“Mystery creates wonder, and wonder is the basis of man’s desire to understand.”
— Neil Armstrong
I still remember the first time I tried building a model to predict how people would behave in a high-stakes decision - think major financial moves or life-changing career choices. The data was massive, my algorithms well-tested, and the compute power practically humming with possibility. Yet, no matter how polished my approach became, there was always this uncanny gap between the data-driven “probability” of what someone might do and the murky realm of what they actually chose. It was both fascinating and frustrating. Call it the aggregation of quantum uncertainty at the macro level, or maybe just something more profound—something that hints at free will.
That realisation hit me hard: data science can estimate with astonishing accuracy, but it will never fully capture the unpredictable spark that makes us human. And honestly? That gap became the most interesting part of the whole process.
It also forced me to question my assumptions—not just about model performance or statistical significance, but about the nature of choice itself. Why did this unpredictable element linger stubbornly out of reach? I started turning to my faith, searching for answers in a place far removed from data lakes and regression lines. Surprisingly, it wasn’t a clash. Faith didn’t stifle my curiosity; it expanded it, offering a way to understand those hidden aspects of personhood, morality, and purpose that numbers couldn’t quite pin down. My work shifted from simply refining predictions to exploring the beautiful, elusive space where logic ends, and wonder begins.
Data Science Meets Faith: A Surprising Convergence
“Not everything that can be counted counts, and not everything that counts can be counted.”
— William Bruce Cameron
Data science thrives on what we can measure. Questions like, “Is this model accurate?” or “Does the data support our hypothesis?” are its bread and butter. But even the best-trained models have their limits. There are always confidence intervals, error margins, and the unquantifiable unknowns that keep us humble.
Faith, on the other hand, starts in the opposite place—with the unknowable. It’s about belief, trust, and hope—qualities that don’t fit neatly into an algorithm. At first glance, the two seem like polar opposites: data science demands proof, while faith leans into mystery.
But here’s the thing. The deeper I dove into data science, the more I realised that more data doesn’t always mean more certainty. Outliers, exceptions, and the trailing edges of probability remind us of the limits of what we know. Meanwhile, faith—starting in the intangible—often becomes an anchor of firm conviction. It’s like they meet in the middle: one starts with evidence and bumps into mystery; the other starts with mystery and leads to assurance.
Why This Matters in the Modern World
“The real problem is not whether machines think but whether men do.”
— B.F. Skinner
We’re living in an era where AI is advancing faster than we can sometimes process. With it comes a slew of moral questions: Who decides how data is gathered and used? How do we prevent bias in machine learning models from unfairly affecting entire communities? Where’s the line between personalised convenience and invasive privacy breaches?
These aren’t just puzzles for AI researchers; they’re deeply human questions. They touch on fairness, dignity, and the kind of world we want to create. And honestly? Having a framework of values—whether rooted in religious faith or a broader moral philosophy—is more important than ever.
For example, when designing AI systems, an ethical compass could push us to ask hard questions: Does this facial recognition tool inadvertently discriminate against certain groups? Are our data monetisation practices aligned with respecting individual privacy? These aren’t barriers to progress; they’re signposts pointing us toward innovation that serves humanity.
Take the controversies around facial-recognition software. Studies have shown that these systems can struggle with darker skin tones, leading to wrongful arrests and systemic inequities. By engaging our ethical sensibilities early, we can address these blind spots and create technology that genuinely enhances human well-being. It’s not about stalling progress—it’s about making progress more human.
What’s Next?
In the coming weeks, I’ll explore these intersections of faith, ethics, and technology. Expect deep dives into thorny topics like algorithmic bias or the moral weight of data privacy, mixed with lighter pieces—perhaps a satirical cartoon poking fun at the quirks of a data scientist’s life.
Some posts will be short reflections, perfect for a coffee break. Others will be more in-depth essays to challenge your thinking. Along the way, I’ll share personal anecdotes and stories to keep things grounded.
Let’s Talk
I’d love for you to join this journey. If you haven’t already, subscribe, share your thoughts, or throw in a question—especially if you’re juggling logic and belief in your own life. Together, we’ll navigate this fascinating space where data science meets faith, and maybe even learn to love the view.
“We are our choices.”
— Jean-Paul Sartre