But the longer I worked in Machine Learning, the more I realized that building models that work is only half the fun. The really good stuff is when you realize you're building systems deeply entwined with messy, beautiful, human life. This is where my love for code met my deep interest in philosophy.
This isn't an academic paper — think of it more as a quiet moment of reflection.
The Turning Point: When a Chatbot Needed a Conscience
My "lightbulb moment" happened while developing an AI Chatbot for Dengue Symptom Triage in Bangladesh. On the surface, the project was straightforward: use a Decision Tree Classifier to help people quickly assess symptoms.
But as I worked on feature prioritization and handling contradictory inputs, the technical task morphed into an ethical one. A low-income person might downplay a symptom to avoid clinic costs, or a non-native speaker might struggle to articulate their discomfort. The cost of a false negative was immense.
It wasn't just about minimizing False Negatives; it was about ensuring the system didn't dismiss the testimonial of someone whose data profile was statistically unusual.
Finding Philosophical Anchors
I found incredible clarity in the concept of epistemic injustice, championed by philosopher Miranda Fricker. She describes this as harm done to someone in their capacity as a knower when their credibility is unfairly discounted.
Suddenly, the chatbot's failure wasn't just a misclassification error. It was a potential act of testimonial injustice.
"When a model confidently classifies or reroutes based on demographic features, isn't it making epistemic judgments? Some voices are 'heard' more clearly by the model; others are marginalized."
This insight has been humbling. It forces me to think beyond simply minimizing error.
Why This Intersection Sparks Me
- Real Impact, Real Responsibility: My work isn't just about building "more accurate models." It's about building just models.
- Growth Beyond the Code: Learning philosophy stretches me in ways that model-building alone never could.
- A Vision for Better Systems: I dream of systems that don't just predict, but understand in a human-sensitive way.
Looking Forward: Building With Conscience
As I move forward, I feel more grounded in my identity: not just as a researcher or engineer, but as a philosophically informed technologist. I care deeply about asking the right questions and making sure that, when AI touches people's lives, it does so with humility, fairness, and respect.
I'm excited to continue this work — using data science not just to optimize outcomes, but to elevate dignity.