Online Archive of University of Virginia Scholarship
Optimizing an ETL Pipeline From Multiple Angles; The Role of Ethical Design in Building Trust in Machine Learning Algorithms189 views
Author
Choksi, Akshay, School of Engineering and Applied Science, University of Virginia
Advisors
Seabrook, Bryn, EN-Engineering and Society, University of Virginia
Foley, Rider, Engineering and Society, University of Virginia
Vrugtman, Rosanne, EN-Comp Science Dept, University of Virginia
Abstract
My Capstone project's technical enhancements directly contribute to improving data accuracy, reliability, and real-time access for stakeholders within the bank. Simultaneously, my STS project's focus on ethical design principles ensures that these technological advancements are implemented in a manner that respects user privacy, promotes fairness in algorithmic decision-making, and fosters transparency in data handling practices. As a result, this portfolio provides methodology and research for both projects that contribute value to the machine learning (ML) industry. By integrating technical improvements with ethical considerations, the collective impact of these projects not only optimizes operations but also reinforces the bank's commitment to responsible and trustworthy data-driven strategies. Therefore, this STS Thesis builds a stronger foundation for leveraging advanced technologies, like machine learning, effectively, and promotes harmony between producers and end-users.
Degree
BS (Bachelor of Science)
Keywords
Ethical Design; Data Pipeline; Machine Learning; SCOT; AWS
Notes
School of Engineering and Applied Science
Bachelor of Science in Computer Science
Technical Advisor: Rosanne Vrugtman
STS Advisors: Rider Foley, Bryn Seabrook
Choksi, Akshay. Optimizing an ETL Pipeline From Multiple Angles; The Role of Ethical Design in Building Trust in Machine Learning Algorithms. University of Virginia, School of Engineering and Applied Science, BS (Bachelor of Science), 2024-05-07, https://doi.org/10.18130/rpcf-n607.
