Terrible, No Good, Very Bad User Experience

How to Design a Horrible, Terrible, No Good, Very Bad User Experience

GUEST POST from Geoffrey A. Moore


Some of you may know that early in my career I taught English at the college level. The freshman writing requirement was always a challenge as textbook publishers struggled valiantly to find some reading material that would actually help students write better. One of their best efforts was an essay titled “How to Write an F Paper.” It turns out we learn better from failure than from success—who knew?

With that thought in mind, and taking liberties with the title of one of my favorite children’s books, I want to review an actual user experience delivered to me by the manufacturer of a luxury automobile. The vehicle itself performs admirably, so kudos to the product engineers. It is the customer experience team that needs to be taken to the woodshed.

Here’s how the experience starts. I get in my car, start it, and back out of my garage, benefiting as always from the rear camera system. The system stays on when I shift into drive until I get onto the road and have gone perhaps fifty yards. At that point, the multimedia display presents the following:

An update is ready for installation on your multimedia system. The following conditions must be agreed to before installation.
(READ NOW) (LATER)

Well, I am driving the car, so I don’t think READ NOW is a very good option. I hit LATER, the screen returns to normal, and I get on with my day. To tell the truth, I forget about the whole experience until the next day when, after backing out of my garage and getting onto the road, I get a replay of the same message. Astoundingly, I am driving my car again, so again I push LATER.

Now, as my spouse will testify, sometimes I am a slow learner, so it is not until the better part of a week has passed that I realize the only time I am going to get this message is the first time I start the car in the morning and have driven around fifty yards. At this point, I decide to pull over and push READ. Here is what I got in reply:

Software update for your infotainment system — In order to read the terms and conditions, please park the vehicle safely, switch off the ignition and apply the parking brake.

Well, as it turns out, the reason I got in my car and drove that first fifty yards is that I actually have someplace I need to get to on time, so the idea of switching off the ignition does not appeal. I go back, push the LATER button (feeling a bit like Neo in the Matrix at this point), sub-vocalize a few choice words for the vendor, and carry on with my day.

I won’t testify as to how many days after I had the same introductory message appear and pushed LATER because you guessed it, I actually had somewhere to go and wanted to arrive there on time. But, one day I had the opportunity to be parking somewhere for a good while, so that day I did not push either button until I got to the lot. (“You can fool some of the people all the time, and all of the people some of the time, but you cannot fool all the people all the time.”) Once parked, I did switch off my ignition and applied the parking brake, and was rewarded with the following messages.

Software update for your installation system

Notes
The installation process requires several minutes and cannot be canceled or closed. Individual functions and buttons in the vehicle are not available for use during the installation or their use is limited. The multimedia display does not support display messages.

In the unlikely event of a technical error during installation, functional restrictions of the multimedia system and the above-mentioned functions may persist and make it necessary to consult a workshop.

This is what happens when you let the legal team review the customer communications text. Fresh from their latest efforts with the Safe Harbor statement from the prior quarter’s earnings call, they are fiercely protecting their enterprise from any and every liability risk. Heartwarming as these words were, they actually felt they were not protection enough because they were followed by:

Warnings

During installation of this update, the multimedia system is not available. In particular, this includes systems such as the navigation system, phone, reversing camera, 360 camera, Active Parking Assist, Remote Parking Assist, PARKTRONIC, and the switch for DYNAMIC SELECT.

There is an increased risk of accident.

Installing the update while operating the vehicle may distract you from the traffic situation.

There is an increased risk of accident.

Carry out the installation

And yes, that last line is a call to action, clearly meant to benefit from the wave of inspiration created by the earlier sentences. My only surprise was that it did not append the phrase “at your own risk.”

Now, to be fair, I did carry out the installation, and it took about seven minutes or so, and it was fine. So again, the product engineers know what they are doing. But where in the name of all that is holy is the customer experience engineering? Who in their right mind would ever want their customers—and remember this is a luxury vehicle with some pretty high-end customers—to go through such an experience? And most importantly, what are the takeaways that will keep us from going down the same path?

Here are three that come to mind:

  1. Design the experience. Work backward from the end in mind, making sure each element is contributing to the desired outcome.
  2. Test the experience. Make this a real-world test, not a lab test. Recruit vehicle owners to participate. Capture their feedback.
  3. Eliminate friction. All hygiene processes entail some amount of friction. In such situations, your job is not to delight your customers here but rather to avoid annoying them. Do so by respecting their time.

In this case, what if the car company had sent me an email first? That could have included all their liability stuff. It also could coach me on when and how to best install the update. Once I replied I had read the stuff, then they could have sent a much simpler message over the multimedia system, or maybe just triggered the download on my behalf when my car was safely in my garage. The point is, there was clearly a better way, and just as clearly, nobody at the car company cared enough to advocate for it.

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

Image Credit: Pexels, Geoffrey Moore

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Why Zero UI Will Redefine Experience Design

The Invisible Interface

LAST UPDATED: May 2, 2026 at 9:13 AM

Why Zero UI Will Redefine Experience Design

GUEST POST from Art Inteligencia


I. Introduction: The End of the Glass Slab

The Screen Fatigue Phenomenon: We have reached a point of peak saturation with traditional displays. Our lives are currently mediated by glowing rectangles, leading to a fragmented human experience where the tool often overshadows the task.

Defining Zero UI: This is not the absence of an interface, but the disappearance of the user interface as we know it. It represents a move away from rigid, button-heavy menus toward more organic inputs like voice, haptics, computer vision, and ambient intelligence.

The Core Thesis: Technology is at its most powerful when it is invisible. By removing the friction between human intent and technological execution, we allow people to return their focus to the experience itself, rather than the device required to facilitate it.

II. The Sensory Stack: How Zero UI Works

Voice & Natural Language: We are witnessing a transition from the “Command-Line Interface” era of voice (where specific keywords were required) to fluid, contextual conversations. The goal is a system that understands nuance, sarcasm, and intent, mirroring human-to-human interaction.

Biometrics & Gesture Control: In a Zero UI world, the body becomes the input device. Through computer vision and skeletal tracking, technology can interpret a wave of a hand or a shift in gaze, allowing for spatial computing that feels like an extension of natural movement.

Proactive vs. Reactive Design: Traditional UI waits for a user to click; Zero UI anticipates. By leveraging machine learning and sensor data, systems can predict needs—adjusting the lighting when you enter a room or preparing a summary of a meeting before you even ask for it.

Haptics & Sensory Feedback: Communication doesn’t always need to be audible or visual. Subtle vibrations (haptics) or environmental changes (thermal or olfactory cues) can provide “glanceable” information without demanding the user’s full cognitive attention.

III. From UX to HX (Human Experience)

Designing for Context: In the era of Zero UI, the focus shifts from “clicks” to “intent.” Experience design no longer lives within the boundaries of a screen; it must account for a user’s physical location, environmental noise levels, and even social setting. We aren’t just designing a path to a button; we are designing a response to a human moment.

Reducing Cognitive Load: The “Invisible Assistant” model moves us away from app management and toward outcome management. By utilizing ambient intelligence, technology handles the “how” so humans can focus on the “why.” This creates a “Calm UI” effect, where digital interactions support our life goals without demanding constant visual attention.

The Ethics of Invisibility: As interfaces disappear, the “Black Box” problem grows. Designers must prioritize radical transparency—ensuring users understand when and how they are being sensed. Trust becomes the primary currency; without clear consent and “off-switches” for predictive features, invisible interfaces risk becoming intrusive rather than helpful.

From Screens to Systems: We are moving toward “Sentient Interfaces” that detect hesitation or frustration through behavioral cues. Transitioning to HX (Human Experience) means building ecosystems that are emotionally aware, neuro-inclusive, and capable of failing gracefully when the AI misinterprets human intent.

IV. Leading Innovators: The Architects of Invisibility

The transition to Zero UI is being led by a diverse ecosystem of startups and legacy tech giants. As of 2026, the following organizations are moving beyond the screen to define the future of human-centered interaction:

Company / Startup Core Focus Why They Matter Now
Neuralink Brain-Computer Interface (BCI) Entering high-volume production in 2026, Neuralink is moving BCI from clinical trials to the ultimate seamless interface: thought-based control.
Ultraleap Mid-air Haptics & Tracking By projecting ultrasound waves onto the skin, they provide tactile feedback in mid-air, crucial for non-visual “touch” in automotive and XR environments.
SoundHound AI Agentic Voice Commerce Their latest “Amelia 7” platform allows users to manage complex real-world transactions—like dinner reservations and parking—entirely through natural conversation.
Memories.ai Contextual Wearables (LUCI) Following the pivot of early wearables like the Humane Ai Pin, Memories.ai is building the “Android of AI wearables,” providing a system-level reference for ambient intelligence.
Synchron Endovascular BCI A key competitor to Neuralink, Synchron focuses on minimally invasive brain interfaces that allow users to control digital devices via the blood vessels, emphasizing safety and accessibility.

Strategic Implementation: For brands, the challenge is no longer just “building an app.” It is about integrating into these emerging ecosystems. Whether it is through voice agents or haptic-enabled environments, the goal for designers is to ensure their brand’s presence is felt and heard, even when it cannot be seen.

V. The Futurologist’s Perspective: What’s Next?

The Transition to “Liquid Services”: In 2026, we are moving away from the “static app” model. Instead, we are entering the era of liquid services—capabilities that flow seamlessly across devices. Your interaction might start as a voice command in the kitchen, continue as a haptic pulse on your wrist while walking, and conclude as a spatial projection in your vehicle. The interface is no longer a destination; it is a persistent, supportive presence.

Hyper-Personalization and Ambient Intelligence: One-size-fits-all design is dead. Leveraging what I call “Fortified Intelligence,” future systems will adapt in real-time to the individual’s neurodiversity, physical abilities, and current emotional state. Environments will become “sentient,” adjusting lighting, acoustics, and information density based on the user’s “Digital Persona” without a single manual adjustment.

The Challenge for Designers: Behavioral Architecture: The role of the designer is shifting from visual storytelling to behavioral and sensory architecture. We are no longer just drawing screens; we are defining the “rules of engagement” between humans and machines. This requires a Whole-Brain approach—part scientist to manage the data and part artist to inspire human connection. Success in this new landscape is measured by “Speed to Resilience” rather than just speed to market.

Reclaiming the Human Moment: Paradoxically, the more advanced our technology becomes, the more we value “human friction.” As Zero UI automates the logistical “drudge work” of life, experience design for the future will emphasize the things AI cannot replicate: intentional inefficiency, the warmth of human presence, and the physical tangibility of the world around us. We are designing technology to get it out of the way, so we can finally be human again.

VI. Conclusion: Reclaiming the Human Moment

Beyond Efficiency: As I often say, true innovation isn’t just about making things faster or cheaper—it’s about making things more human. Zero UI is the final step in removing the technical debt of the 21st century. By dissolving the “glass slab” that separates us from our tasks, we aren’t just improving efficiency; we are restoring presence. When the technology disappears, we are finally free to focus on the work that matters and the people who inspire us.

A Call for Design Integrity: As we look toward the 2030s, the “Wild West” era of digital interfaces is closing. We are entering an era of Structural Integrity in experience design. Designers and innovation leaders must move beyond “Process Theater”—workshops that generate ideas without outcomes—and start building the resilient, invisible infrastructure that supports a flourishing society. We must have the courage to design a future that doesn’t require us to retreat into the friction of the past.

Final Thought: The most disruptive interface is the one that doesn’t exist because it works so well you’ve forgotten it’s there. The goal of the Invisible Interface is not to automate the human out of the loop, but to close the loop on friction, leaving only the experience behind. Let’s design an infrastructure that doesn’t just survive the future, but defines it.

Are you ready to move from UX to HX?

If you’re looking to get to the future first, increase your speed of innovation, or create a culture of continuous transformation, connect with Braden Kelley for a keynote or a FutureHacking™ workshop to teach you to be your own futurist.

Frequently Asked Questions

What is the difference between Zero UI and traditional UI?

Traditional UI (User Interface) relies on visual elements like screens, buttons, and menus to facilitate interaction. Zero UI moves away from these “glass slabs,” instead utilizing natural human behaviors—such as voice, gestures, haptics, and ambient intelligence—to interact with technology without a physical screen as the primary mediator.

How does Zero UI improve the Human Experience (HX)?

By reducing cognitive load and removing the friction of navigating complex menus, Zero UI allows technology to become a proactive assistant rather than a reactive tool. This shift toward “Human Experience” prioritizes context and intent, allowing users to stay present in their physical environment while still benefiting from digital capabilities.

Is Zero UI secure and private?

As interfaces become invisible, transparency becomes the most critical design element. Leading innovators are focusing on “Privacy by Design,” ensuring that ambient sensing and voice processing are handled with clear consent and robust encryption, often processing data locally (on-edge) rather than in the cloud to maintain user trust.

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: Gemini

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

A Tiny Bit of Uninterrupted Work Goes a Long Way

A Tiny Bit of Uninterrupted Work Goes a Long Way

GUEST POST from Mike Shipulski

If your day doesn’t start with a list of things you want to get done, there’s little chance you’ll get them done. What if you spent thirty minutes to define what you want to get done and then spent an hour getting them done? In ninety minutes you’ll have made a significant dent in the most important work. It doesn’t sound like a big deal, but it’s bigger than big. Question: How often do you work for thirty minutes without interruptions?

Switching costs are high, but we don’t behave that way. Once interrupted, what if it takes ten minutes to get back into the groove? What if it takes fifteen minutes? What if you’re interrupted every ten or fifteen minutes? Question: What if the minimum time block to do real thinking is thirty minutes of uninterrupted time?

Let’s assume for your average week you carve out sixty minutes of uninterrupted time each day to do meaningful work, then, doing as I propose – spending thirty minutes planning and sixty minutes doing something meaningful every day – increases your meaningful work by 50%. Not bad. And if for your average week you currently spend thirty contiguous minutes each day doing deep work, the proposed ninety-minute arrangement increases your meaningful work by 200%. A big deal. And if you only work for thirty minutes three out of five days, the ninety-minute arrangement increases your meaningful work by 400%. A night and day difference.

Question: How many times per week do you spend thirty minutes of uninterrupted time working on the most important things? How would things change if every day you spent thirty minutes planning and sixty minutes doing the most important work?

Great idea, but with today’s business culture there’s no way to block out ninety minutes of uninterrupted time. To that I say, before going to work, plan for thirty minutes at home. And set up a sixty-minute recurring meeting with yourself first thing every morning and do sixty minutes of uninterrupted work. And if you can’t sit at your desk without being interrupted, hold the sixty-minute meeting with yourself in a location where you won’t be interrupted. And, to make up for the thirty minutes you spent planning at home, leave thirty minutes early.

No way. Can’t do it. Won’t work.

It will work. Here’s why. Over the course of a month, you’ll have done at least 50% more real work than everyone else. And, because your work time is uninterrupted, the quality of your work will be better than everyone else’s. And, because you spend time planning, you will work on the most important things. More deep work, higher quality working conditions, and regular planning. You can’t beat that, even if it’s only sixty to ninety minutes per day.

The math works because in our normal working mode, we don’t spend much time working in an uninterrupted way. Do the math for yourself. Sum the number of minutes per week you spend working at least thirty minutes at time. And whatever the number, figure out a way to increase the minutes by 50%. A small number of minutes will make a big difference.

Image credit: Pexels

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Designing Work for Humans and AI Agents to Do Together

LAST UPDATED: April 29, 2026 at 6:28 PM

Designing Work for Humans and AI Agents to Do Together

by Braden Kelley and Art Inteligencia


The Work Design Gap

We are not struggling to build artificial intelligence. We are struggling to design work for it.

Across industries, organizations are layering AI onto workflows that were never meant for collaboration. The result is predictable: inefficiency, mistrust, and unrealized value.

The real divide is not human versus AI. It is between work that is intentionally designed for collaboration and work that is not.

Why Traditional Tools Fail Us

Most of our management tools were built for a different era.

  • Process maps assume predictability
  • Org charts assume static roles
  • RACI models assume clear ownership

But human and AI collaboration is dynamic, contextual, and continuously learning. These tools help us optimize yesterday’s work, not design tomorrow’s.

What we need is a new visual language for collaboration.

Introducing the Human–AI Collaboration Canvas

The infographic below is not just a diagram. It is a thinking tool.

Its purpose is to make invisible interactions visible, clarify roles without over-constraining them, and embed judgment, trust, and learning into how work gets done.

This is a shift from process design to system design for collaboration.

Designing Work for Humans and AI Infographic

The Three-Lane Model: A More Honest Representation of Work

The canvas is built around three interconnected lanes:

The Human Lane

Where judgment, empathy, ethics, and accountability live. Humans frame the problem, not just solve it.

The AI Agent Lane

Where scale, speed, pattern recognition, and automation operate. AI expands what is possible.

The “Together” Lane

This is where value is actually created. Co-creation, co-decision, and co-learning happen here.

If you are not explicitly designing the middle lane, you are leaving value on the table.

The Work Journey: Sense → Decide → Act → Learn

Instead of rigid workflows, the canvas maps work as an adaptive cycle:

  • Sense: Understand context and gather signals
  • Decide: Blend human reasoning with AI recommendations
  • Act: Execute with scale and oversight
  • Learn: Reflect, adapt, and improve

Learning is not the end of the process. It feeds everything.

Collaboration Nodes: Where the Magic (or Failure) Happens

At key points in the journey are collaboration nodes—the moments where humans and AI interact.

Each node forces three critical questions:

  • Who leads?
  • What is the role of the other?
  • What is at stake?

Most AI failures are not technical failures. They are interaction design failures.

Making Judgment Visible

One of the biggest risks in AI adoption is invisible decision-making.

The canvas highlights:

  • Where human judgment is required
  • Where AI recommendations are sufficient
  • Where escalation is necessary

Automation without explicit judgment design is just risk at scale.

Designing for Trust, Not Just Performance

Capability alone is not enough. Systems must be trusted to be used effectively.

This requires:

  • Transparency
  • Explainability
  • Auditability

The real question is not “Can the AI do this?” but “Will humans trust and use this appropriately?”

Learning Loops: The System That Gets Smarter

The canvas includes two reinforcing learning loops:

  • AI Learning Loop: Data → Model → Output → Feedback → Improvement
  • Human Learning Loop: Experience → Reflection → Insight → Better decisions

The real competitive advantage is not AI itself. It is how quickly your combined system learns.

Risk, Ethics, and Failure by Design

No system is perfect. The best systems are designed with failure in mind.

The canvas highlights:

  • Bias and fairness
  • Privacy and security
  • Safety and compliance

It also asks essential questions:

  • What happens if the AI is wrong?
  • What happens if the human is wrong?
  • How do we recover?

Resilience comes from designing for breakdowns, not ignoring them.

Human-AI Agent Work Collaboration Canvas

How to Use This Canvas

This is a practical tool, not a theoretical one.

  • Use it in workshops to map collaboration
  • Audit existing workflows
  • Design new human–AI systems from scratch

A simple place to start:

  1. Map one critical workflow
  2. Identify collaboration nodes
  3. Redesign the “together” lane first

Designing for a More Human Future

AI does not reduce the need for humans. It raises the bar for how we design work.

The goal is not efficiency alone. The goal is better decisions, better experiences, and better outcomes.

The organizations that win will not be the ones with the most AI. They will be the ones who best design how humans and AI work together.

EDITOR’S NOTE: You should read this article too to learn more about atomizing work for man and machine to do together.

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

Image credits: Google Gemini, ChatGPT

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

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

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Aesthetics – Part One

Aesthetics - Part One

GUEST POST from Geoffrey A. Moore

The Infinite Staircase offers readers a metaphysics and an ethics shaped by the 21st century’s understanding of how the world came to be. It has little to say, however about esthetics, and that is too large a part of human experience to neglect. With that in mind, I am going to address the topic in two short essays.

The first essay, the one you have in hand, is an interaction with The Cambridge Dictionary of Philosophy’s entry on the topic. I found myself constantly quarreling with it, and I wanted to sort out why, hence this piece. What I see now is that I was clearing a space to dig deeper into the issues I truly care about. That’s what the second essay is intended to do.

Of course, this begs the question, do you even need to read this essay? I mean, just because I have to clear my throat before I speak doesn’t mean you have to listen to it. That said, if you are academically oriented, or have ever taken courses in philosophy, I suggest you do read this if only to clarify your own point of view. If, on the other hand, you are simply interested in the nature of the esthetic experience itself, feel free to ignore this piece, but do keep an eye out for the next essay.

Essay #1: A Dialog with Cambridge

NOTE: The format of the dialog is to present the Cambridge material in blockquote format and my responses to it in normal text.

Aesthetics: the branch of philosophy that examines the nature of art and the character of our experience of art and of the natural environment.

The purpose of esthetics, as of any academic discipline, is to investigate a body of forces in order to better understand its nature and determine how best to incorporate it into our strategies for living. In the case of esthetics, the forces under study create psychological experiences, and it is these experiences that provide the data upon which the discipline is based.

Because the concept of experience is central to the understanding of esthetics, we need to get clear about its meaning. In particular, we need to distinguish between two common understandings of the term, one of which is central, the other of which is tangential to our purposes.

Here are the two definitions, taken from the Oxford English Dictionary:

  1. The actual observation of facts or events considered as a source of knowledge.
  2. The fact of being consciously the subject of a state or condition, or of being consciously affected by an event.

Definition 2 is the one that is central to our purpose. We are interested in the impact of an object on a subject, what it is like to be “consciously affected,” something that depends very much on the properties of both the subject and the object. We investigate this experience first by examining the residue of its impact on the subject and then by seeking attributes in the object that account for it.

This is where Definition 1 comes in. It is a tactic we use in pursuing a better understanding of what is happening under Definition 2. But we need to be careful here as we cannot objectively observe the facts in question—they are inherently subjective and can only be contemplated internally or reported externally. That means there can be no purely objective basis for esthetics. We must keep both subject and object in view at all times, focusing specifically on what is happening when we are being internally affected by an externally occasioned event.

It emerged as a separate field of philosophical inquiry during the eighteenth century in England and on the Continent. Recognition of aesthetics as a separate branch of philosophy coincided with the development of theories of art that grouped together painting, poetry, sculpture, music, and dance (and often landscape gardening) as the same kind of thing, les beaux arts, or the fine arts.

The fine arts are indeed all within the scope of esthetics. As a group, however, they are highly refined. Their force tends to be more ethereal than many people can experience, particularly modern audiences that are more global and less privileged than the eighteenth century thinkers who created the concept initially. As a result, we should not position the fine arts as the centerpoint of our category but rather at one end of a more inclusive spectrum, albeit one we have as yet to define.

Baumgarten coined the term ‘aesthetics’ in his Reflections on Poetry (1735) as the name for one of the two branches of the study of knowledge, i.e. for the study of sensory experience coupled with feeling, which he argued provided a different type of knowledge from the distinct, abstract ideas studied by “logic.” He derived it from the ancient Greek aisthanomai (to perceive), and “the aesthetic” has always been intimately connected with sensory experience and the kinds of feelings it arouses.

“Sensory experience coupled with feeling” is as good a starting point as any for capturing the full spectrum of aesthetic experience. It is still too general, as there are many such experiences that are not aesthetic, but it gives us a point of departure. The challenge is that when we try to convert any such experience into knowledge, of necessity we must express ourselves in language, and this can be confusing because the experience itself is pre-linguistic.

That is, to use the framework of The Infinite Staircase, sensory experience coupled with feeling takes place on the stairs of desire, consciousness, values, and culture—all prior to the stairs of language, narrative, analytics, and theory. When we use these higher stairs to explain what is happening on the lower ones, we are prone to imposing their structure in ways that ride roughshod over the subtleties of the actual experience. This is reflected throughout the list of questions that follow.

Questions specific to the field of esthetics are: Is there a special attitude, the aesthetic attitude, which we should take toward works of art and the natural environment, and what is it like?

The answer is no. This is an example of analytics seeking to reposition experiences that arise from below by proposing that they descend from above. That is, the refined analytical intellect is positioning itself at the center of an experience during which it was not even present. This is a big mistake, one that implies aesthetic experiences are reserved for the few who possess refined sensibilities when in fact they are universal.

Is there a distinctive type of experience, an aesthetic experience, and what is it?

The answer is yes, and in the lexicon of philosophy, it falls into the category of qualia. The entry on qualia from Wikipedia provides a useful introduction, defining it as subjective conscious experiences, examples of which include the perceived sensation of pain of a headache, the taste of wine, and the redness of an evening sky. As qualitative characteristics of sensation, qualia stand in contrast to propositional attitudes, where the focus is on beliefs about experience rather than what it is directly like to be experiencing.

Now, to be fair, pain does not qualify as an aesthetic experience, but the taste of wine and the color of red certainly do. The key point is that all the examples stand in contrast to propositional attitudes, the domain of analytics, which can be about aesthetic experience but not integral to it.

Is there a special object of attention that we can call the aesthetic object?

Yes, there is. It is whatever body of forces that are creating the impact on the subject, be that the wine, the evening sky, a painting, a story, or a piece of wood. But the object alone cannot be said to be inherently aesthetic. Only after it has evoked a sensory experience coupled with feeling can it be so termed, and then only with respect to subjects in whom that experience has been evoked.

Finally, is there a distinctive value, aesthetic value, comparable with moral, epistemic, and religious values?

Yes, there is. To put things in perspective

  • Moral value consists of behavior that is beneficial to others and consistent with social norms.
  • Epistemic value consists of justified true beliefs that lead to effective action in the world.
  • Religious value consists of spiritual experiences and commitments that provide sacred and undeniable guidelines for life in the world.

In such a context, aesthetic value consists of pleasurable, contemplative, non-utilitarian, resonating experiences that we characterize as beautiful, refreshing, and inspiring.

Some questions overlap with those in the philosophy of art, such as those concerning the nature of beauty, and whether there is a faculty of taste that is exercised in judging the aesthetic character and value of natural objects or works of art.

The nature of beauty is indeed an elusive topic, one where we need to be humble, but with respect to the faculty of taste, we can be more assertive. In the eighteenth century, judgments of taste were appropriated by a social class that privileged refinement and intellect over sensibility and joy. In the nineteenth century, the Romantic movement aggressively worked to overthrow and reverse this polarity, and in the twentieth, cultural relativism worked to deny the validity of any aesthetic judgments that extended beyond the personal preferences of the person making them within the norms of the culture they are inhabiting. All three positions contain an element of truth, and none by itself does a good job of accounting for the overall nature of beauty. The good news is that they are not incompatible with one another, so a synthesis of all three can potentially provide a stable foundation for esthetic theory.

Aesthetics also encompasses the philosophy of art. The most central issue in the philosophy of art has been how to define ‘art’. Not all cultures have, or have had, a concept of art that coincides with the one that emerged in Western Europe during the seventeenth and eighteenth centuries. What justifies our applying our concept to the things people in these other cultures have produced?

It is justifiable to apply our concepts to our experience of things other cultures have produced and how they stack up against our cultural norms. We just should not apply them to their experiences or the status of the things in their culture. The temptation to do so derives from seeking to locate the aesthetic force solely in the object. That is not a tenable claim.

There are also many pictures (including paintings), songs, buildings, and bits of writing that are not art. What distinguishes those pictures, musical works, etc., that are art from those that are not?

They do not evoke the pleasurable, contemplative, non-utilitarian, resonating experiences we call beautiful, refreshing, and inspiring.

Various answers have been proposed that identify the distinguishing features of art in terms of form, expressiveness, intentions of the maker, and social roles or uses of the object.

None of these topics is off limits, but each one can take us down a rabbit hole if we try to use it as definitive of what constitutes art. That begs the question of how we would define art, but we will leave that to the second essay.

Since the eighteenth century, there have been debates about what kinds of things count as “art.” Some have argued that architecture and ceramics are not art because their functions are primarily utilitarian, and novels were for a long time not listed among the “fine arts” because they are not embodied in a sensuous medium. Debates continue to arise over new media and what may be new art forms, such as film, video, photography, performance art, found art, furniture, posters, earthworks, and computer and electronic art. Sculptures these days may be made out of dirt, feces, or various discarded and mass-produced objects, rather than marble or bronze. There is often an explicit rejection of craft and technique by twentieth-century artists, and the subject matter has expanded to include the banal and everyday, and not merely mythological, historical, and religious subjects as in years past. All of these developments raise questions about the relevance of the category of “fine” or “high” art.

When discussing esthetics in general, over-rotating to fine or high art is simply a mistake. It is a valid subcategory, but not to the exclusion of other sensory experiences coupled with esthetic feelings. Once again, we see the analytical intellect overstepping its bounds, seeking to impose itself as an arbiter of aesthetic value when its proper role is to be an interpreter of aesthetic experience.

Another set of issues in philosophy of art concerns how artworks are to be interpreted, appreciated, and understood. Some views emphasize that artworks are products of individual efforts, so that a work should be understood in light of the producer’s knowledge, skill, and intentions. Others see the meaning of a work as established by social conventions and practices of the artist’s own time, but which may not be known or understood by the producer. Still, others see meaning as established by the practices of the users, even if they were not in effect when the work was produced. Are there objective criteria or standards for evaluating individual artworks?

All these views are legitimate in their own right, provided we surface the context in which the judgment is made. What is not legitimate is to overrule a rival approach, asserting one’s own as the only valid one. Overall, the goal is to get as much insight as possible into the body of forces at work in an esthetic experience, any way we can.

There has been much disagreement over whether value judgments have universal validity, or whether there can be no disputing about taste if value judgments are relative to the tastes and interests of each individual (or to some group of individuals who share the same tastes and interests). A judgment such as “This is good” certainly seems to make a claim about the work itself, though such a claim is often based on the sort of feeling, understanding, or experience a person has obtained from the work. A work’s aesthetic or artistic value is generally distinguished from simply liking it. But is it possible to establish what sort(s) of knowledge or experience(s) any given work should provide to any suitably prepared perceiver, and what would it be to be suitably prepared?

With respect to this question, we should acknowledge that university degree programs in the humanities do purport to teach this kind of knowledge and thereby suitably prepare the perceiver to appreciate the works being studied. As a practical exercise, this is invaluable. Where things can go astray is when the judgment “this is good” floats free of its moorings in culture-specific subject-object relationships and imposes itself as objective fact.

It is a matter of contention whether a work’s aesthetic and artistic values are independent of its moral, political, or epistemic stance or impact.

They are independent. Clearly works of art can have moral, political, or epistemic dimensions, but these are outboard of the aesthetic dimension. When criticism seeks to interpret art through these kinds of filters, be they Marxist, feminist, deconstructionist, or the like, we have left the realm of the humanities behind and ceded authority instead to the social sciences.

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.

The paragraph above represents a laundry list of what for me are all the interesting topics. It warrants an entire essay of its own. That will be the subject of the essay to follow.

Work in the field has always been influenced by philosophical theories of language or meaning, and theories of knowledge and perception, and continues to be heavily influenced by psychological and cultural theory, including versions of semiotics, psychoanalysis, cognitive psychology, feminism, and Marxism.

Here we see more ceding of authority to the social sciences. It is not that they have nothing to add. It is that they are appropriating the aesthetic experience to promote another agenda. That agenda may indeed be worthwhile, but it cannot substitute for aesthetic analysis.

Some theorists in the late twentieth century have denied that the aesthetic and the “fine arts” can legitimately be separated out and understood as separate, autonomous human phenomena; they argue instead that these conceptual categories themselves manifest and reinforce certain kinds of cultural attitudes and power relationships. These theorists urge that aesthetics can and should be eliminated as a separate field of study, and that “the aesthetic” should not be conceived as a special kind of value. They favor instead a critique of the roles that images (not only painting, but film, photography, and advertising), sounds, narrative, and three-dimensional constructions have in expressing and shaping human attitudes and experiences.

And this is the ultimate ceding of authority to the social sciences, to which I am viscerally opposed.

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

Part Two coming soon!

Image Credit: Pexels

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Resilient Innovation

Why the Future Belongs to Organizations That Think in Three Dimensions

Why the Future Belongs to Organizations That Think in Three Dimensions

LAST UPDATED: March 11, 2026 at 6:56 PM (SPANISH LANGUAGE VERSION)

by Braden Kelley and Art Inteligencia


I. The Spark: A Venn Diagram That Captures a Powerful Truth

Inspiration for this article came from a simple but powerful visual shared in a recent post by Hugo Gonçalves. The image illustrated the relationship between Future Thinking, Design Thinking, and Systems Thinking using a Venn diagram that placed Resilient Innovation at the center.

At first glance the framework seems obvious. Each discipline is already well established in the innovation world:

  • Future Thinking helps organizations anticipate multiple possible futures.
  • Design Thinking focuses on solving problems through a human-centered approach.
  • Systems Thinking encourages examining systems holistically to understand complexity.

But what makes the diagram compelling is not the individual circles. It is the insight revealed at their intersections. When these disciplines operate together rather than in isolation, they unlock capabilities that are difficult for organizations to achieve otherwise.

At the intersection of Future Thinking and Design Thinking, organizations begin designing solutions for future scenarios rather than merely reacting to present conditions.

Where Design Thinking meets Systems Thinking, innovation becomes both human-centered and system-aware, producing solutions that account for real-world complexity and ripple effects.

And where Future Thinking intersects with Systems Thinking, organizations gain the ability to prepare systems for long-term sustainability and increasing complexity.

Resilient Innovation

When all three perspectives come together, something more powerful emerges: the ability to create innovations that are not only desirable and viable today, but resilient enough to thrive across multiple possible futures.

In a world defined by accelerating change, uncertainty, and interconnected systems, resilient innovation may be the most important capability organizations can develop. And as this simple diagram suggests, it thrives at the intersection of three powerful ways of thinking.

II. The Problem with One-Dimensional Innovation

Most organizations pursue innovation through a single dominant lens. Some lean heavily into design thinking workshops and rapid prototyping. Others invest in strategic foresight to anticipate future disruption. Still others focus on systems analysis to understand complexity and organizational dynamics.

Each of these approaches provides valuable insight. But when used in isolation, each also has significant limitations.

Design thinking, for example, excels at uncovering human needs and translating them into compelling solutions. Yet even the most desirable idea can fail if it ignores the larger systems it must operate within — regulatory structures, supply chains, cultural norms, or organizational incentives.

Future thinking helps organizations explore uncertainty and imagine multiple possible futures. Scenario planning and horizon scanning can expand strategic awareness and reduce surprise. But foresight alone rarely produces solutions that people are ready to adopt.

Systems thinking provides the ability to map complexity, understand feedback loops, and identify leverage points within interconnected environments. However, deep system insight does not automatically translate into solutions that resonate with human users.

When organizations rely on only one of these approaches, innovation often stalls. Ideas may be creative but impractical, visionary but disconnected from human behavior, or analytically sound but difficult to implement.

The challenge is not that these disciplines are flawed. The challenge is that they are incomplete on their own.

Innovation today takes place in environments that are simultaneously human, complex, and uncertain. Addressing only one dimension of that reality inevitably leads to blind spots.

Resilient innovation requires something more: the integration of multiple ways of thinking that together allow organizations to anticipate change, understand complexity, and design solutions people will actually embrace.

III. Future Thinking: Anticipating Multiple Possible Futures

One of the most dangerous assumptions organizations can make is that the future will look largely like the present. History repeatedly shows that markets, technologies, and societal expectations can shift faster than even experienced leaders anticipate.

This is where Future Thinking becomes essential, and the FutureHacking™ methodology helps everyone be their own futurist.

Future thinking is not about predicting a single outcome. Instead, it focuses on exploring a range of plausible futures so organizations can prepare for uncertainty rather than react to it after the fact.

Practitioners of future thinking use tools such as horizon scanning, trend analysis, and scenario planning to identify emerging signals of change and imagine how those signals might combine to shape different future environments.

By examining multiple possible futures, organizations expand their strategic imagination. They begin to see opportunities and risks that would otherwise remain invisible when planning is based solely on past performance or current market conditions.

Future thinking helps leaders ask better questions:

  • What changes on the horizon could reshape our industry?
  • Which emerging technologies or behaviors might disrupt our assumptions?
  • How might our customers’ needs evolve over the next decade?

When organizations incorporate future thinking into their innovation efforts, they gain the ability to design strategies and solutions that remain relevant even as conditions change.

However, foresight alone does not create innovation. Imagining the future is only the beginning. Organizations must also translate those insights into solutions that people value and systems can support.

That is why future thinking becomes far more powerful when combined with other perspectives — particularly the human-centered creativity of design thinking and the holistic understanding provided by systems thinking.

IV. Design Thinking: Solving Problems with a Human-Centered Approach

If future thinking expands our view of what might happen, design thinking helps ensure that the solutions we create actually matter to the people they are intended to serve.

Design thinking is grounded in a deceptively simple premise: innovation succeeds when it begins with a deep understanding of human needs, behaviors, and motivations. Rather than starting with technology or internal capabilities, design thinking begins with empathy.

Practitioners use methods such as observation, interviews, journey mapping, and rapid prototyping to uncover insights about how people experience products, services, and systems in the real world.

Through this process, organizations move beyond assumptions and begin designing solutions that reflect genuine human needs. Ideas are then explored through iterative experimentation, allowing teams to quickly learn what works, what doesn’t, and why.

This approach offers several powerful advantages:

  • It surfaces unmet or unarticulated customer needs.
  • It encourages experimentation and rapid learning.
  • It increases the likelihood that new solutions will be embraced by the people they are designed for.

Design thinking reminds organizations that innovation is not simply about creating something new. It is about creating something people will choose to adopt.

However, even the most human-centered solution can fail if it ignores the broader systems in which it must operate. A beautifully designed product may struggle against regulatory constraints, supply chain limitations, or cultural resistance within organizations.

This is why design thinking alone is not enough. To create innovations that truly endure, organizations must also understand the complex systems surrounding those solutions.

V. Systems Thinking: Seeing the Whole System

While design thinking focuses on people and future thinking explores uncertainty, systems thinking helps organizations understand the complex environments in which innovation must operate.

Modern organizations do not exist in isolation. They function within interconnected systems made up of customers, partners, suppliers, regulators, technologies, cultures, and internal structures. Changes in one part of the system often create ripple effects across many others.

Systems thinking encourages leaders and innovators to step back and examine these relationships holistically rather than focusing only on individual components.

Practitioners use tools such as system maps, causal loop diagrams, and stakeholder ecosystem mapping to identify patterns, dependencies, and feedback loops that influence outcomes over time.

This perspective provides several critical advantages:

  • It reveals hidden interdependencies within complex environments.
  • It helps identify leverage points where small changes can create large impact.
  • It reduces the likelihood of unintended consequences when introducing new solutions.

Many innovations fail not because the idea was flawed, but because the surrounding system was never designed to support it. Incentives may be misaligned. Processes may resist change. Infrastructure may not exist to scale the solution.

Systems thinking helps innovators recognize these structural realities early, allowing them to design solutions that fit within — or intentionally reshape — the systems they operate within.

Yet systems thinking alone can also fall short. Deep analysis of complexity does not automatically produce solutions that resonate with people or anticipate future shifts.

This is why resilient innovation emerges not from any one perspective, but from the intersection of future thinking, design thinking, and systems thinking working together.

Resilient Innovation Infographic

VI. Future Thinking + Design Thinking: Designing Solutions for Future Scenarios

When future thinking and design thinking come together, innovation shifts from solving today’s problems to designing solutions that remain meaningful in tomorrow’s world.

Future thinking expands the time horizon. It helps organizations explore emerging technologies, evolving social expectations, and potential disruptions that could reshape the environment in which products and services operate.

Design thinking brings the human perspective. It ensures that ideas developed in response to these future possibilities remain grounded in real human needs, motivations, and behaviors.

Together, these disciplines allow organizations to design solutions not just for the present moment, but for multiple possible futures.

Rather than asking only “What do customers need today?” teams begin asking deeper questions:

  • How might customer expectations evolve in the next five to ten years?
  • What new behaviors could emerge as technologies mature?
  • How might shifting social norms reshape what people value?

Several practices emerge from this intersection:

  • Creating future personas that represent how users might behave in different scenarios.
  • Building scenario-based prototypes that test how solutions perform under different future conditions.
  • Using speculative design to explore bold possibilities before they become reality.

This combination helps organizations avoid a common innovation trap: designing solutions perfectly optimized for a present that is already beginning to disappear.

By integrating foresight with human-centered design, organizations create innovations that are better prepared to evolve as the future unfolds.

VII. Design Thinking + Systems Thinking

Human-centered innovation is most powerful when it takes the wider system into account.
Integrating empathy with complexity awareness ensures that solutions are not only desirable but also viable and scalable within real-world systems.

Many well-intentioned innovations fail because they neglect system dynamics—leading to unintended consequences that can undermine adoption, efficiency, or long-term impact.

Example Practices

  • Journey Mapping + System Mapping: Understand the user experience alongside the broader system in which it operates.
  • Stakeholder Ecosystem Analysis: Identify all the players, relationships, and dependencies that influence outcomes.
  • Designing for Policy, Culture, and Infrastructure Simultaneously: Ensure solutions are compatible with the real-world environment, not just ideal scenarios.

Benefit: Solutions that scale effectively and endure within complex systems, reducing risk and maximizing long-term impact.

VIII. Future Thinking + Systems Thinking

Combining anticipation with structural understanding enables organizations to prepare systems for long-term sustainability and complexity. This intersection ensures that strategies and innovations are not just reactive but resilient to change and disruption.

Many organizations fail because they plan for the future without considering system-wide dynamics, leaving them vulnerable when change inevitably occurs.

Example Practices

  • Resilience Mapping: Identify system vulnerabilities and strengths to anticipate risks and opportunities.
  • Adaptive Strategy Design: Develop strategies that can flex and evolve as conditions change.
  • Long-Term Capability Building: Invest in skills, processes, and structures that sustain innovation over time.

Benefit: Organizations become prepared for volatility, able to respond to complex challenges without being derailed by disruption.

IX. The Center of the Venn Diagram: Resilient Innovation

True innovation resilience happens at the intersection of all three disciplines: Future Thinking, Design Thinking, and Systems Thinking. Organizations that operate here anticipate multiple possible futures, design solutions humans actually want, and understand the systems those solutions must survive inside.

This holistic approach moves beyond isolated innovation efforts, ensuring solutions are desirable, viable, and adaptable in a complex world.

Capabilities at the Center

  • Adaptive Innovation Portfolios: Maintain a diverse set of initiatives that can pivot as conditions change.
  • Experimentation Across Future Scenarios: Test solutions against multiple possible futures to validate robustness.
  • Human-Centered System Transformation: Redesign processes, structures, and policies to align with real human needs within systemic constraints.

Benefit: Organizations achieve resilient innovation that can thrive amidst uncertainty, disruption, and complexity, rather than merely surviving it.

Innovation Resilience Insights Quote

X. What Leaders Must Do to Build This Capability

Building resilient innovation requires leaders to shift their mindset and practices. It’s no longer enough to treat innovation as a siloed department or isolated initiative. Leaders must actively create the conditions that allow foresight, design, and systems thinking to work together.

Practical Leadership Shifts

  • Stop Treating Innovation as a Department: Embed innovation across teams and functions, not just in a single unit.
  • Build Foresight, Design, and Systems Capabilities Together: Develop cross-disciplinary skills that enable three-dimensional thinking.
  • Encourage Cross-Disciplinary Collaboration: Foster communication and shared problem-solving across different expertise areas.
  • Measure Resilience, Not Just Efficiency: Track long-term adaptability, system impact, and future-readiness, not only short-term outputs.
  • Design Organizations That Can Evolve Continuously: Create structures and processes that allow constant learning, adaptation, and iteration.

By adopting these leadership practices, organizations can ensure that their innovation efforts are not only creative but also resilient and scalable within complex systems.

XI. A Simple Test for Your Organization

To evaluate whether your organization is truly building resilient innovation capabilities, ask three critical questions:

  1. Are we designing only for today’s customers, or tomorrow’s realities?
    This question tests whether your innovation anticipates future needs and scenarios.
  2. Do our solutions work only in pilot environments, or within real systems?
    This evaluates whether innovations are scalable and resilient within the complex systems they must operate in.
  3. Are we solving human problems, or just optimizing processes?
    This ensures that your solutions are genuinely human-centered, not just operationally efficient.

If the answer to any of these is “no,” the missing capability likely lies at one of the intersections of Future Thinking, Design Thinking, and Systems Thinking. Addressing these gaps is critical for achieving resilient innovation.

XII. Final Thought: Innovation Is No Longer Linear

The world has become too complex for single-method innovation. Organizations that thrive in the future will be those that operate at the intersection of:

  • Anticipation: Preparing for multiple possible futures.
  • Human Understanding: Designing solutions people actually want and will adopt.
  • System Awareness: Ensuring solutions can survive and scale within real-world systems.

Resilient innovation does not come from seeing the future clearly. It comes from being prepared for many possible futures and designing systems and solutions that can adapt when they arrive. Organizations that master this approach are the ones that will endure, evolve, and thrive.

FAQ: Resilient Innovation

1. What is resilient innovation?

Resilient innovation is the ability of an organization to anticipate multiple possible futures, design solutions humans actually want, and ensure those solutions survive and scale within complex systems. It emerges at the intersection of Future Thinking, Design Thinking, and Systems Thinking.

2. Why do organizations struggle with one-dimensional innovation?

Many organizations rely on a single approach—such as design thinking, systems thinking, or future thinking—without integrating the others. This can lead to solutions that are desirable but not viable, or insightful but not actionable, resulting in innovation that fails to scale or adapt.

3. How can leaders build resilient innovation capabilities?

Leaders can foster resilient innovation by embedding cross-disciplinary collaboration, developing foresight, design, and systems capabilities together, measuring resilience (not just efficiency), and designing organizations that can continuously learn, adapt, and evolve.

p.s. Kristy Lundström posed the question of whether regenerative would be a better adjective than resilient, and I responded that it depends on where you draw the boundaries on the word resilient. I tend to think of it as an active word instead of a passive one, meaning the way that I look at the word incorporates elements of regeneration and making *#&! happen. Keep innovating!

Image credits: ChatGPT, 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 ChatGPT to clean up the article and add citations.

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

Has AI Killed Design Thinking?

Or Just Removed Its Excuses?

LAST UPDATED: March 2, 2026 at 5:13 PM

Has AI Killed Design Thinking?

by Braden Kelley and Art Inteligencia


I. The Question Everyone Is Whispering

Something fundamental has changed in how products are created.

Artificial intelligence can now generate working software in minutes. Designers can move from an idea to a functional prototype without waiting for engineering. Engineers can generate interface concepts, user flows, and even early product ideas with a few well-crafted prompts.

The traditional product development cycle — design, then build, then test — is collapsing into something faster, messier, and far more fluid.

In the past, the biggest constraint in innovation was the cost and time required to build something. Today, AI dramatically reduces that barrier. Entire features, experiments, and even applications can be created almost instantly.

Which raises an uncomfortable question that many product leaders, designers, and engineers are quietly asking:

If we can ship almost immediately, do we still need design thinking?

At first glance, the answer might seem obvious. Design thinking was created to help teams understand people, define the right problems, and avoid building the wrong solutions. Those goals have not disappeared.

But when the cost of building approaches zero, the role of design inevitably changes. The traditional pacing of discovery, ideation, prototyping, and testing begins to compress. The boundaries between designer and engineer begin to blur.

And as those boundaries dissolve, the question is no longer simply whether design thinking still matters.

The deeper question is whether the discipline itself must evolve to survive in a world where almost anyone can turn an idea into working software.

II. Design Thinking Was Built for a World of Scarcity

To understand how artificial intelligence is reshaping product creation, it helps to remember the environment in which design thinking originally emerged.

Design thinking did not appear because organizations suddenly discovered empathy or creativity. It emerged because building things was expensive, slow, and risky. Every product decision carried significant cost, and mistakes could take months or years to correct.

In that world, organizations needed a structured way to reduce uncertainty before committing engineering resources. Design thinking provided that structure.

Its now-famous stages helped teams move deliberately from understanding people to building solutions:

  • Empathize — deeply understand the people you are designing for.
  • Define — frame the real problem worth solving.
  • Ideate — generate a wide range of possible solutions.
  • Prototype — create rough representations of potential ideas.
  • Test — validate whether those ideas actually work for people.

The goal was simple: avoid spending months building something no one actually needed.

Design thinking slowed teams down in the right places so they could move faster later. It created space for exploration before the heavy machinery of engineering was set in motion.

But this entire framework assumed one critical constraint:

Building was the most expensive part of innovation.

Prototypes were often static mockups. Experiments required engineering time. Even small product changes could take weeks or months to ship.

In other words, design thinking was optimized for a world where the biggest risk was building the wrong thing.

Today, AI is rapidly changing that assumption. When working software can be generated in minutes rather than months, the bottleneck shifts — and the role of design must evolve with it.

III. AI Has Flipped the Innovation Constraint

For most of the history of digital product development, the limiting factor in innovation was the ability to build. Even the best ideas had to wait in line for scarce engineering resources, long development cycles, and complex release processes.

Artificial intelligence is rapidly dismantling that constraint.

Today, AI tools can generate functional code, working interfaces, and interactive prototypes in minutes. What once required a team of specialists and weeks of effort can often be produced by a single individual in an afternoon.

Designers can now:

  • Create interactive prototypes that behave like real products
  • Generate front-end code directly from design concepts
  • Rapidly explore multiple product directions

Engineers can now:

  • Generate user interfaces and layouts
  • Experiment with product concepts before committing to full builds
  • Quickly iterate on product experiences

The barrier between idea and implementation is shrinking dramatically.

As a result, the core constraint in innovation is no longer the ability to build something. The new constraint is the ability to decide what should actually be built.

When creation becomes cheap, judgment becomes the scarce resource.

Organizations can now generate more ideas, features, and experiments than they have the capacity to evaluate thoughtfully. The risk is no longer simply building the wrong thing slowly.

The risk is building thousands of things quickly without enough clarity about which ones actually matter.

This shift fundamentally changes the role of design. Instead of primarily helping teams avoid costly mistakes in development, design increasingly becomes the discipline that helps organizations navigate overwhelming possibility.

IV. The Blurring of Roles: Designers Reach Forward, Engineers Reach Back

One of the most profound effects of AI in product development is the erosion of traditional professional boundaries.

For decades, the technology industry operated with relatively clear separations of responsibility. Designers focused on user needs, interaction models, and visual systems. Engineers translated those designs into working software. Product managers coordinated priorities and timelines between the two.

That structure was largely a reflection of technical limitations. Designing and building required specialized tools, knowledge, and workflows that made cross-disciplinary work difficult.

AI is rapidly dissolving those barriers.

Designers can now reach forward into the domain that once belonged exclusively to engineering. With AI-assisted tools, they can generate working interfaces, produce front-end code, and simulate complex user interactions without waiting for implementation.

At the same time, engineers can reach backward into design. AI systems can help them generate layouts, propose interface structures, and explore experience flows that once required specialized design expertise.

The result is a new kind of creative overlap:

  • Designers who can prototype in code
  • Engineers who can explore experience design
  • Product creators who move fluidly between disciplines

The traditional model of work moving through a linear chain — research to design to engineering — begins to give way to a far more integrated creative process.

The future product creator is not defined by a job title, but by the ability to move fluidly between understanding problems and building solutions.

This does not mean design expertise or engineering skill become less important. If anything, the opposite is true. As tools make it easier for everyone to participate in creation, the depth of real craft becomes more visible and more valuable.

But it does mean the rigid boundaries between “designer” and “builder” are beginning to dissolve, creating a new generation of hybrid creators who can move seamlessly between imagining, designing, and shipping experiences.

V. The Death of the Handoff

For decades, most product development operated like a relay race. Work moved from one team to the next through a series of formal handoffs.

Researchers gathered insights and passed them to designers. Designers created wireframes and mockups that were handed to engineering. Engineers translated those designs into working software and eventually passed the finished product to testing and operations.

Each transition introduced delays, misinterpretations, and loss of context. The original understanding of the problem often became diluted as it traveled through the system.

Artificial intelligence is accelerating the collapse of this model.

When individuals can move rapidly from idea to prototype to functional product, the need for rigid handoffs begins to disappear. A single person can now:

  • Explore a user problem
  • Design a potential solution
  • Generate working code
  • Launch an experiment

Instead of waiting for work to pass from one discipline to another, creators can stay connected to the entire lifecycle of an idea.

The distance between insight and implementation is shrinking.

This shift has profound implications for how innovation happens inside organizations. Instead of large teams coordinating complex handoffs, smaller groups — or even individuals — can rapidly test ideas and learn from real-world feedback.

Product development begins to look less like an industrial assembly line and more like a creative studio, where ideas are explored, built, and refined continuously.

The most effective teams in this environment will not simply move faster. They will maintain ownership of ideas from the moment a problem is discovered all the way through to the moment a solution is experienced by real people.

VI. What AI Actually Kills

Artificial intelligence is not killing design thinking.

What it is killing are many of the habits that organizations adopted in the name of design thinking but that were never truly about understanding people or solving meaningful problems.

For years, some teams have mistaken the appearance of innovation for the practice of it. Workshops replaced experiments. Sticky notes replaced decisions. Slide decks replaced prototypes.

When building was slow and expensive, these behaviors were often tolerated because teams needed time to align before committing resources. But in a world where working solutions can be generated almost instantly, those habits quickly become friction.

AI removes the excuses that allowed these patterns to persist.

Process Theater

Innovation workshops that generate energy but not outcomes become difficult to justify when teams can build and test ideas immediately.

Endless Ideation

Brainstorming sessions that produce dozens of ideas without committing to experiments lose their value when ideas can be rapidly turned into prototypes and evaluated in the real world.

Documentation Instead of Exploration

Detailed reports, long strategy decks, and static artifacts once helped communicate ideas across teams. But when AI allows concepts to be expressed through working experiences, documentation becomes less important than experimentation.

Safe Innovation

Perhaps most importantly, AI challenges organizations that use process as a shield against risk. When it becomes easy to test bold ideas quickly and cheaply, avoiding experimentation becomes a choice rather than a necessity.

AI doesn’t eliminate design thinking. It eliminates the distance between thinking and doing.

The organizations that thrive in this environment will not be the ones with the most polished innovation processes. They will be the ones that are most willing to replace discussion with discovery and ideas with experiments.

Has AI Killed Design Thinking Infographic

VII. The New Role of Design: Decision Velocity

When the cost of building drops dramatically, the nature of competitive advantage changes.

In the past, organizations succeeded by efficiently transforming ideas into products. Engineering capacity, technical expertise, and operational discipline were often the primary constraints.

But when AI can generate working software, prototypes, and experiments almost instantly, the challenge is no longer how quickly something can be built.

The challenge becomes how quickly and wisely teams can decide what is actually worth building.

In an AI-driven world, innovation speed is no longer about development velocity — it is about decision velocity.

This is where the role of design evolves.

Design shifts from primarily producing artifacts — wireframes, mockups, and prototypes — to guiding the choices that shape meaningful innovation.

Designers increasingly become the people who help teams:

  • Frame the right problems to solve
  • Clarify human needs and motivations
  • Prioritize which ideas deserve experimentation
  • Interpret signals from real-world user behavior

In other words, design becomes less about shaping the interface of a product and more about shaping the direction of learning.

When organizations can generate thousands of potential solutions, the real value lies in identifying the small number that actually create meaningful value for people.

Designers, at their best, help organizations navigate that complexity. They connect technology to human context, helping teams avoid the trap of building faster without thinking better.

In the AI era, design is not slowing innovation down. It is helping organizations move quickly without losing their sense of where they should be going.

VIII. From Design Thinking to Design Doing

As artificial intelligence compresses the distance between idea and implementation, the nature of design practice begins to change. The emphasis shifts away from structured stages and toward continuous experimentation.

Traditional design thinking frameworks helped teams organize their thinking before committing to build. But in an AI-enabled environment, building itself becomes part of the thinking process.

Instead of long cycles of analysis followed by development, teams can now explore ideas directly through working prototypes and rapid experiments.

The most effective teams no longer separate thinking from building. They think by building.

This shift marks a move from design thinking to what might be called design doing.

In this model, learning happens through fast cycles of creation, feedback, and refinement. Ideas are not debated endlessly in workshops or captured in lengthy documents. They are explored through tangible experiences that can be observed, tested, and improved.

The practical differences begin to look like this:

Traditional Model AI-Enabled Model
Workshops and brainstorming sessions Rapid experiments and live prototypes
Personas and research summaries Behavioral data and real-world signals
Concept mockups Functional prototypes
Long planning cycles Continuous learning loops

None of this diminishes the importance of understanding people. If anything, the need for deep human insight becomes even more important as the pace of experimentation accelerates.

What changes is how that understanding is expressed. Instead of existing primarily as documents or presentations, insight becomes embedded directly into the experiences teams create and test.

In an AI-native organization, design is no longer a phase that happens before development begins. It becomes an ongoing activity woven directly into the act of building and learning.

IX. Human Trust Becomes the New Design Material

As artificial intelligence accelerates the speed of building, the most important design challenges begin to shift away from usability and toward something deeper: trust.

When products can be created, modified, and deployed almost instantly, the risk is not simply poor interface design. The risk is creating experiences that feel disconnected from human values, human context, and human expectations.

AI makes it easier than ever to generate functionality. But it does not automatically ensure that what is generated is responsible, understandable, or aligned with the needs of the people who will use it.

In an AI-driven world, the most important design material is no longer pixels or screens — it is human trust.

This raises a new set of responsibilities for designers, engineers, and product leaders alike.

Teams must think carefully about questions such as:

  • Do people understand what the system is doing?
  • Are decisions being made transparently?
  • Does the experience respect human autonomy?
  • Does the technology reinforce or erode confidence?

As AI systems become more powerful, the danger is not just that they might fail. The danger is that they might succeed in ways that quietly undermine the relationship between organizations and the people they serve.

Design therefore becomes a critical safeguard. It ensures that rapid technological capability does not outpace thoughtful consideration of human consequences.

In this sense, the role of design expands beyond shaping products. It becomes the discipline that ensures technology remains grounded in human meaning, responsibility, and trust.

X. The Future: Designers Who Ship, Engineers Who Empathize

As AI blurs the traditional boundaries between design and engineering, the most valuable creators in the future will be those who can move fluidly between imagining, designing, and building.

Designers will need to ship working products, not just static prototypes. Engineers will need to empathize deeply with users, understanding problems and shaping experiences that align with human needs.

The new hybrid product creator embodies both curiosity and capability, bridging the gap between thinking and doing. They are able to:

  • Rapidly translate insights into working solutions
  • Experiment and learn from real-world user behavior
  • Balance technical feasibility with human desirability
  • Maintain alignment between strategy, design, and execution

In this new landscape, design thinking does not disappear — it evolves. AI removes many of the barriers that previously prevented designers and engineers from collaborating fully and iterating quickly.

The organizations that succeed will be those where everyone has the ability to both understand humans and act on that understanding at the speed of AI.

The future belongs to hybrid creators who can navigate ambiguity, make fast decisions, and embed human trust into every experiment. In such a world, innovation is no longer the domain of specialists — it is the responsibility of anyone capable of connecting insight with action.

XI. The Real Question Leaders Should Be Asking

The debate is often framed as a dramatic question: “Has AI killed design thinking?” But this framing misses the deeper challenge facing organizations today.

The real question is not whether design thinking survives — it is whether organizations are prepared to operate in a world where anyone can turn ideas into working products almost instantly.

In this AI-accelerated environment, success depends less on the speed of coding or the elegance of design frameworks. It depends on human judgment, understanding, and alignment.

Leaders must ask themselves:

  • Do our teams know what problems are truly worth solving?
  • Can we prioritize experiments that create real human value?
  • Are we embedding human trust and ethical consideration into everything we build?
  • Are our designers and engineers equipped to operate across traditional boundaries?

In this new era, the organizations that thrive will not be the ones with the fastest developers or the slickest design processes.

They will be the organizations that can rapidly identify meaningful opportunities, make thoughtful decisions, and maintain human-centered principles while moving at the speed of AI.

Innovation will no longer belong to the people who can code. It will belong to the people who understand humans well enough to know what should be built in the first place.

The role of leadership is no longer just managing workflows — it is shaping the environment in which hybrid creators can think, act, and build responsibly at unprecedented speed.

New Tools for the New Design Reality

Get the new design thinking downloadsTo help you find problems worth solving and to design and execute experiments, I created a couple of visual and collaborative tools to help you thrive in this new reality. Download them both from my store and enjoy!

  1. Problem Finding Canvas — Only $4.99 for a limited time
  2. Experiment Canvas — FREE

FAQ: AI and the Evolution of Design Thinking

1. Has AI made design thinking obsolete?
No. AI has not killed design thinking, but it has changed the context in which it operates. Traditional design thinking frameworks assumed that building was slow and expensive. With AI accelerating the creation of prototypes and software, design thinking evolves from a staged process into a continuous cycle of experimentation and decision-making.
2. How are the roles of designers and engineers changing with AI?
AI blurs the traditional boundaries between designers and engineers. Designers can now generate working code and functional prototypes, while engineers can explore user experience and interface design. The future favors hybrid creators who can both understand human needs and rapidly implement solutions.
3. What becomes the main focus of design in an AI-driven product environment?
The primary focus shifts from producing artifacts to guiding decision-making and protecting human trust. Design becomes the discipline that helps teams prioritize meaningful experiments, interpret real-world feedback, and ensure that rapid technological development remains aligned with human values and needs.


Image credits: ChatGPT

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

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

How Mature is Your Technology?

How Mature is Your Technology?

GUEST POST from Mike Shipulski

As a technologist it’s important to know the maturity of a technology. Like people, technologies are born, they become children, then adolescents, then adults and then they die. And like with people, the character and behavior of technologies change as they grown and age. A fledgling technology may have a lot of potential, but it can’t pay the mortgage until it matures. To know a technologies level of maturity is to know when it’s premature to invest, to know when it’s time to invest, to know when to ride it for all it’s worth and time to let it go.

Google has a tool called Ngram Viewer that performs keyword searches of a vast library of books and returns a plot of how frequently the word was found in the books. Just type the word in the search line, specify the years (1800-2007) and look at the graph.

Below is a graph I created for three words: locomotive, automobile and airplane. (Link to graph.) If each word is assumed to represent a technology, the graph makes it clear when authors started to write about the technologies (left is earliest) and how frequently it was used (taller is more prevalent). As a technology, locomotives came first, as they were mentioned in books as early as 1800. Next came the automobile which hit the books just before 1900. And then came the airplane which first showed itself in about 1915.

Google Ngram graph 1

In the 1820s the locomotives were infants. They were slow, inefficient and unreliable. But over time they matured and replaced the Pony Express. In the late 1890s the automobiles were also infants and also slow, inefficient and unreliable. But as they matured, they displaced some of the locomotives. And the airplanes of 1915 were unsafe and barely flight-worthy. But over time they matured and displaced the automobiles for the longest trips.

[Side note – the blip in use of the word in 1940s is probably linked to World War II.]

But for the locomotive, there’s a story with a story. Below is a graph I created for: steam locomotive, diesel locomotive and electric locomotive. After it matured in the 1840s and became faster and more efficient, the steam locomotive displaced the wagon trains. But, as technology likes to do, the electric locomotive matured several decades after it’s birth in 1880 and displaced it’s technological parent the steam locomotive. There was no smoke with the electric locomotive (city applications) and it did not need to stop to replenish it’s coal and water. And then, because turn-about is fair play, the diesel locomotive displaced some of the electric locomotives.

Google Ngram graph 2

The Ngram Viewer tool isn’t used for technology development because books are published long after the initial technology development is completed and there is no data after 20o7. But, it provides a good example of how new technologies emerge in society and how they grow and displace each other.

To assess the maturity of the youngest technologies, technologists perform similar time-based analyses but on different data sets. Specialized tools are used to make similar graphs for patents, where infant technologies become public when they’re disclosed in the form of patents. Also, special tools are used to analyze the prevalence of keywords (i.e., locomotives) for scientific publications. The analysis is similar to the Ngram Viewer analysis, but the scientific publications describe the new technologies much sooner after their birth.

To know the maturity of the technology is to know when a technology has legs and when it’s time to invent it’s replacement. There’s nothing worse than trying to improve a mature technology like the diesel locomotive when you should be inventing the next generation Maglev train.

Image credit: Wikimedia Commons, Google Ngram

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

What is the right time horizon for technology development?

What is the right time horizon for technology development?

GUEST POST from Mike Shipulski

Patents are the currency of technology and profits are the currency of business. And as it turns out, if you focus on creating technology you’ll get technology (and patents) and if you focus on profits you’ll get profits. But if no one buys your technology (in the form of the products or services that use it), you’ll go out of business. And if you focus exclusively on profits you won’t create technology and you’ll go out of business. I’m not sure which path is faster or more dangerous, but I don’t think it matters because either way you’re out of business.

It’s easy to measure the number of patents and easier to measure profits. But there’s a problem. Not all patents (technologies) are equal and not all profits are equal. You can have a stockpile of low-level patents that make small improvements to existing products/services and you can have a stockpile of profits generated by short-term business practices, both of which are far less valuable than they appear. If you measure the number of patents without evaluating the level of inventiveness, you’re running your business without a true understanding of how things really are. And if you’re looking at the pile of profits without evaluating the long-term viability of the engine that created them you’re likely living beyond your means.

In both cases, it’s important to be aware of your time horizon. You can create incremental technologies that create short term wins and consume all your resource so you can’t work on the longer-term technologies that reinvent your industry. And you can implement business practices that eliminate costs and squeeze customers for next-quarter sales at the expense of building trust-based engines of growth. It’s all about opportunity cost.

It’s easy to develop technologies and implement business processes for the short term. And it’s equally easy to invest in the long term at the expense of today’s bottom line and payroll. The trick is to balance short against long.

And for patents, to achieve the right balance rate your patents on the level of inventiveness.

Image credit: 1 of 1,050+ FREE quotes for your meetings & presentations at http://misterinnovation.com

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.