Browsing by Author "Johnson, Sylvester A."

Now showing 1 - 8 of 8
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    Belief, Values, Bias, and Agency: Development of and Entanglement with "Artificial Intelligence"
    Williams, Damien Patrick (Virginia Tech, 2022-08-15)
    Contemporary research into the values, bias, and prejudices within "Artificial Intelligence" tends to operate in a crux of scholarship in computer science and engineering, sociology, philosophy, and science and technology studies (STS). Even so, getting the STEM fields to recognize and accept the importance of certain kinds of knowledge— the social, experiential kinds of knowledge— remains an ongoing struggle. Similarly, religious scholarship is still very often missing from these conversations because many in the STEM fields and the general public feel that religion and technoscientific investigations are and should be separate fields of inquiry. Here I demonstrate that experiential knowledge and religious, even occult beliefs are always already embedded within and crucial to understanding the sociotechnical imaginaries animating many technologies, particularly in the areas of "AI." In fact, it is precisely the unwillingness of many to confront these facts which allow for both the problems of prejudice embedded in algorithmic systems, and for the hype-laden marketing of the corporations and agencies developing them. This same hype then intentionally obfuscates the actions of both the systems and the people who create them, while confounding and oppressing those most often made subject to them. Further, I highlight a crucial continuity between bigotry and systemic social projects (eugenics, transhumanism, and "supercrip" narratives), revealing their foundation in white supremacist colonialist myths of whose and which kinds of lives count as "truly human." We will examine how these myths become embedded into the religious practices, technologies, and social frameworks in and out of which "AI" and algorithms are developed, employing a composite theoretical lens made from tools such as intersectionality, ritual theory, intersubjectivity, daemonology, postphenomenology, standpoint epistemology, and more. This theoretical apparatus recontextualizes our understanding of how mythologies and rituals of professionalization, disciplinarity, and dominant epistemological hierarchies animate concepts such as knowledge formation, expertise, and even what counts as knowledge. This recontextualization is then deployed to suggest remedies for research, public policy, and general paths forward in "AI." By engaging in both the magico-religious valences and the lived experiential expertise of marginalized people, these systems can be better understood, and their harms anticipated and curtailed.
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    Civil War Twin: Exploring Ethical Challenges in Designing an Educational Face Recognition Application
    Kusuma, Manisha (Virginia Tech, 2022-01-06)
    Facial recognition systems pose numerous ethical challenges around privacy, racial and gender bias, and accuracy, yet little guidance is available for designers and developers. We explore solutions to these challenges in a four-phase design process to create Civil War Twin (CWT), an educational web-based application where users can discover their lookalikes from the American Civil War era (1861-65) while learning more about facial recognition and history. Through this design process, we synthesize industry guidelines, consult with scholars of history, gender, and race, evaluate CWT in feedback sessions with diverse prospective users, and conduct a usability study with crowd workers. We iteratively formulate design goals to incorporate transparency, inclusivity, speculative design, and empathy into our application. We found that users' perceived learning about the strengths and limitations of facial recognition and Civil War history improved after using CWT, and that our design successfully met users' ethical standards. We also discuss how our ethical design process can be applied to future facial recognition applications.
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    The Craft of Violence: A Posthuman Patchwork of Technological Interrelations
    Fox, Alice Quinn (Virginia Tech, 2023-05-04)
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    Designing Human-AI Collaborative Systems for Historical Photo Identification
    Mohanty, Vikram (Virginia Tech, 2023-08-30)
    Identifying individuals in historical photographs is important for preserving material culture, correcting historical records, and adding economic value. Historians, antiques dealers, and collectors often rely on manual, time-consuming approaches. While Artificial Intelligence (AI) offers potential solutions, it's not widely adopted due to a lack of specialized tools and inherent inaccuracies and biases. In my dissertation, I address this gap by combining the complementary strengths of human intelligence and AI. I introduce Photo Sleuth, a novel person identification pipeline that combines crowdsourced expertise with facial recognition, supporting users in identifying unknown portraits from the American Civil War era (1861--65). Despite successfully identifying numerous unknown photos, users often face the `last-mile problem' --- selecting the correct match(es) from a shortlist of high-confidence facial recognition candidates while avoiding false positives. To assist experts, I developed Second Opinion, an online tool that employs a novel crowdsourcing workflow, inspired by cognitive psychology, effectively filtering out up to 75% of facial recognition's false positives. Yet, as AI models continually evolve, changes in the underlying model can potentially impact user experience in such crowd--expert--AI workflows. I conducted an online study to understand user perceptions of changes in facial recognition models, especially in the context of historical person identification. Our findings showed that while human-AI collaborations were effective in identifying photos, they also introduced false positives. To reduce these misidentifications, I built Photo Steward, an information stewardship architecture that employs a deliberative workflow for validating historical photo identifications. Building on this foundation, I introduced DoubleCheck, a quality assessment framework that combines community stewardship and comprehensive provenance information, for helping users accurately assess photo identification quality. Through my dissertation, I explore the design and deployment of human-AI collaborative tools, emphasizing the creation of sustainable online communities and workflows that foster accurate decision-making in the context of historical photo identification.
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    Ensuring Scholarly Access to Government Archives and Records
    Ingram, William A.; Johnson, Sylvester A. (Virginia Tech, 2022-01-31)
    This report summarizes the activities and outcomes of a collaborative planning project supported by The Andrew W. Mellon Foundation and organized by University Libraries at Virginia Tech, in collaboration with Virginia Tech Center for Humanities and the National Archives and Records Administration (NARA). A diverse group of archivists, librarians, humanists, technologists, information scientists, and computer scientists were convened for a five-part online workshop series to discuss and plan how artificial intelligence and machine learning could be used to ensure public access to the massive and ever-growing collection of government records in the NARA digital catalog. During the workshop, participants identified requirements, developed conceptual models, and discussed a work plan for a subsequent pilot project that would apply state-of-the-art tools and technologies to increase the effectiveness of archival programs and broaden public access to the important content in the NARA catalog. The workshop focused on humanistic and equitability issues of artificial intelligence and developing ethical, human-centered technology that promotes the public good. As such, the topic of intentional mitigation of AI bias was a thread that ran through the entirety of the workshop.
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    Hip Hop, Bluegrass, Banjos, and Solidarity: Race and Class Histories in Appalachia U.S.A
    Salmons, Patrick Jeremiah (Virginia Tech, 2021-06-10)
    This dissertation examines the historical race and class tensions across the United States, and particularly focuses on Appalachia as a potential place of resistance against racial and class injustice. Arguing for a thick cross-racial solidarity movement, I examine the history of Black oppression from slavery to current modes of oppression such as mass incarceration and colorblind constitutionalism. The presence of anti-Black racism and under acknowledgement of whiteness hinders any form of cross-racial solidarity. To combat this, I ask, are the genres of hip hop, bluegrass, and country able to provide a reckoning of the continual racial oppression of Black people and an acknowledgement of whiteness, in Appalachia and the U.S.? I examine the historical progression of bluegrass and country, and hip hop, through the history of the banjo and music industry. The banjo, an African instrument, links Appalachia with histories of both Black expression and racial oppression. From here, I argue that the history of the music industry provides a further understanding of racial injustice that is parallel to the instances of institutional racial injustice in the U.S. This history provides evidence that Black artists used their music to enable social movements and resistance against systemic racial injustice in the U.S. Throughout several chapters, I analyze the many untold, forgotten, and hidden histories of Black racial violence that exists in the U.S. and Appalachia, and how music operates as a tool of resistance that can enable Black liberation against racial injustice. Through an examination of racial injustice in my hometown of Martinsville, Virginia, and using music as a tool, I suggest that, a thick cross-racial solidarity can exist with a recognition of historical racial injustice against Blacks, both locally and nationally, an acknowledgment of whiteness, an anti-racist framework for community activism, and a centering of Black voice, narrative, and Black liberation.
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    Synthetic Women: Gender, Power, and Humanoid Sex Robots
    Wenger, Sara Elizabeth II (Virginia Tech, 2023-05-16)
    Drawing from gender studies, cultural studies, and feminist technoscience literature, this dissertation employs an interdisciplinary approach to analyze the androcentric imaginaries through which humanoid sex robots ("sexbots") emerge. Specifically, I utilize sexbots to interrogate and reflect on issues such as consent, whiteness, and humanity. By situating sexbots as proxies for feminized and racialized humans, I argue that the production, portrayal, and proliferation of sexbots are reflections of how we treat marginalized people, reifying existing hierarchal power relations. This project begins by analyzing the creation and dissemination of sexbots by popular sex technology ("sextech") companies. Critically surveying published papers, interviews, and research from various sexbot texts, I attend to gendered and racialized discourses of sexbot consent and companionship in human-sexbot relationships. Next, I analyze the overwhelming presence of whiteness with/in sexbots, exploring how anti-Black racism manifests in sexbots, and underscoring how both the present and "future" of sextech remains rooted in the past. Then, I catalog and dissect the published materials and interviews of prominent sextech creators, critically juxtaposing the marketing discourses of sexbots and evincing how both the sextech elite and science journalists—specifically writers I refer to as "sexbot journalists"—influence, change, and inform the meanings of sexbots. Finally, I turn to robots and robot alternatives found in feminist speculative fiction, utilizing these stories as a way of looking elsewhere in order to theorize what is possible for sexbots as well as our (current and future) relationships to these emerging technologies. At its core, this dissertation is an invitation to question white heteropatriarchy mediated through the controversial existence of sexbots. While synthetic women are the ostensible "subjects" of investigation—as well as commodities exchanged by creators and subsequently praised by enthusiasts—it is the "real" feminized and racialized humans who lie at the heart of this project. Through a much-needed feminist intervention, this project offers an in-depth analysis of humanoid sex robots and what they reveal about violence and power in the world around us.