Topographical Data Analysis for Enhanced Environmental Planning; A Virtue Ethics Analysis of the Development of Amazon’s Artificial Intelligence Hiring Tool

Fetea, Alex, School of Engineering and Applied Science, University of Virginia
Laugelli, Benjamin, EN-Engineering and Society, University of Virginia
Vrugtman, Rosanne, EN-Comp Science Dept, University of Virginia

My technical project and STS research are connected through the usage of artificial intelligence (AI), exploring the many roles that AI plays in our society, however, the focus of each project differs significantly. In the technical capstone, the project investigates the application of AI to enhance current agricultural practices and its contributions to environmental planning through the use of Topological Data Analysis (TDA) within hypergraph neural networks. This project specifically analyzes data analysis tools that can be used to improve sustainability and efficiency in farms in Washington State by providing more accurate data. Conversely, my STS research explores the ethical aspects of Amazon’s AI hiring tool. This research uses virtue ethics to analyze how the AI tool perpetuated societal biases rather than eliminate them. While both projects leverage AI, the overall theme reflects the impact of AI on society and the essential role of ethics in its development and deployment.
My technical project explores the idea of incorporating TDA into hypergraph neural networks. This method was created to tackle the complex, multidimensional data typically seen in agricultural datasets, specifically focusing on optimizing fallowing in Washington State. The project not only aims to improve current machine learning data analysis techniques through a novel approach, but also strives to make decision-making tools accessible to farmers, promoting sustainable farming practices. By improving existing models, the project aims to provide more accurate insights that could lead to better-informed decisions regarding fallowing land, potentially increased yields and reduced environmental impact.
The focus of my STS research was an ethical analysis of Amazon’s AI hiring tool, which was designed to automate Amazon's hiring process but instead reinforced gender biases due to flaws in the training of the model. This study used a virtue ethics framework to explore the moral issues in the AI tool, emphasizing the lack of commitment to objectivity, openness to correction, and seeing the “big picture” as well as the details of smaller domains. By exploring these ethical aspects, the paper sheds light on how AI can perpetuate rather than eliminate societal inequalities, leading to significant impacts on corporations and society.
Working on my capstone project and STS research paper together allowed me to make many interesting discoveries about the interplay of technology and ethics. In the technical capstone, I applied AI to improve agricultural planning by analyzing crop patterns, a project that significantly benefited from the ethical aspects of my STS research. This research focused on the downfall of Amazon's AI hiring tool, showing how without ethical oversight, AI can inadvertently perpetuate biases. These projects show the importance of incorporating ethical considerations into all aspects of technological development. In the future, I will ensure that the technologies I work on are not only technically correct but also morally acceptable. This balance is crucial, as I aim to develop technologies that are innovative and be mindful of their impact on society.

BS (Bachelor of Science)
Virtue Ethics, AI, Topographical

School of Engineering and Applied Science

Bachelor of Science in Computer Science

Technical Advisor: Rosanne Vrugtman

STS Advisor: Benjamin Laugelli

Technical Team Members: NA

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