Open learning analytics (OLA) is a new research field focusing to create an open platform for integration of heterogeneous learning environments. The central notion in OLA is openness, and it relates to architectures, processes, access, and datasets. Learning analytics (LA) usually employs artificial intelligence (AI) technologies and machine learning (ML) algorithms to provide information and predictions, thus enhancing learning experience. AI-based systems provide many benefits, but their implementation raises ethical concerns due to wide range of possible negative consequences. OLA approach amplifies ethical concerns related to AI-based systems, such as privacy, transparency, bias, fairness, etc. In this paper we discuss a comprehensive list of ethical issues in OLA along with mitigations procedures.