A thorny issue in the research community, especially in the last decade, is the criteria for career advancement. In Romania and internationally, the indicators specific to academic promotion have been radically modified over the years. Their permanent refinement has been natural because research activity has changed radically, for instance, in terms of the way partnerships are formed and organised. Moreover, research data are made available and distributed openly, and the valorisation of scientific results in the form of articles and/or patents is actively encouraged. The world has continued to change, and the need to remove barriers to accessing research results is increasingly being questioned, with open science being a topic encouraged by policymakers. This new paradigm impacts the sphere of value indicators of research, and the subject of alt-metrics, i.e., alternative ways of measuring the quality of research, has also become a topic of interest. Many current proposals for considering research impact in line with the specificities of the contemporary world are derived from measuring interactions on social networks, which may or may not be dedicated to research activity. In this paper, we aim to explore the possibility of introducing sociometric alternatives that include indicators based on metrics specific to social networks in the context of evolving artificial intelligence (AI) technologies, which may influence the field in unethical ways. Therefore, we will identify and present how AI can influence alt-metrics, especially those based on social network activity such as Twitter, and explore the possibilities for detecting such actions, especially with bot identification.