The Key Concepts of Ethics of Artificial Intelligence - A Keyword based Systematic Mapping Study

Core ethical concepts in AI remain fragmented: The study identified 37 recurring keywords across 83 papers, suggesting that while the AI ethics field is active, there is no unified vocabulary or consensus on fundamental concepts—making it difficult to translate ethical principles into consistent practical implementation.

Philosophical frameworks are essential for implementation: The research emphasizes that philosophical conceptualization must precede practical implementation of ethics in AI systems, indicating that abstract ethical thinking is a necessary foundation before engineers and developers can build responsible AI into actual products.

The field needs clearer terminology to move forward: By conducting a systematic keyword analysis of 1,062 papers, the authors highlight that establishing shared definitions and language around AI ethics concepts is a critical first step—without this clarity, different stakeholders may be talking past each other when discussing responsible AI.

Values embedded in AI systems require deliberate attention: The study underscores that autonomous systems and AI already carry values within them, and these are not neutral—suggesting that organizations building AI cannot avoid making ethical choices and must consciously decide what values their systems will reflect.