Abstract
Throughout time, technological advancement has come at a price of concealing the exploitation involved beneath the veil of innovation. The foundation of The University of Virginia was built through enslaved labor, and even after the construction, harbored years of segregation. This university parallels the hidden costs that sustain artificial intelligence - both infrastructures were built on the basis of inequity, with hard labor and the stealing of resources. My prospectus aims to explore the depths to which inequitable labor has affected our modern day world, along with exploring how these issues can be addressed in a sensitive way.
This delves into my technical topic, which concerns AR (Augmented Reality) and its place in education. The history of The University of Virginia has deep ties with racial segregation, exclusion, and the exploitation of enslaved people - this aspect of our school’s history is emotionally charged, and potentially difficult for students to learn about.
My technical project aims to create a bridge for this gap by introducing an Augmented Reality application, to provide a tool for students to use to learn about our school’s history. Our goal is to balance communicating difficult historical topics with maximizing user engagement.
Prior research shows that AR is capable of conveying cultural heritage in a sensitive yet effective way, as seen through applications made for medical staff (Srdanović et al., 2025; Pimentel et al., 2020). My question is the following: Can AR be used as a tool for ethical historical education, bringing forward university-specific historically charged topics?
My STS research aims to examine the effects of AI workloads (large-scale computational operations needed to train and run machine learning models) exacerbate global inequities and existing geopolitical tensions.
For example, Africa and South America bear the largest loads pertaining to rare-earth mining - this often leads to local communities being harmed by being forced into displacement. Meanwhile, economically rich countries such as those in North America and the European Union enjoy the benefits of AI and the datacenters, without the harm of environmental consequences and displaced communities. This uneven impact exacerbates global inequalities, especially with economically rich and poor countries (Kansal & Kansal, 2025). My STS research question is the following: How are AI’s demands for material and energy intensifying existing geopolitical and regional inequalities?
The history of The University of Virginia and modern artificial intelligence both highlight how progress often relies on hidden inequalities concerning labor and resources. My research confirms the parallels between labor exploitation for building UVA, and the same exploitation for resource mining to maintain modern technology systems. These parallels urge us to reconsider how we define innovation - we must not only consider its efficiency or output, but by its ethics. Addressing these problems does not only requires guardrails, but a deeper look into the advancement of technologies, and the uncomfortable aspects of innovation that are often overlooked.
