In his July 31, 1996 remarks on welfare reform, President Clinton signaled his intent to sign into law the Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA), bipartisan legislation aimed at reforming federal welfare policy. During the press conference, Clinton framed welfare as necessary but ultimately temporary relief, stating its...
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DEDICATION
In memory of Robert Iltis—scholar, mentor
In an increasingly computation-driven world, algorithms and mathematical models significantly impact decision making across various fields. To foster trust and understanding, it is crucial to provide users with clear and concise explanations of the reasoning behind the results produced by computational tools, especially when recommendations appear counterintuitive. Legal frameworks in...
This thesis is an IRB-exempt oral history focused on the non-profit Corvallis Multicultural Literacy Center (CMLC) in Corvallis, Oregon. The CMLC, formerly on 9th Street, was known to many community members as the Yellow House. The Yellow House was a dedicated community-based space where people of all cultures could come...
The advancement of artificial intelligence (AI) has led to transformative developments across multiple sectors, fostering innovation and redefining our interactions with technology. As AI matures and becomes integrated into society, it offers numerous opportunities to address global challenges and revolutionize a wide array of human endeavors. These advances are driven...
Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
This dissertation delves into understanding, characterizing, and addressing dataset shift in deep learning, a pervasive issue for deployed machine learning systems. Integral aspects of the problem are examined: We start with the use of counterfactual explanations in order to characterize the behavior of deep reinforcement learning agents in visual input...