Identifying and Evaluating Ethical and Legal Determinants of Artificial Intelligence: An ISM-MICMAC Approach
The proliferation of Artificial Intelligence (AI) technologies has transformed numerous industries, providing unprecedented efficiency and innovation. Nevertheless, this rapid progress has prompted substantial ethical and legal concerns that necessitate cautious contemplation. In the context of artificial intelligence systems becoming more prevalent in daily life, concerns about privacy, bias, accountability, transparency, and societal impact have arisen. This paper uses the ISM-MICMAC approach to systematically examine and establish the interdependence of determinants influencing AI's ethical and legal practices. Identifying and evaluating these factors creates a structured model to illuminate their complex relationships. According to the study, legal compliance and regulations are the most important determinants, having the greatest impact on other ethical and legal factors. Furthermore, the MICMAC analysis classifies these determinants into autonomous, dependent, linkage, and independent clusters based on their driving and reliance capabilities. The findings underscore the critical importance of prioritizing legal compliance and regulations in enhancing ethical and legal AI practices. The developed model provides valuable insights for decision-makers, aiding in the anticipation of crucial ethical and legal considerations to foster responsible AI development and usage. This systematic approach enhances understanding of AI's ethical and legal implications, promoting the development of ethical and legally compliant AI practices across various fields.
Authors
- Mohnish Kumar
- Manish Gupta (ORCID: https://orcid.org/0000-0002-2843-3110)
- Manmohan Bansal
- Somesh Sharma
- Ashish Saxena (ORCID: https://orcid.org/0000-0003-2383-4617)
- Anu Singh (ORCID: https://orcid.org/0009-0009-5396-8625)
Institutions
- Invertis University (IN)
- IFTM University (IN)
- Graphic Era University (IN)
Publication Details
- Published
- 2025-08-04
- DOI
- https://doi.org/10.1109/icscsa66339.2025.11170858
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00