About The Data Human
The Data Human is a way of thinking about data that starts with people, not systems.
Much of how data is used today feels disconnected from the humans it describes. We collect more data than ever, build increasingly sophisticated models, and promise more personalized experiences. Yet many people feel misunderstood, over-measured, or uneasy about how their data is collected and used.
This work begins with a simple belief.
If data is about people, it should be designed with people in mind.
The Data Human exists to explore what that actually means in practice.
Why this work exists
Data-driven systems are often evaluated by what they can do. How accurate they are. How efficient they are. How well they optimize outcomes.
Far less attention is paid to how those systems are experienced by the people on the other side of them.
Do they feel clear or opaque. Helpful or invasive. Respectful or extractive.
The Data Human focuses on that gap. It looks at data, personalization, and technology through the lens of human behaviour, intent, and expectation, and asks whether our systems are truly designed to understand people or simply to measure them.
About me
My name is Andrew Ko. I work at the intersection of behaviour, technology, and digital experience.
Over the years, my work has spanned research, teaching, and building companies focused on personalization and data-driven decision making. Across those environments, I became increasingly interested in how people express themselves through behaviour rather than through forms, surveys, or explicit declarations.
Again and again, I encountered the same tension. Data systems were becoming more capable and more precise, yet many people felt less understood by them.
The Data Human grew out of trying to make sense of that tension.
How this thinking took shape
Earlier work with contextual and behavioural data showed how much could be inferred from what people do, often without asking them anything at all.
Later experiences building and working with data-driven systems revealed the limits of that approach. Technical accuracy did not always translate into comfort, trust, or understanding. In some cases, the more accurate a system became, the more uncomfortable it felt.
Teaching added another perspective. Students intuitively understood the promise of personalization, but were often uneasy with how invisible and one-sided many data practices had become.
These experiences shaped the questions that sit at the centre of this work.
The Data Human Index
One outcome of this thinking is the Data Human Index.
The Index is a framework for evaluating how human-centred an organization’s data practices really are. It looks beyond performance and compliance to consider how data practices feel from the human side.
Dimensions such as transparency, consent, clarity, control, and empathy form the basis of that evaluation.
Rather than asking what companies are legally allowed to do with data, the Index asks whether their data practices align with human expectations, understanding, and trust.
The Index is evolving and shared openly as part of this project.
How to read this site
This site is not a finished framework.
It is a place to think in public, test ideas, and explore tensions that do not have simple answers. Some concepts will evolve. Others may change entirely.
The writing here reflects that process.
If you are interested in how data can be more transparent, more humane, and more aligned with human expectations, you are in the right place.
Let’s Work Together
Get in touch so we can start working together.
