Blind spots in AI ethics

Abstract This paper critically discusses blind spots in AI ethics. ethics discourses typically stick to a certain set of topics concerning principles evolving mainly around explainability, fairness, and privacy. All these can be framed way that enables their operationalization by technical means. However, this requires stripping down the multidimensionality very complex social constructs something is idealized, measurable, calculable. Consequently, rather conservative, mainstream notions mentioned are conveyed, whereas critical research, alternative perspectives, non-ideal approaches largely neglected. Hence, one part considers specific regarding focusses on. The other part, then, hold significant ethical importance but hardly or not discussed at all Here, focuses on negative externalities systems, exemplarily discussing casualization clickwork, ethics’ strict anthropocentrism, AI’s environmental impact. Ultimately, intended commentary ongoing development field It makes case for rediscovery strength field, namely its sensitivity suffering harms caused connected technologies.