Abstract
With the rapid development of generative artificial intelligence technologies, we stand at a pivotal moment in the history of technology as these systems produce works once exclusive to human minds, compelling us to reconsider what it means to be human. Our interdisciplinary project examines how aligning generative AI with human values transforms human identity in healthcare contexts. Together, we aim to answer the question: How do conceptions of humans, bodies and healthcare ethics change in the age of AI? Contributing to interpretive research within the history of technology, our work draws on each author’s respective discipline to perform artifact analysis and close reading of 1) healthcare metrics framed by fairness and bias from ancient legal codes to modern algorithms (computer science), 2) embodied AI in surgical and assistive robotics (mechanical engineering), 3) AI-generated health responses to Internet queries (rhetoric), and 4) the ethical dimensions of AI diagnostics in healthcare (philosophy). Using findings from meta-analysis, we synthesize thematic patterns that traverse fairness, embodiment, ethical decision-making, and linguistic interpretation, illuminating how these domains interlock to shape evolving human–AI relations and draw attention to aligning AI with human values. These analyses offer an interdisciplinary understanding of essential elements of what it means to be human, whether that be the persistence of ethical codes or the error-laden qualities of texts, which are neither purely static nor purely ephemeral. These insights invite a reevaluation of technology’s role in shaping the boundaries of human agency and identity, informing future strategies for design, policy, and education.
Presenters
Julie Homchick CroweAssociate Professor, Communication and Media, Seattle University, Washington, United States Yen Lin Han
Professor, Mechanical Engineering, Seattle University, Washington, United States Matthew Rellihan
Wan Bae
Professor, Department of Computer Science, Seattle University, Washington, United States
Details
Presentation Type
Theme
2026 Special Focus—Human-Centered AI Transformations
KEYWORDS
Generative AI; Human Values; Interdisciplinary Research; Healthcare
