Humanizing Technology in a High Context Culture

Technology conversations often focus on what systems can do: faster processing, wider reach, greater efficiency. Less frequently discussed is how those systems actually feel to the people expected to live with them.

Last Thursday, May 7, I spoke before the Philippine Chief Information Officers Association (PCIOA) on a subject that has stayed with me for years as someone shaped by the humanities: humanizing technology. I came into the room fully aware that I was surrounded by CIOs, innovation leaders, and digital leaders tasked with shaping how organizations navigate digital transformation – from enterprise systems and cybersecurity to cloud infrastructure, integration, data, and AI deployment.

I was there to offer another lens – one shaped by anthropology, behavioral science, and marketing strategy. I knew better than to challenge technology itself, but instead to ask what happens when we forget the human being on the other side of it. After all, solving a problem and humanizing the experience of being helped are not the same thing.

For example, a queueing system can reduce waiting time and still make people feel processed rather than cared for. A hospital portal can organize records perfectly and still leave a frightened patient feeling alone. An HR system can automate everything correctly while making the HR manager feel less like a steward of people and more like a reluctant system administrator. That gap matters more than many organizations realize.

The irony is that technology itself was born from empathy. The wheel came from the need to lessen burden. The telephone emerged from the desire to bridge distance. The printing press democratized knowledge. At their core, these were deeply human inventions – responses to frustration, limitation, isolation, or pain.  This origin story beautifully encompasses how perspectives can change based on how we see technology – would the design brief change if we defined technology not just as tools, devices, or methods to solve problems, but as   “the purposeful use of human capability to shape the world?”

Here we find how technology began with someone paying close attention to another person’s difficulty and deciding to do something about it. Unfortunately, somewhere in the race to deploy faster, scale faster, and optimize faster, the system itself became the center of gravity. We started asking what the technology could do before asking what the person actually needed.

This is not to suggest that modern technology ignores human behavior. On the contrary, it increasingly depends on understanding it with remarkable precision, especially in the age of AI and algorithms. Netflix predicts what we are likely to watch. Grab anticipates when demand will surge. Recommendation engines, dynamic pricing models, and AI systems are all built around predicting human behavior.

But behavioral science reminds us of something important: humans are not perfectly rational actors. Herbert Simon called it bounded rationality. Richard Thaler and Cass Sunstein later expanded this through behavioral economics and “nudge” theory. Human beings make decisions while distracted, emotional, tired, overwhelmed, uncertain, and pressed for time. We rely on shortcuts. We skip instructions. We look for the easiest path.

The real question then is not whether technology understands human behavior but what it chooses to do with that knowledge. When systems know how we are likely to behave, are they designed to help us — or simply to optimize us for the efficiency of the platform? That distinction is becoming increasingly important.

Some of the most effective Filipino platforms succeeded precisely because they designed around real human behavior instead of forcing people to behave like ideal users in a textbook. GCash understood that many Filipinos would trust a neighborhood sari-sari store for cash-in faster than a formal bank branch. Sprout embedded compliance processes directly into workflows because exhausted HR teams were unlikely to search for separate policy documents after work hours. These systems succeeded not simply because they were technologically sound, but because they were behaviorally realistic.

And this is where culture — not just behavior — becomes important in how we conceive technology.

When designing for Filipinos, it helps to remember that we operate within a deeply relational, high-context culture. When many Filipinos need help from a bank or government office, the instinct is often to contact someone they know before opening the app. When a new workplace platform is introduced, employees frequently ask seatmates for guidance rather than reading the manual. When customers feel ignored, they escalate publicly through Facebook because public visibility often gets faster results than formal complaint systems.

These are not irrational behaviors. They are culturally rational responses shaped by decades of institutional experience. The technology itself may not even be the problem. Sometimes it’s the assumptions underneath it.

There are many systems built on assumptions — for example,  that users trust institutions automatically, prefer purely self-service systems, follow linear instructions carefully, and make decisions independently. Those assumptions work in some cultures. They do not always work in ours. Which means humanizing technology is not simply about adding softer language, better interfaces, or friendlier chatbots. It requires understanding how people actually behave, decide, trust, relate, and seek help within their own cultural environments.

Here’s a final case in point: The Philippine Identification System or PhilSys is one of the country’s most ambitious digital transformation initiatives. Over 90 million Filipinos have already registered.  The intention behind it is important and necessary. But there were reports of elderly Filipinos struggling with biometric registration because decades of manual labor had worn their fingerprints smooth.

The scanners could not read them properly. They were asked to return another day. The technology was functioning exactly as designed. But nobody had fully anticipated what would happen to the oldest and most vulnerable person standing at the end of that error message. That is not simply a technology issue — but a failure of imagination.

And perhaps that is where the real responsibility of today’s technology leaders now sits – not merely building systems that function, but building systems capable of recognizing human dignity even under imperfect conditions.

Technology is no longer confined to IT departments. It is now the expression layer of the entire business model. Every customer interaction, operational workflow, employee experience, and institutional promise increasingly passes through technology. This means every technology decision is also a human decision. And maybe that is the question worth carrying into every boardroom, design review, procurement meeting, and digital transformation plan:

Are we merely solving the problem – or are we truly serving the person?

(Chiqui Escareal-Go is a marketing anthropologist and behavioral strategist who studies how people think, decide, and respond to the systems built around them. As CEO of Mansmith and Fielders, Inc., she has worked with leaders and organizations across industries on strategy, innovation, and leadership for over three decades. She writes on the intersection of human behavior and technology — arguing that the most consequential design decisions are never purely technical. She can be reached at chiqui@mansmith.net.)