Informatic Opacity: Biometric Facial Recognition and the Aesthetics and Politics of Defacement

Confronting the rapidly increasing, worldwide reliance on biometric technologies to surveil, manage, and police human beings, my dissertation Informatic Opacity: Biometric Facial Recognition and the Aesthetics and Politics of Defacement charts a series of queer, feminist, and anti-racist concepts and artworks that favor opacity as a means of political struggle against surveillance and capture technologies in the 21st century. Utilizing biometric facial recognition as a paradigmatic example, I argue that today's surveillance requires persons to be informatically visible in order to control them, and such visibility relies upon the production of technical standardizations of identification to operate globally, which most vehemently impact non- normative, minoritarian populations. Thus, as biometric technologies turn exposures of the face into sites of governance, activists and artists strive to make the face biometrically illegible and refuse the political recognition biometrics promises through acts of masking, escape, and imperceptibility. Although I specifically describe tactics of making the face unrecognizable as "defacement," I broadly theorize refusals to visually cohere to digital surveillance and capture technologies' gaze as "informatic opacity," an aesthetic-political theory and practice of anti- normativity at a global, technical scale whose goal is maintaining the autonomous determination of alterity and difference by evading the quantification, standardization, and regulation of identity imposed by biometrics and the state. My dissertation also features two artworks: Facial Weaponization Suite, a series of masks and public actions, and Face Cages, a critical, dystopic installation that investigates the abstract violence of biometric facial diagramming and analysis. I develop an interdisciplinary, practice-based method that pulls from contemporary art and aesthetic theory, media theory and surveillance studies, political and continental philosophy, queer and feminist theory, transgender studies, postcolonial theory, and critical race studies.

Qualitative analysis of the interdisciplinary interaction between data analysis specialists and novice clinical researchers.

BACKGROUND: The inherent complexity of statistical methods and clinical phenomena compel researchers with diverse domains of expertise to work in interdisciplinary teams, where none of them have a complete knowledge in their counterpart's field. As a result, knowledge exchange may often be characterized by miscommunication leading to misinterpretation, ultimately resulting in errors in research and even clinical practice. Though communication has a central role in interdisciplinary collaboration and since miscommunication can have a negative impact on research processes, to the best of our knowledge, no study has yet explored how data analysis specialists and clinical researchers communicate over time. METHODS/PRINCIPAL FINDINGS: We conducted qualitative analysis of encounters between clinical researchers and data analysis specialists (epidemiologist, clinical epidemiologist, and data mining specialist). These encounters were recorded and systematically analyzed using a grounded theory methodology for extraction of emerging themes, followed by data triangulation and analysis of negative cases for validation. A policy analysis was then performed using a system dynamics methodology looking for potential interventions to improve this process. Four major emerging themes were found. Definitions using lay language were frequently employed as a way to bridge the language gap between the specialties. Thought experiments presented a series of "what if" situations that helped clarify how the method or information from the other field would behave, if exposed to alternative situations, ultimately aiding in explaining their main objective. Metaphors and analogies were used to translate concepts across fields, from the unfamiliar to the familiar. Prolepsis was used to anticipate study outcomes, thus helping specialists understand the current context based on an understanding of their final goal. CONCLUSION/SIGNIFICANCE: The communication between clinical researchers and data analysis specialists presents multiple challenges that can lead to errors.