Lulu's World

Image via marketoonist

Welcome to the start of my blogging journey. My name is Lulu Liu, and I am currently an undergraduate student at UC Davis majoring in Statistics and Computer Science. While I enjoy seemingly unrelated hobbies outside the classroom—like playing the violin, dancing, cooking, drawing, and more—my professional ambitions are rooted in statistical modeling and software engineering. In these fields, we spend an incalculable amount of time in R Markdown, Visual Studio Code, and the classical study method of furiously handwriting formulas and proofs to solve related problems. However, I have increasingly realized that solving the given academic prompts and questions is only half the battle.

Recently, I read Public Writing for Social Change by Ashley J. Holmes, which impacted how I view my responsibilities as a STEM student. Holmes challenges students to step outside the classroom and become “academic citizens”. This means taking the scholarly knowledge we learn in college and putting it into practical, civic use in our communities to promote social change. She notes that simply doing the work for the grade limits the potential, and that public writing has the power to leverage broader social movements. These points keep reminding me of the potential of my disciplines that I have not yet set foot in. In prevalent years, the tech industry has shaped almost every aspect of modern society, yet the systems and logic driving these changes are often locked behind the scene.

As I begin thinking about what this blog could become, a few topics have stood out to me as areas where public writing could make a real difference. The gap between what experts know and what everyday people understand is not wide, but significant. Too often, people write off such mathematical and technical fields as overly nerdy, incomprehensibly dense, or simply irrelevant to their daily lives. In fact, almost every peer I’ve spoken to outside of similar majors has confessed that they would avoid taking a statistics or coding class at all costs. These are issues I want to test my voice on, and where I believe translating technical knowledge into accessible language is not only useful, but overdue. Here are a few possible topics I may cover in the coming weeks:

• Algorithmic Bias in Everyday Tech: Algorithms dictate everything from the social media content we consume to the loan approvals we receive. But how neutral is this math? I’d like to explore how algorithmic bias fundamentally alters our digital experiences, rewording the underlying statistics so consumers understand what these systems actually mean for them.
• Data Privacy and the Illusion of Anonymity: With the vast amounts of data collected by applications and websites, true anonymity is rapidly becoming a myth. I want to research current legislative and ethical issues in digital privacy and write accessible guides for non-technical users. We cannot simply ignore the current invasive tracking standards.
• The Hidden Costs of AI Training Data: As machine learning models become more prevalent, the datasets used to train them are under scrutiny. I plan to look into the underground race to acquire AI training datasets and explore how the demand for massive data impacts creators without deviating too much from the core technical realities.

Image via Randall Munroe