Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 22 for “"Algorithmic Bias"”.
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Identifying, Measuring, and Addressing Algorithmic Bias in AI Admission Systems for Graduate Education
… volume of applications, it is prone to data and algorithmic bias, which can lead to unfair outcomes for underprivileged subgroups among applicants. Recent changes in legislation such as the ban of affirmative action by the U.S. Supreme Court make it increasingly relevant to study the demographic …
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Evaluation of Biases That Challenge the Implementation and Use of Machine Learning Clinical Decision Support Tools
… the presence and causes of sociodemographic bias in clinical ML algorithms. It found that algorithmic bias evaluations are infrequently performed, that algorithmic bias is often present, and that addressing algorithmic bias requires an approach tailored to the specific ML model and …
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Artificial intelligence (AI) in the public service: Public administrator perspectives on leveraging AI to support citizen and stakeholder engagement
… expressed around data privacy, data security, algorithmic bias, and the reliability of outputs from machine analysis. A lack of AI literacy, risk-averse public sector cultures, and dated IT infrastructures were seen as key barriers. Participants emphasized: the need for continued human …
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Uncommon pasts converging in the digital present: Constructions of gender and race in the era of airport security
… management is widespread. This is called algorithmic governance, where algorithms are used in decision making processes that govern the functioning of our society. While this technology is constantly being innovated upon, serious questions regarding algorithmic bias are gaining traction. …
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Human As We All Are: Posthuman Subjectivity in The Paper Menagerie and The Three-Body Problem
… magnifies humanity through the effects of algorithmic bias. Throughout the collection, Liu’s stories communicate with one another through “questions” and “answers” about humanism. Chapter Two focuses on how representations of virtual reality and BCI in Cixin Liu’s <em>The Three-Body …
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Artificial Intelligence in 2024: A Thematic Analysis of Media Coverage
… centered on disinformation, job displacement, algorithmic bias, environmental costs, and existential risk. Results suggest that U.S. legacy media have moved beyond early techno-optimism towards a more nuanced discourse that simultaneously fuels investment and adoption, demands regulation and …
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Art, Authorship, and Artificial Intelligence
… I show that by deploying a technique I call bias-prompting, artists are able to exploit the algorithmic bias of AI systems to generate artworks that possess an aesthetic feature I call misalignment. I then consider whether AI is an artistic medium or artform and argue that AI is the vehicle …
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Leveraging blockchain and artificial intelligence for enhanced copyright enforcement in South Africa
… accessibility concerns, non-compliance, and algorithmic bias. These issues necessitate innovative solutions to protect intellectual property rights effectively. With its decentralised and immutable nature, blockchain technology offers promising solutions for transparent and efficient …
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Impact of personalization on businesses and their stakeholders
… individual users through data-driven models and algorithmic decision-making — has become a strategic axis for contemporary European firms, promising enhanced engagement, increased efficiency, and new pathways for value creation. This dissertation investigates the multifaceted economic, …
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Organizational Decision-making in the Age of Big Data and Artificial Intelligence
… This study contributes to extant literatures on algorithmic decision-making and automation by moving beyond only examining individual decision-makers’ attributes to examine the intertwined roles of organizational factors and AI’s characteristics. The results show that when firms implement …
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Creative AI Literacies for Families
… technologies in the home are prone to algorithmic bias and cyber-security attacks. To ensure the new generations of children growing up with AI can develop a critical understanding of AI technologies, we must explore parents' roles in helping their children develop AI literacies and …
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Utilizing facial scanning to screen for fetal alcohol spectrum disorder in South Africa
… datasets and the associated risk of algorithmic bias. OHPs demonstrated both the capability and willingness to participate in FASD screening, provided that adequate training and systemic support are in place. The curriculum review further revealed a marked lack of FASD and …
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Needs-driven, utility-oriented, standards-based operationalization of artificial intelligence for clinical decision support: a framework with application to suicide prevention
… user interfaces), model formulation (e.g. algorithmic bias, limited practical utility, trustworthiness or interpretability), and workflow context (e.g. a lack of integration into existing workflows; limited actionability). Critically, AI projects must demonstrate overall utility, balancing …
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Improved integration of information to reduce subsurface model bias
… data-related issues like cognitive and sampling biases, and model-related challenges including statistical assumptions, misspecification, and algorithmic biases. These challenges introduce four critical implications during subsurface modeling. Firstly, subsurface sampling is subject to sampling …
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Examining teacher and learner perceptions on the ethical challenges of generative AI (gen AI) in transforming teaching and learning practices : a mixed methods study
… in education increasingly address issues such as algorithmic bias, data governance, academic integrity, and educational equity, these discussions are predominantly framed through a Higher Education (HE) lens. As a result, the ethical implications of GenAI within FE remain underexplored. This study …
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Context-conscious fairness throughout the machine learning lifecycle
… on how to define, test for, and mitigate unfair algorithmic bias. One key obstacle is the disparity between academic theory and practical and contextual applicability. The unambiguous formalisation of fairness in a technical solution is at odds with the contextualised needs in practice. The …
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Advancing Internet Viewpoint Diversity: A Novel Algorithm and a Corpus Creation Tool
… and worries surrounding filter bubbles and algorithmic bias, this research presents a novel tool for constructing internet-based topical corpora and an algorithm tailored for viewpoint detection and the curation of diverse search results.Following a comprehensive exploration of viewpoint …
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Machine Learning Approaches for Equitable Healthcare
… data we collect can be noisy, incomplete, and biased, seemingly straight-forward implementation of existing methods for clinical intervention or better understanding human knowledge can lead to inaccurate and inequitable clinical algorithms. To begin to address these challenges, we need new …
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Understanding User and Investor Perspectives on Robo-Advisors Adoption in Fintech
… (LLMs) in Robo-advisors, especially around algorithmic bias and privacy consent. This dissertation makes multiple theoretical and practical contributions. It advances the academic understanding of FinTech adoption by proposing an integrative adoption framework grounded in both user behavior …
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