Study title

This project aimed to quantitatively understand citizens' attitudes to Emotional AI via national surveys (as described in point 6 "Project Description", see above). We developed a demographically representative survey to gauge citizen attitudes to emotion capture technologies in cities in the UK. The survey introduces the overall topic of emotion profiling with the phrase: ‘We would now like to ask your opinion on use of technologies that try to measure and understand emotions (e.g., through computer analysis of social media posts, facial expression, voice, heart rate, gesture, and other data about the body). Closed-ended questions allowed then to explore 10 different use cases (38 questions in total): security, policing, communications, political campaigning, health, transport, education, toys and robots. For each case, positive and negative themes were tested, by grounding each question in an applied use case. In total, nine themes were explored, (although not across all the use cases to minimise survey fatigue).CONTEXT Emotional AI (EAI) technologies sense, learn and interact with citizens' emotions, moods, attention and intentions. Using weak and narrow rather than strong AI, machines read and react to emotion via text, images, voice, computer vision and biometric sensing. Concurrently, life in cities is increasingly technologically mediated. Data-driven sensors, actuators, robots and pervasive networking are changing how citizens experience cities, but not always for the better. Citizen needs and perspectives are often ancillary in emerging smart city deployments, resulting in mistrust in new civic infrastructure and its management (e.g. Alphabet's Sidewalk Labs). We need to avoid these issues repeating as EAI is rolled out in cities. Reading the body is an increasingly prevalent concern, as recent pushback against facial detection and recognition technologies demonstrates. EAI is an extension of this, and as it becomes normalised across the next decade we...