When Bias Brings Silence, I Chose to be a New Voice

by Hosna Safiarian – Instructor, Data Science and Machine Learning, RRC Polytech

In the world of technology, bias is not just a statistical error or a flaw in an algorithm. Bias is the absence of voices that deserve to be heard. When data is unequal, decisions become unequal too and that imbalance gradually turns into silence, excluding half of society from shaping, innovating, and building the future.

I know that silence well. I’ve experienced it many times throughout my professional journey but instead of accepting it, I chose to be a new voice.

My journey began when I was just thirteen. Alongside a team of girls, I won a national programming competition at a time when seeing girls in such spaces still felt rare and unusual.

That moment sparked a flame in me, one that led me to pursue a degree in Information Technology in Iran.

Very quickly, I realized that the lack of diversity in classrooms and teams wasn’t just a surface-level observation, it was systemic bias. And when left unchecked, bias grows roots: in unfair decisions, in one-sided designs, and in structures that fail to reflect the whole of society.

Those experiences led me to data science. Not just to analyze numbers, but to bring back the voices that had been left out of the data for far too long.

Along this path:

• I’ve published over 15 academic papers in artificial intelligence and data science,
• Volunteered in girls’ schools to teach computer science and make knowledge more accessible,
• Translated technical IT resources into Persian to break down language barriers,
• And led several high impact fintech projects with the belief that knowledge, when not accessible to all, cannot deliver justice.

In my work, I’ve used the power of data to demonstrate one thing clearly: when we remove bias from decision-making, we don’t just restore fairness, we unleash innovation, profitability, and belonging.

In redesigning a banking application, data revealed that every major decision had been based solely on male user behavior. By introducing insights from female users, I balanced the user experience and created a product that served all users which led to a significant increase in engagement and financial transaction volume.

In analyzing hiring processes, I discovered that roles and opportunities were often unconsciously distributed based on gender stereotypes with certain positions assumed to be for men and others for women, regardless of actual skills. Through data-driven evaluation systems, I helped challenge those assumptions and build fairer pathways for recruitment and advancement resulting in greater diversity and innovation within tech teams.

In a social impact project, I used labor data to show that simply implementing policies like flexible working hours and childcare support could dramatically increase women’s retention in the workplace a benefit not only for women, but for the entire economy and society.

And that was just the beginning. Every project I led wasn’t just a technical achievement, it was a step toward change, balance, and human progress.

Today, as a data science instructor in Canada at RRC Polytech, I am proud to see more and more girls sitting alongside boys in my classrooms. It means the voices once ignored are now being heard, voices rooted in data, analysis, courage, and awareness.

And my mission is clear: To inspire, educate, and support women who don’t just want a seat at the table in tech, they want to redesign the table.

If bias is a silence in the data, I chose to be the voice that breaks it.