The Next Decade of UX: Why Psychology Matters More Than Ever

We're in the midst of a new year, grappling with new tools and motivations, particularly the rapid advancements in AI. Yet, at our core, we remain the same humans, evolving at a much slower pace than technology. Ironically, as AI quickly helps us create interfaces, we're not necessarily seeing better designs—just a lot of average, templatized "slop." A deep understanding of psychology, however, may be the very ticket to helping our industry avoid this era of blandness.

I recently spoke with Thomas Watkins, a self-professed design psychologist, Principal UX Architect and founder of Threeleaf, and a lecturer at Rice University's Graduate School of Business. Our conversation explored psychology as a genuine superpower for UX and product teams, how templatization and AI shortcuts can flatten experiences, and why there's still plenty of "blue ocean" opportunity for those willing to truly understand the people and contexts they design for.

Psychology: The Enduring UX Superpower

Thomas shared his career journey, which started with cognitive science and human factors, then went "full circle" back to psychology after immersing himself in product and design. He emphasizes psychology as a superpower we should lean into.

Historically, psychology has been incredibly important in shaping how we design the world. We reflected on Don Norman, often called the grandfather of UX, who was profoundly influential in applied psychology and digital design. He was even instrumental in making cognitive science a cohesive, recognized field.

He made it a psychological concept by borrowing JJ Gibson's concept of affordance, real affordance, and he adapted that to perceived affordance and made it a a psychological construct, leaned into that kind of stuff, and was completely differentiated from his peers. — Thomas Watkins

A classic example is the "Norman door"—a door whose design makes it unclear whether to push or pull. Don Norman took this industrial design problem and framed it psychologically, demonstrating how our understanding of affordances (how we perceive possibilities for interaction) dictates our behavior.

Connecting Psychology to Design Patterns

For UX professionals without a formal psychology background, the path to leveraging these insights lies in understanding design patterns. This concept, originating from Christopher Alexander's "A Timeless Way of Building" in the late 70s, suggests that throughout history, humans have built things in archetypal, repeatable ways. Recognizing these patterns is the basic language of design, whether in architecture, industrial design, or UX.

To integrate psychology into your practice:

• Develop a strong vocabulary for the design patterns and elements specific to your field.
• Map these patterns onto their psychological pros and cons.

For instance, when designing how users interact with lists and their details, different approaches will have varying "visual load" or "cognitive load." Understanding these psychological implications allows you to intelligently choose the best solution for your situation, rather than just relying on intuition.

The Pitfalls of Templatization and AI Shortcuts

A critical challenge facing our industry is the "templatization of design." While relying on established conventions for elements like shopping carts is efficient and wise (we don't need to reinvent the wheel), it can also lead to an "averaging of experiences." This can result in products that feel generic, making it unclear why a user would choose one over another.

I've observed that psychology is often taken for granted in UX, with a common assumption that "we've figured it out." However, this overlooks several dangers:

• Isolated Factoids: Psychology is sometimes reduced to isolated "factoids" like "Miller's 7 ± 2," without understanding the deeper research traditions from which these insights emerged.
• Manipulative Applications: Psychology is unfortunately also discussed in a "nefarious gray area," intentionally used in marketing to manipulate users into behaviors or purchases they don't truly need.
• Superficial Buzzwords: Stakeholders might use psychological-sounding terms like "information overload" without a deep, informed understanding of what's truly going on.

There's a vast opportunity to enrich the conversation and move beyond these superficial understandings.

The Deeper Meaning of Products

Even after figuring out the basics of usability and good widgets, there's another crucial layer: "what the product means to people's lives." Our products impact users profoundly, sometimes even eliciting different personas.

Not all social media apps are the same. And if you were to sit down and introspect on it, you could say, "I'm kind of a different person on different, you know, these apps bring out something different in me with each one I use." You might say something like, you know, Twitter makes me a pundit. Um, IG makes me a curator. You know, Tik Tok makes me a performer. Um, you know, LinkedIn makes me like a persona manager. You know, Facebook makes me like a community member. You know, Reddit makes me a commentator. — Thomas Watkins

This principle extends beyond social media to any product. A note-taking tool, for example, might turn one user into an "information hoarder" and another into a "databaser." Understanding these nuanced behavioral impacts, these "meta layers," allows us to apply psychology strategically to orchestrate design at a higher level and uncover new opportunities.

The Blue Ocean Opportunity

The templatization trend tends to push products into a "red ocean" of intense competition. The real strategic advantage, often discussed in business circles, lies in pursuing "blue ocean" opportunities—finding and serving needs that are currently unmet or poorly served.

If you want to go where nobody else is, you have to do research about things that maybe other people haven't researched, right? You have to learn about people in very specific ways. And having that psychology background, I think to your point, is a superpower because you can know a little bit about specific things that people need or tendencies, people have, biases, people have, decision-m structures that they tend to use. — Theres Fessendon

Venturing into a blue ocean demands deep research and psychological insight into specific user needs, biases, and decision-making structures—knowledge that generic templates simply can't provide.

Navigating the AI Era: Humans Remain Human

As a lecturer at Rice University's innovation program, Thomas observes a growing misunderstanding among students about AI's capabilities. There's an opinion forming that AI can simply "do all of this"—build interfaces, manage user interactions, even replace traditional dashboards by just providing answers to questions. Thomas, however, is "betting on the other side that humans are going to still be humans."

I don't think that we will necessarily want to have all of our interactions be that we just ask serial strings of questions and then get answers, exact answers to each question. We like to look at things, right? look at a basic display and make sense of it and try to interpret it. That's something that humans like to do and I don't see that going away. — Thomas Watkins

I noted that this "prompt-based" interaction model feels a lot like the old MS-DOS days, where users needed technical know-how to input specific commands. The graphical user interface (GUI) was invented precisely because looking at and tapping on things was an easier, more natural way to interact. While AI offers powerful "cognitive augmentation" for complex tasks, relying solely on it risks bypassing fundamental design understanding. Just as a writer uses ChatGPT more effectively because they understand storytelling, designers need to grasp the "why" behind their craft, not just generate deliverables instantly.

Overhumanization and Human Detection

A significant issue is the overestimation of how "human" AI truly is, often driven by marketing that "misappropriates psychology terms." While computer science and psychology have a history of borrowing terms from each other (like "inputs" and "outputs"), the current trend is to sell AI as "thinking" and "humanlike," even implying it can replace human workforces.

The AI sort of marketing machine, the AI kind of tech bros have oversold how human things are and to the point where they're kind of misappropriating psychology terms in order to sell it... they're saying, "No, it's it's uh it's like a human. It's thinking like like nowadays like when it's processing." No, it's processing. It's not thinking, right? — Thomas Watkins

AI, at its core, performs "statistical inference"—calculating the most probable answer, not arriving at truth through cognition. While humans have a long history of anthropomorphizing technology (like the "Eliza effect," where the first chatbot was perceived as human), we are also "human detection machines." We are biologically wired to be hyper-social and incredibly adept at discerning the nuances of authentic human interaction. This creates an "arms race" between AI's ability to imitate and our innate capacity to detect. Recognizing this fundamental difference helps us appreciate the unique "human value" we bring.

Developing Your Psychology Understanding

Becoming a psychology expert isn't necessary, but enriching your understanding is vital. People have implicitly used psychological principles for millennia—magicians understood inattentional blindness long before the term existed, and writers like Jane Austen mastered "theory of mind." Science simply codifies and validates these phenomena.

As practitioners, we're likely already using some psychology. The goal is to make that implicit understanding explicit:

• Follow your curiosity: When you notice a design pattern that works, ask if there's an underlying psychological effect and delve into it.
• Focus on application: Seek out resources that connect psychological principles directly to practical design scenarios and explain how to use them.

The Cognitive Load Theory Example

A powerful example comes from instructional design. Thomas highlighted John Sweller, who developed Cognitive Load Theory in the 1980s. In UX, we often say, "get rid of cognitive load" to make things easy. However, Sweller's theory distinguishes between different types:

• Extrinsic cognitive load: Unnecessary mental effort (which we should minimize).
• Intrinsic cognitive load: Effort related to the inherent complexity of the material itself.
• Germane cognitive load: Effort related to learning and building mental models (which we want to optimize).

This insight means that for complex interfaces like dashboards, the goal isn't always to simplify everything to the point of stripping away information. Instead, we should embrace the fact that "a certain amount of effort is necessary for learning," optimize the germane load, and eliminate only the extraneous. This enriches our understanding, preventing oversimplification.

Whether it's data visualization, instructional design, game design, or UX, understanding psychology allows us to cater to human perceptual and cognitive systems, optimize learning, foster flow states, and ultimately make technology fade into the background, so users can focus on their true goals.

Actionable Takeaways

In an era of rapid change and increasing automation, staying grounded in human understanding is more critical than ever. Here are some actionable takeaways:

• Embrace Psychology as Your Superpower: Don't take foundational psychological principles for granted. Understanding the "why" behind design patterns and best practices is what differentiates truly insightful design from mere templatization.
• Focus on Product Meaning, Not Just Features: Move beyond usability and features to consider how your product impacts users' lives and the behaviors it encourages. This strategic, psychologically informed perspective can unlock "blue ocean" opportunities.
• Become a Human Detection Machine: Recognize the powerful but inherently non-human nature of AI. Don't fall for "overhumanization." As designers, our unique value lies in understanding and catering to the innate human need for connection and authentic interaction.
• Continuously Enrich Your Psychology Understanding: You don't need a formal psychology degree. Cultivate your curiosity. When you see a design pattern, ask, "Is there a psychological effect at play here?" Read articles and resources that connect psychological principles directly to practical application in UX.
• Automate Tedium, Not Talent: As Don Norman famously advised, leverage automation to handle repetitive, tedious tasks. This frees you to focus your human talent on high-value activities—understanding nuanced user needs, strategizing unique experiences, and bringing humanity back to interactions, especially at the moments that matter most to users.