Information Management & Technology
Honors Thesis Faculty Advisor: Jennifer Stromer-Galley
Algorithmic Bias and Its Implications: How to Maintain Ethics in AI Governance
This thesis project is intended to consider bias in artificial intelligence (AI). This paper will explore how AI bias occurs through a technical explanation of AI. In particular, this thesis seeks to understand the implications of AI bias when utilized in the public sector in AI Governance. To advance an understanding of bias in AI governance, I developed a framework to analyze and critique potential faults of AI development, use, and regulation, particularly in the United States. My findings support AI governance with caution. With safeguards and regulatory policy stemming from a federal and state level, AI can be safely implemented in government with less risk of bias harming or excluding marginalized groups. These conclusions were developed through assessing comparative government frameworks within the United States and beyond, conversations with field experts, and reading academic papers and literature from government and non-government organizations.
Links to Project Materials:https://s3.amazonaws.com/files.formstack.com/uploads/4336933/108624839/806709365/108624839_ruby_isley_senior_honors_capstone.doc