Smart Home Security Systems and Women’s Privacy in Patriarchal Societies
Dr. Hope Chidziwisano
Presidential Postdoctoral Fellow
Human-Computer Interaction Institute
Carnegie Mellon University
Smart home technologies have significantly contributed to the design of new applications that improve people’s domestic lives. Even though homes are not the same across the globe, human-computer interaction (HCI) research on smart home technologies overwhelmingly take place in industrialized countries. Despite this, prior research suggests that the introduction of smart home security systems in sub-Saharan African homes can perpetuate patriarchal attitudes and exacerbate the privacy challenges women face. In this talk, Hope will present his research about smart home security technologies and women’s privacy in patriarchal societies. Hope will focus on the unexpected ways patriarchs use these technologies and women’s reflections on using sensor-based technologies to support domestic activities. His work presents opportunities for designing personal privacy-aware smart home technologies for patriarchal societies. Further, his approach demonstrates how the unintended consequences of using technology can be understood before the deployment of any artifact. Hope’s work expands on the existing discussion about gender and technology use by making visible marginalized women’s perspectives on designing smart home security systems for their context.
Bio: George Hope Chidziwisano is a Presidential Postdoctoral Fellow in the Human Computer Interaction Institute at Carnegie Mellon University. His research focuses on designing sensing technologies for resource constrained areas. More specifically, he conducts design-oriented studies in the Global South, where he collaborates with local technicians and families to design, develop, and deploy novel sensing technologies that have the potential to solve some of the challenges facing homes in Sub-Saharan Africa. Hope’s research has received recognition from Google Research and ACM COMPASS. Hope was a fellow in the Data Science for Social Good program. He used his expertise in machine learning, natural language processing and deep learning to contribute to a project on identifying disinformation in online news articles. Hope has also participated in the Global Innovation Exchange program where he practiced a variety of human-centered design methods to develop novel sensing techniques, user-friendly interfaces, and cutting-edge computer technologies. Before joining CMU, Hope completed his Ph.D and M.A. in Information and Media at Michigan State University. Hope completed his undergraduate studies in Computer Science and Physics at the University of Malawi.