A Fuzzy Logic-Based Method for Incorporating Ethics in the Internet of Things

IoT is expected to have far-reaching consequences on society due to a wide spectrum of applications like smart healthcare, smart transportation, smart agriculture, smart home, etc. However, ethical considerations of AI-enabled smart devices have not been duly considered from a design perspective. In this paper, the authors propose a novel fuzzy logic-based method to incorporate ethics within smart things of IoT. Ethical considerations relevant to a machine context are represented in terms of fuzzy ethics variables (FEVs) and ethics rules. For each ethics rule, a value called scaled ethics value (SEV) is used to indicate its ethical desirability. In order to model flexibility in ethical response, the authors employ the concept of ethics modes that selectively allow scenarios depending on the value of SEV. The method offers a viable mechanism for smart devices to imbue ethical sensitivity that can pave the way for a technology society amenable to human ethics. However, the method does not account for varying ethics, as such incorporating learning mechanisms represent a promising research direction.