The rapid development of advanced technologies has resulted in corresponding concerns about potential impacts on privacy. This is also true in the realm of quality of life technology, which involves monitoring, collecting, and transmitting data on individual-level behavior. Privacy concerns are seen as potential barriers to adoption and/or effectiveness of quality of life technology. This project is exploring various dimensions of privacy in the QoLT context with the ultimate goal of informing design of Center technologies to minimize potential privacy concerns.
The project has important implications for all qolt systems and research thrusts. Privacy concerns represent a fundamental barrier to adoption and effectiveness of QoLT in ultimately enhancing user independence and quality of life. Understanding the dynamics of privacy perceptions and behavior will increase the likelihood of achieving Center goals. Major barriers include lack of input from potential users and stakeholders in the design of QoLT with a corresponding lack of interaction between engineers and users early in the design process. We have employed both large-sample surveys of potential users and stakeholder-engineer focus groups and qualitative methods.
National surveys have consistently revealed public concern about the potential privacy impact of computers and the internet, and high-tech surveillance, tracking, and monitoring systems. There is a large and expanding literature on end-user privacy in human-computer interaction (HCI) and computer-supported cooperative work (CSCW) settings, and designers of such systems are being encouraged to explicitly consider privacy in initial development. The development of nano-technology in the form of invisible tags, sensors, and radio frequency identification (RFID) chips has also raised privacy concerns, which are being investigated. Empirical evidence on privacy concerns among users of quality of life technology is limited, with most studies involving small samples and qualitative methods. Our work extends previous work by exploring privacy in a variety of QoLT applications and potential user populations using both qualitative and quantitative methods.