Workshop Proceedings of the 15th International AAAI Conference on Web and Social Media
Workshop: Mining Actionable Insights from Social Networks: Special Edition on Healthcare Social AnalyticsDOI: 10.36190/2021.72
Driver monitoring is expected to contribute greatly to safety in nascent smart cities, also in complex, mixed-traffic scenarios with autonomous vehicles (AVs), vulnerable road users (VRUs), and manually driven vehicles. Until now, one focus has been on detecting bio signals during the relatively short time when a person is inside a vehicle; but, life outside of the vehicle can also affect driving. For example, loneliness, depression, and sleep-deprivation, which might be difficult to detect in time, can increase the risk of accidents-raising possibilities for new and alternative intervention strategies. Thus, the current conceptual paper explores one idea for how continuous care could be provided to improve drivers' mental states; in particular, the idea of a "robot" that could positively affect a driver's health through interactions supported by social media mining on Facebook. A speculative design approach is used to present some potential challenges and solutions in regard to a robot's interaction strategy, user modeling, and ethics. For example, to address how to generate appropriate robot activities and mitigate the risk of damage to the driver, a hybrid neuro-symbolic recognition strategy leveraging stereotypical and self-disclosed information is described. Thereby, the aim of this conceptual paper is to navigate through some "memories" of one possible future, toward stimulating ideation and discussion within the increasingly vital area of safety in smart cities.