This dissertation seeks to identify an ecology of knowledge to serve as a theoretical lens for understanding the state of the electronic waste management industry in the United States. Semi-structured interviews of stakeholder groups such as e-waste recyclers, manufacturers, government agencies, refurbishers, and other interested organizations were used to determine the current status of used electronics management in the US. The focus is on how the electronics reuse and recycling industry is being affected by the rapid changes in consumer electronic device technology as well as the lack of recycling infrastructure, insufficient consumer engagement with electronics reuse and repair, and inconsistent regulation. The stakeholders which are being impacted by the changing industry are also participating in shaping it either in terms of initiating the changes, or in how they are reacting and adapting to them. Furthermore, electronics reuse and recycling have been widely considered two aspects of the same industry despite increasing evidence of bifurcation and competition for material flows. Based on stakeholder response, the ecology of knowledge that exists within this industry suggests that recyclers should shift their business to incorporate more repair and resale in addition to recycling to remain profitable. Case studies involving participant observation, additional semi-structured interviews, and policy comparisons were utilized to serve as representations for the three primary stakeholder groups: electronics recyclers, electronics refurbishers, and government agencies regulating electronics recycling and e-waste disposal. These three stakeholder groups and their ability to capture electronics at the end of their useful life drive the percentage of discarded electronics which are recycled or reused. The used electronics infrastructure, institutions, and stakeholder networks along with the knowledge generated within make-up an ecology of knowledge which explains how changes in newer consumer electronic devices are antagonistic to recycling systems couched in a slow-to-change scrap industry. Intellectual property laws prevent the repair and reuse of used electronic devices. Finally, inconsistent, patchwork e-waste recycling laws do not sufficiently capture used electronics at the end of their useful life. These factors have had a significant impact on the larger socio-technical system of end-of-life consumer electronic device management in the United States.

There is a lack of prior research about factors and conditions relating to the underdevelopment of infrastructure on Navajo Nation, especially from a community-centered perspective. As a Diné researcher, the intersection created via the fields of Science and Technology Studies (STS), American Indian Studies (AIS), and Diné Studies creates a means by which developmental policy and futures planning can be discussed. Through qualitative inquiry, specifically cross-case analysis, oral histories, and archival review from a Diné perspective, this work establishes the relationship between roads, energy, and Information and Communication Technologies (ICTs) in the Navajo Nation in relation to the historical underdevelopment of infrastructure on the reservation, especially from 2000 to 2020. Roads and energy infrastructures make way for ICT deployments, and together, these three infrastructures shape futures planning for the Nation, including governance decisions relating to partnerships, and internal versus external development. Relationships between infrastructural efforts, past colonial practices of the United States (U.S.), and relations between the U.S. and tribes during this era shape the development of relevant expertise within Navajo Nation entities and also impact access to and uses of significant funding opportunities available via the early 21st century American Recovery and Reinvestment Act. A Diné-centered concept of care through long-term infrastructure deployment relates tribal sovereignty and Indigenous ways of knowing to Indigenous Science and Technology Studies (STS) and suggests new directions for applied Diné studies in the field of Indigenous STS.

ABSTRACTThis dissertation addresses two pivotal challenges within the US technology industry: racial equity and the rise of artificial intelligence (AI). It investigates whether the integration of AI in human resources (HR) can foster inclusivity and diversity for Black women in the tech workforce. Despite numerous diversity initiatives, Black women account for less than 2% of the US tech workforce, symbolizing a persistent challenge. Furthermore, AI often perpetuates structural biases, magnifying workforce inequities. This dissertation employs intersectionality, responsible innovation, and algorithmic bias theories to amplify the voices of Black women. It poses three critical questions: 1) How have Black women's HR experiences influenced diversity issues in the tech industry? 2) How is AI in HR developed considering the experiences of Black women? 3) What measures can enhance the role of AI in HR to promote diversity without deepening inequalities? Key findings reveal that current HR practices do not adequately serve Black women, driven by competing corporate priorities. Solutions should concentrate on recruiting, developing, promoting, and retaining Black women. Black women acknowledge the potential of AI to either reinforce or mitigate biases, yet they express apprehension about the development and implementation of AI in HR, which often lacks Black women's input. For AI to facilitate positive diversity results, companies must actively involve Black women in its development. This entails understanding the problems Black women face, using insights to design AI that addresses these issues and supports Black women's success, and engaging Black women in the development and assessment of AI implementations in HR, thereby enhancing accountability for diversity outcomes.

This is an ethnographic study of how curanderas (healers), physicians, scientists, people who use drugs and health advocates participate in emergent forms of addiction science, recovery medicine, and care. Across archives, participant observation, and interviews, data was derived from field notes and conversations in and about institutions of drug science and recovery medicine, contested socio-technical landscapes, and sites of drug advocacy. Focusing on the data from these sites and relevant emergent artifacts from that data, this dissertation recounts case studies focusing on three well-meaning public health interventions for substance use disorders (SUDs) and related harms in New Mexico over the last 50 years including: (1) treatment provisioning of the biomedical technologies methadone, buprenorphine and naloxone for opioid use disorder and related overdose prevention in the context of the harm reduction movement; (2) neuroscience solutionism for fetal alcohol spectrum disorder and reproductive justice; and (3) safe-use drug supply, emancipatory technoscience, and economic development in the context of 1960s-1970s Chicano movement. Recovery Futures offers a situated, yet partial contemporary history of drug recovery science and addiction medicine, one grounded in social movements, culture, power, state-building, and biomedicine. I suggest that biotechnologies of SUDs intervention emerged as a core, but troubled, site of innovation and that there are social and political incongruencies of modernizing drug recovery science and medicine as a both a state-building project and citizen science project that present challenges to doing medicine and science in postcolonial contexts.

This research interconnects three case studies to examine survivability as a framework through which to explore historic, current, and future collaborations in the face of existential threats, social-ecological-technical uncertainty, and indeterminate futures. Leveraging archival research, document analysis, and ethnographic field work, this study focuses on artist Georgia O’Keeffe’s mid-20th-century construction of a nuclear fallout shelter, the COVID Tracking Project’s response work in the first year of the Coronavirus Disease 2019 (COVID-19) pandemic, and three decades of future-facing scientific research performed at Biosphere 2. These cases demonstrate multidisciplinary collaborations across individual, organizational, and institutional configurations at local, national, and international scales in threat contexts spanning nuclear weapons, pandemics, and increasing climate catastrophe. Within each of the three cases, I examine protagonists’ collaborations within knowledge systems, their navigation of scientific disciplinary boundaries, their acknowledgement and negotiation of credibility and expertise, and how their engagements with these systems impact individual and collective survivability. By combining complex adaptive systems (CAS) framings with Science and Technology Studies concepts, I explore ways in which transformations of hierarchy and epistemological boundaries impact, and particularly increase, social-ecological-technical systems (SETS) survivability. Including notions of who and what systems deem worthy of protection, credibility, expertise and agency, imaginations, and how concepts of systems survivability operate, this work builds a conceptual scaffolding to better understand the dynamic workings of quests for survival in the 21st century.

Northeastern Arizona has experienced a recent increase in helium extraction activity. This qualitative case study articulates and explores various sociotechnical imaginaries – or, collectively produced social justifications for technological decisions and systems – that inform this new stage of underground helium extraction. Leveraging two years of interviews, document analysis, and participant observations to understand and interrogate the political and cultural origins of perceptions around helium extraction, I examined how these imaginaries and associated power dynamics influenced communication within and between stakeholder groups. In order to mitigate the power differentials between stakeholder groups, and put these imaginaries in conversation with each other, I led the development of a series of short videos that explain controversial technoscientific concepts from this research. These videos were produced in continuous collaboration with multiple disparate stakeholders, including activists, regulators, and industry members, in order to create a space for a productive conversation and reflection to explore tensions between conflicting points of view between stakeholders. This iterative work used the imaginaries of helium extraction in Arizona to produce a space for collective deliberation that can result in negotiated shared knowledge through brokered dialogue amongst these disparate groups and their competing visions of Arizona’s helium futures.

Software systems can exacerbate and cause contemporary social inequities. As such, scholars and activists have scrutinized sociotechnical systems like those used in facial recognition technology or predictive policing using the frameworks of algorithmic bias and dataset bias. However, these conversations are incomplete without study of data models: the structural, epistemological, and technical frameworks that shape data. In Modeling Power: Data Models and the Production of Social Inequality, I elucidate the connections between relational data modeling techniques and manifestations of systems of power in the United States, specifically white supremacy and cisgender normativity. This project has three distinct parts. First, I historicize early publications by E. F. Codd, Peter Chen, Miles Smith & Diane Smith, and J. R. Abrial to demonstrate that now-taken-for-granted data modeling techniques were products of their social and technical moments and, as such, reinforced dominant systems of power. I further connect database reification techniques to contemporary racial analyses of reification via the work of Cheryl Harris. Second, I reverse engineer Android applications (with Jadx and apktool) to uncover the relational data models within. I analyze DAO annotations, create entity-relationship diagrams, and then examine those resultant models, again linking them back to systems of race and gender power. I craft a method for performing a reverse engineering investigation within a specific sociotechnical context -- a situated analysis of the contextual epistemological frames embedded within relational paradigms. Finally, I develop a relational data model that integrates insights from the project’s reverse and historical engineering phases. In my speculative engineering process, I suggest that the temporality of modern digital computing is incommensurate with the temporality of modern transgender lives. Following this, I speculate and build a trans-inclusive data model that demonstrates uses of reification to actively subvert systems of racialized and gendered power. By promoting aspects of social identity to first-order objects within a data model, I show that additional “intellectual manageability” is possible through reification. Through each part, I argue that contemporary approaches to the social impacts of software systems incomplete without data models. Data models structure algorithmic opportunities. As algorithms continue to reinforce systems of inequality, data models provide opportunities for intervention and subversion.

Some say that science fiction becomes science. If science fiction eventually becomes science and technology, then US-American science and technology surrounding robots are rooted in white supremacy. Scholarship has previously highlighted the way that films and stories about robots are exclusionary towards Black people and persons of color. These texts, while aptly making the connection between race, Blackness, and technology, do not sufficiently address the embedded design of anti-Blackness in cultural artifacts in the early twentieth century and the anti-Black logics that, to this day, continue to inform how stories about robots are told. Further, these analyses do not consider the connection between cultural artifacts and the material development of emerging technologies; how these embedded racist narratives drive and shape how the technologies are then constructed. In this dissertation, I aim to link how anti-Black scientific popular culture has informed academic scholarship and engineering related to robots in the United States. Stories are an inherently spatial project. Stories about robots are a spatial project intended to create “Cartographies of Subordination.” I contend from 1922 to 1942, US-American robots were mapped into and onto the world; in just twenty short years, I argue a Cartography of Subordination was established. I apply a spatial lens to critique the impact of embedding stories about robots with anti-Blackness. These stories would develop into narratives with material consequences and maintain lasting ties and allegiance to a world invested in white supremacy. I outline how popular culture and stories are transfigured into narratives that have a direct impact on how futures are built. I expose the loop between popular culture and scholarship to unmask how research and development in robotics are based on white-informed futures. My dissertation makes an original geographical contribution to the fields of Human and Cultural Geography by asserting that narrative and popular culture about robots serves to remake Cartographies of Subordination in both science fiction and science and technology broadly. If science fiction has the potential to become real scientific outcomes, I connect culture, geography, and legacies of power in an otherwise overlooked space.

Technology and society co-exist, influencing each other simultaneously and iteratively, in ways that are sufficiently interdependent that it can be hard to see where one ends and the other begins. A set of sociotechnical relations exist between and across society and technologies that structure the ways that people live and work. What happens to sociotechnical relations when technologies are introduced or changed? In this dissertation, I argue that key parts of the processes that link technological and social change occur in a liminal space between the invention of new technologies and their widespread adoption and integration in society. In this space, engineers, businesses, and users of new technologies imagine, explore, develop, and test new ways of weaving together technology and society in novel sociotechnical arrangements. I call this space between invention and adoption a testbed, which I theorize as an early phase of technological deployment where outcomes are explored and tested, and sociotechnical assemblages are imagined, assembled, evaluated, and stabilized. I argue that the testbed, which is often delimited in both time and location, should be understood, interrogated, and governed appropriately to anticipate and examine the possibilities of social disruption inherent in technological change and to design the relationships between technology and society to improve sociotechnical outcomes. To understand the testbed, I engage in a case study of the Arizona public autonomous vehicle testbed, leveraging a multi-method approach that includes public observations, interviews, a survey, and content analyses. Through this work, I analyze diverse aspects of the testbed and articulate how the work of testbed actors imagines, assembles, tests, and stabilizes sociotechnical assemblages and futures. The dissertation builds on the insights gained from this investigation to evaluate the testbed and develop recommendations about assessing the space between technology invention and widespread adoption. Ultimately, this dissertation concludes that testbeds are key places where futures get made and so should be given greater attention by theorists of innovation and by societies confronting the societal and ethical challenges posed by new technologies.