Eric Morrison on How Interdisciplinary Backgrounds Improve User Experience Research

The History Major Who Decodes Technology

Eric Morrison studied History at Yale University and earned a Master of Science in the Social Science of the Internet at Oxford. Today, he leads research at Google on how artificial intelligence shapes workplace collaboration. His path from history to tech isn’t a detour. It’s the reason his work stands out.

With over 14 years of experience leading research programs at Google, TikTok, and Disney, Morrison brings a perspective grounded in the humanities rather than computer science. His interdisciplinary background allows him to ask questions that others miss and find patterns that purely technical researchers often overlook.

Why Technical Teams Need Non-Technical Thinking

A healthy share of UX researchers come from human-computer interaction or design programs. Morrison took a different route. He spent years studying how societies evolve, why movements succeed or fail, and what drives people to adopt new ideas. That foundation now shapes how he approaches product development.

“History and the social sciences give me a unique approach to UX research,” Morrison explains. “I believe that even the most complex outcomes—say, for example: building a novel innovation, or driving viral adoption of a product—can be broken down into foundational processes that can be replicated.”

This mindset changes the game. Instead of treating each product launch as a standalone event, Morrison looks for underlying mechanics. He sees user behavior as something that can be decoded and engineered, not just observed and documented.

The tech industry has long valued specialists who go deep in one area. But as products become more complex and users more diverse, teams need people who can connect dots across disciplines. Morrison’s work proves that broad knowledge bases produce sharper insights.

Finding Repeatable Formulas in User Behavior

Traditional UX research often focuses on identifying problems and suggesting fixes. Morrison goes further. He wants to understand the fundamental sequences that lead to successful adoption. That requires looking beyond surface-level feedback.

“Too often, product decisions are based on assumptions or one-off successes,” he says. “Our job is to find the repeatable formula. If we understand the fundamental process of why a user finds value, we can engineer that success again and again.”

This approach stems directly from his training as a historian. Academic research taught him to trace causality, identify patterns across time periods, and separate correlation from actual drivers of change. Those same skills apply when analyzing why users embrace certain features and ignore others.

At Google, Morrison leads research on AI in the workplace. The challenge isn’t just figuring out what features to build. It’s understanding how teams actually collaborate, what blocks productivity, and how technology can support human creativity rather than replace it.

Curiosity as a Competitive Advantage

Interdisciplinary backgrounds create something valuable: sustained curiosity about systems. Morrison doesn’t take technology at face value. He questions why things work the way they do and whether they could work differently.

“History taught me to ask why things happen the way they do,” Morrison notes. “That curiosity still drives my work today.”

That questioning mindset matters more as AI becomes embedded in everyday tools. Companies need researchers who can anticipate how new capabilities will reshape behavior, not just measure reactions after products launch.

Morrison’s work on AI and workplace communication reveals gaps that purely technical analysis might miss. He identified a pattern he calls the Automated Echo Trap, where machines generate updates, other machines summarize them, and people review without truly engaging.

“We’ve removed the cost of generating text, but we haven’t expanded the capacity of the person reading it,” he explains. “That gap is where everything starts to fall apart.”

Catching these systemic issues requires understanding human cognition, organizational behavior, and communication theory alongside technical capabilities. No single discipline covers all three.

Building Research Programs That Deliver Insight Quickly

Interdisciplinary thinking also helps with strategic velocity. Morrison has worked across fast-moving companies where waiting months for research findings means missing critical opportunities.

“There is a hidden cost to moving fast without direction,” he says. “But there is also a massive cost to moving too slowly. If you take six months to deliver an insight, the world has already moved on.”

His background helps him prioritize what matters. History training teaches you to sift through massive amounts of information and identify the signal. Social science methods provide frameworks for testing hypotheses rapidly. Together, these skills let Morrison run research programs that inform decisions without slowing them down.

At TikTok, he served as Director of UX Research during a period of explosive growth. At Disney, he managed research for products serving millions of users. In both cases, his ability to synthesize insights from multiple disciplines helped teams make confident bets on new features.

What This Means for the Future of UX Research

The industry is starting to recognize the value of varied backgrounds. But most hiring still favors traditional credentials. Morrison’s career suggests companies should look wider.

Researchers with training in anthropology, sociology, political science, or history bring frameworks that complement technical expertise. They understand power dynamics, cultural context, and how institutions shape individual behavior. These insights matter when building products for global audiences.

Morrison’s interdisciplinary approach also addresses ethical questions that purely technical research misses. His work emphasizes trust, transparency, and user control, especially around AI systems.

“Users need to trust the systems they use,” he stresses. “If they don’t understand what AI is doing, it won’t be effective. Clear communication and control are essential.”

These concerns emerge naturally from a background that includes studying social justice, institutional accountability, and how systems impact individuals. Technical training alone doesn’t always surface these considerations.

Making Better Products Through Broader Thinking

The strongest UX research programs combine deep expertise with wide-ranging curiosity. Eric Morrison’s work demonstrates that backgrounds outside traditional tech fields don’t just add diversity. They fundamentally improve research quality.

His interdisciplinary foundation lets him spot patterns others miss, ask questions that challenge assumptions, and build research frameworks that produce actionable insights quickly. As technology becomes more woven into daily life, teams need researchers who understand both systems and the people using them.

“I’ve always been fascinated by the underlying mechanics of how people adopt new tools,” Morrison says. “My goal isn’t just to observe behavior, but to decode the specific sequences that lead to a successful product launch.”

That goal requires exactly what his background provides: the ability to connect technical capability with human reality, to see patterns across contexts, and to translate complex findings into clear direction. The best UX research comes from people who can think across boundaries, not just within them.