Axiology and the Evolution of Ethics in the Age of AI: Integrating Ethical Theories via Multiple-Criteria Decision Analysis

The fast advancement of artificial intelligence presents ethical challenges that exceed the scope of traditional moral theories. This paper proposes a value-centered framework for AI ethics grounded in axiology, which distinguishes intrinsic values like dignity and fairness from instrumental ones such as accuracy and efficiency. This distinction supports ethical pluralism and contextual sensitivity. Using Multi-Criteria Decision Analysis (MCDA), the framework translates values into structured evaluations, enabling transparent trade-offs. A healthcare case study illustrates how ethical outcomes vary across physician, patient, and public health perspectives. The results highlight the limitations of single-theory approaches and emphasize the need for adaptable models that reflect diverse stakeholder values. By linking philosophical inquiry with governance initiatives like Responsible Artificial Intelligence (AI) and Digital Humanism, the framework offers actionable design criteria for inclusive and context-aware AI development.

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Publication Details

Published
2025-11-06
DOI
https://doi.org/10.3390/proceedings2025126017
Citations
1
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
2.37
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article

Axiology and the Evolution of Ethics in the Age of AI: Integrating Ethical Theories via Multiple-Criteria Decision Analysis

Gordana Dodig-Crnković, Fei Sun, Damir Isovic
1 citations
Ethics and Social Impacts of AI
2.37
article

Axiology and the Evolution of Ethics in the Age of AI: Integrating Ethical Theories via Multiple-Criteria Decision Analysis

Gordana Dodig-Crnković, Fei Sun, Damir Isovic
article en
1 citations

Abstract

The fast advancement of artificial intelligence presents ethical challenges that exceed the scope of traditional moral theories. This paper proposes a value-centered framework for AI ethics grounded in axiology, which distinguishes intrinsic values like dignity and fairness from instrumental ones such as accuracy and efficiency. This distinction supports ethical pluralism and contextual sensitivity. Using Multi-Criteria Decision Analysis (MCDA), the framework translates values into structured evaluations, enabling transparent trade-offs. A healthcare case study illustrates how ethical outcomes vary across physician, patient, and public health perspectives. The results highlight the limitations of single-theory approaches and emphasize the need for adaptable models that reflect diverse stakeholder values. By linking philosophical inquiry with governance initiatives like Responsible Artificial Intelligence (AI) and Digital Humanism, the framework offers actionable design criteria for inclusive and context-aware AI development.

Mälardalen University (SE), Chalmers University of Technology (SE), Mälardalen University (SE)
Openalex Percentile: Top 8%
Ethics and Social Impacts of AI
2.37
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