System Reboot
Reframing the Code to Build Better
Thesis Statement
Design, AI, and data are deeply interconnected, continuously shaping technology and society. While AI and data are typically developed through a linear lens—driving modern innovations and societal shifts—this approach often overlooks the complexity and diversity of our world. Exploring how these systems reshape society and reimagine what they could become if built with a more inclusive and representative foundation. By examining transparency in data ownership and the impact of diversity in AI development, I challenge traditional methodologies and unlock the full potential of these systems through a nonlinear, more equitable approach.
Abstract
As a woman, designer, and researcher, I approach the intersection of design, artificial intelligence, and data with a critical understanding of how these systems shape technology, culture, and creative expression. I investigate AI not only through its outputs, but through its inputs—the prompts, tones, and datasets that inform what is created, for whom, and why.
Traditional AI development often relies on rigid, linear methodologies that overlook the nuance, complexity, and lived experiences of women and other underrepresented identities. In response, I propose a more inclusive, nonlinear framework—one rooted in transparency, diverse data ownership, and ethical design. I explore how identity, authorship, and access influence creative outcomes and imagine how AI systems can evolve when more perspectives are integrated from the ground up. As machine learning tools continue to advance, I encourage designers and technologists to recognize their responsibility in shaping more equitable and inclusive systems.
By centering representation, education, and accountability, I envision a future where AI empowers a broader spectrum of creative voices and contributes to meaningful, transformative change.
Relevance
The urgency of this work lies in the rapid evolution of our world, and at the heart of it, design. Design isn’t just reacting to change; it’s shaping it. It influences how we see, who is seen, and what stories get told. As a woman in this space, I’m driven to question who holds the power behind our systems—who’s training the algorithms, whose data is prioritized, and whose realities are left out. This isn’t just about technology but visibility, ownership, and accountability.
In a landscape dominated by linear thinking and homogenous voices, I challenge traditional practices by centering lived experiences, especially those shaped by gender and identity. Design is a transformative tool that can be reimagined through nonlinear, inclusive approaches that elevate diverse narratives and redefine what progress looks like. This moment calls for bold rethinking, and I believe women’s voices, creativity, and critical perspectives are essential to shaping a more just and representative future.
Methodology
I use a critical, feminist, and design-driven approach to examine how artificial intelligence, data, and design shape culture, identity, and power. Instead of viewing AI systems as neutral, I focus on the inputs—data sources, authorship, and ethical frameworks—that influence their outcomes. Through inclusive design and practice-based research, my thesis contributes to a growing movement reimagining AI as more accountable, ethical, and human-centered.