[Paper Review] The Key Concepts of Ethics of Artificial Intelligence - A Keyword based Systematic Mapping Study

Ville Vakkuri, Pekka Abrahamsson|arXiv (Cornell University)|Sep 19, 2018

Ethics and Social Impacts of AI29 references4 citations

TL;DR

This study conducts a keyword-based systematic mapping study of 83 AI ethics papers to identify core concepts shaping the field. It identifies 37 recurring keywords, establishing a foundational conceptual framework to guide ethical AI implementation and future research.

ABSTRACT

The growing influence and decision-making capacities of Autonomous systems and Artificial Intelligence in our lives force us to consider the values embedded in these systems. But how ethics should be implemented into these systems? In this study, the solution is seen on philosophical conceptualization as a framework to form practical implementation model for ethics of AI. To take the first steps on conceptualization main concepts used on the field needs to be identified. A keyword based Systematic Mapping Study (SMS) on the keywords used in AI and ethics was conducted to help in identifying, defying and comparing main concepts used in current AI ethics discourse. Out of 1062 papers retrieved SMS discovered 37 re-occurring keywords in 83 academic papers. We suggest that the focus on finding keywords is the first step in guiding and providing direction for future research in the AI ethics field.

Motivation & Objective

• To identify and map the key concepts currently shaping the discourse in AI ethics.
• To address the challenge of ethical implementation in autonomous AI systems by analyzing recurring terminology.
• To provide a structured conceptual framework for future research in AI ethics.
• To support the development of practical implementation models by grounding them in philosophical and conceptual foundations.
• To guide researchers and practitioners toward a shared understanding of central themes in AI ethics literature.

Proposed method

• Conducted a systematic mapping study (SMS) on 1,062 papers retrieved from academic databases using keywords related to AI and ethics.
• Focused on identifying and analyzing re-occurring keywords across 83 relevant academic papers.
• Used keyword frequency and co-occurrence analysis to determine central themes in AI ethics discourse.
• Applied a thematic synthesis approach to group and define recurring keywords into coherent conceptual clusters.
• Evaluated the conceptual coherence and relevance of identified keywords to the broader field of AI ethics.
• Validated findings through iterative review and alignment with philosophical and technical foundations of AI ethics.

Experimental results

Research questions

• RQ1 What are the most frequently occurring keywords in the field of AI ethics?
• RQ2 How do these keywords cluster into conceptual themes within AI ethics discourse?
• RQ3 What core concepts are consistently emphasized across AI ethics literature?
• RQ4 How can keyword mapping contribute to the development of a conceptual framework for ethical AI?
• RQ5 What are the implications of identified keywords for future research and practical implementation in AI ethics?

Key findings

• The study identified 37 recurring keywords that are central to the discourse in AI ethics.
• Keywords such as 'autonomy', 'transparency', 'accountability', 'fairness', and 'privacy' emerged as dominant themes.
• The most frequently used keywords were primarily normative and value-laden, reflecting ethical concerns in AI systems.
• A clear conceptual structure was revealed, with keywords clustering into themes like human values, system behavior, and governance.
• The results suggest that ethical AI implementation must be grounded in well-defined philosophical and conceptual frameworks.
• The keyword mapping provides a foundation for future research, standardization, and the development of ethical AI guidelines.