Online Archive of University of Virginia Scholarship
Serverless Image Classification: Implementing a Competing Consumers Architecture for Scalability; Digital Gatekeepers: A Sociotechnical Analysis of Algorithmic Bias in Corporate Hiring8 views
Author
He, Michael, School of Engineering and Applied Science, University of Virginia
Advisors
Francisco, Pedro Augusto, EN-Engineering and Society, University of Virginia
Vrugtman, Rosanne, EN-Comp Science Dept, University of Virginia
Abstract
As digital transformation accelerates, the immense scale of modern computation
promises unprecedented efficiency but simultaneously threatens to encode human limitations
into the systems that govern our lives. My technical capstone project, “Serverless Image
Classification: Implementing a Competing Consumers Architecture for Scalability,” details the
re-architecture of an Amazon Web Services digital asset management system. The research was
undertaken to solve severe bottlenecking and timeout failures encountered when classifying a
massive batch of 50,000 images using a synchronous, monolithic serverless pipeline. My STS
research paper, “Digital Gatekeepers: A Sociotechnical Analysis of Algorithmic Bias in
Corporate Hiring,” investigates how automated artificial intelligence systems codify and amplify
historical prejudices. This research was conducted to critique the rapid, unregulated deployment
of opaque hiring algorithms that prioritize corporate efficiency over demographic equity and
procedural justice. These two projects are fundamentally connected by their shared focus on the
implications of deploying highly scalable, automated systems in high-stakes corporate
environments. While my technical project seeks to optimize computational scalability to
eliminate system failures, my STS research questions the social cost of that very efficiency,
warning against scaling unexamined automated processes without ensuring transparency and
human accountability.
Degree
BS (Bachelor of Science)
Keywords
AWS; Competing Consumers Pattern; Algorithmic Bias; AI Corporate Hiring
Notes
School of Engineering and Applied Science
Bachelor of Science in Computer Science
Technical Advisor: Rosanne Vrugtman
STS Advisor: Pedro Augusto Francisco
Technical Team Members: Michael He
He, Michael. Serverless Image Classification: Implementing a Competing Consumers Architecture for Scalability; Digital Gatekeepers: A Sociotechnical Analysis of Algorithmic Bias in Corporate Hiring. University of Virginia, School of Engineering and Applied Science, BS (Bachelor of Science), 2026-04-29, https://doi.org/10.18130/th7q-hf64.
