CyFer examines the cybersecurity, privacy, bias and trust in female-oriented technologies (FemTech) focusing on fertility tracking apps and IoT devices.
Fertility apps have millions of users and IoT devices are starting to boom ($50 billion by 2025). These technologies gain user-entered data and take body measurements via sensors. By collecting a vast amount of data and processing them through advanced algorithms e.g. AI, these technologies assist in managing reproductive and sexual health, and give scientists more insight about people’s bodies.
However, there is a lack of clarity in the law (e.g. GDPR) and the industry practice in relation to this extremely sensitive data on different levels i.e. user consent, third-party sharing, and algorithmic bias which may lead to malicious purposes. There is evidence that the main audience of these products (women) have been historically discriminated by algorithms (e.g. AI).
The CyFer project looks to build on the research team’s previous work that demonstrated how the majority of fertility apps (some associated with IoT devices) start tracking the user right after the app is open and before any user consent, and how new sensors (e.g. on IoT devices) can put users at serious risk, yet the user perception is far less than the actual risks.
The CyFer project looks to achieve its aims by (1) evaluating security and privacy of fertility technologies, (2) investigating user perception and practice and (3) studying socio-technical bias and trust in data, algorithms and AI systems.