INVASIVE YET INEVITABLE? PRIVACY NORMALIZATION TRENDS IN EMERGING TECHNOLOGY

  • Sejin Paik Boston University, United States of America
  • Kate K. Mays Boston University, United States of America
  • Rebecca F. Giovannetti Boston University, United States of America
  • James E. Katz Boston University, United States of America
Keywords: Facial recognition, biometrics, privacy, surveillance, normalization

Abstract

In the last few years, smart security and physical identification technologies have grown exponentially; people are increasingly installing smart video devices to monitor their homes and buying DNA kits to collect and analyze their genetics. As the number of users and profits of these businesses increase, so too does the potential for privacy violations and exploitation. To explore these dynamics of privacy in emerging technology, we conducted a U.S. nationally representative survey (N=1,587) and asked respondents for their perceptions of a number of emerging technologies such as facial recognition, DNA collection and biometrics monitoring. We also measured individual-level traits that have been found to influence technology acceptance. The results show that the actor wielding the technology matters for people’s acceptance. Respondents were overall more comfortable with public officials and airlines using more invasive technologies to guarantee people’s safety, as compared to private companies or non-profits using data for research. When keeping the actor constant across privacy technologies, there was an overwhelming preference for less invasive means of privacy data sharing. These findings indicate how the concept of normalization, social context and agents of control play a critical role in the way people accept emerging technology into their lives.

Published
2020-10-05
How to Cite
Paik, S., Mays, K. K., Giovannetti, R. F., & Katz, J. E. (2020). INVASIVE YET INEVITABLE? PRIVACY NORMALIZATION TRENDS IN EMERGING TECHNOLOGY. AoIR Selected Papers of Internet Research, 2020. https://doi.org/10.5210/spir.v2020i0.11300
Section
Papers P