The implementation challenge: Embedding ethical reasoning in modern AI Systems
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| Title: | The implementation challenge: Embedding ethical reasoning in modern AI Systems |
|---|---|
| Authors: | Pelluru, Prem Sai |
| Source: | World Journal of Advanced Research and Reviews. 26:2011-2023 |
| Publisher Information: | GSC Online Press, 2025. |
| Publication Year: | 2025 |
| Subject Terms: | Ethical Decision-Making, Validation Frameworks, Machine Learning Implementation, System Architecture, Artificial Intelligence Ethics |
| Description: | This comprehensive article explores the critical challenges and solutions in embedding ethical reasoning capabilities within artificial intelligence systems. The article examines the multifaceted aspects of implementing ethical AI across various sectors, including healthcare, autonomous vehicles, and judicial systems. It explores core technical challenges in framework translation, data dependencies, and algorithmic transparency while evaluating different implementation approaches through rule-based systems and machine learning methods. The article delves into system architecture considerations, focusing on modularity and scalability, and presents detailed validation and testing frameworks. Additionally, it explores emerging technical directions, including quantum computing, neuromorphic approaches, and edge computing solutions, providing insights into the future landscape of ethical AI development. |
| Document Type: | Article |
| ISSN: | 2581-9615 |
| DOI: | 10.30574/wjarr.2025.26.1.1297 |
| DOI: | 10.5281/zenodo.17231486 |
| DOI: | 10.5281/zenodo.17231487 |
| Rights: | CC BY |
| Accession Number: | edsair.doi.dedup.....f60dd8b43db25c2dcab1fa4911e379bf |
| Database: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstract: | This comprehensive article explores the critical challenges and solutions in embedding ethical reasoning capabilities within artificial intelligence systems. The article examines the multifaceted aspects of implementing ethical AI across various sectors, including healthcare, autonomous vehicles, and judicial systems. It explores core technical challenges in framework translation, data dependencies, and algorithmic transparency while evaluating different implementation approaches through rule-based systems and machine learning methods. The article delves into system architecture considerations, focusing on modularity and scalability, and presents detailed validation and testing frameworks. Additionally, it explores emerging technical directions, including quantum computing, neuromorphic approaches, and edge computing solutions, providing insights into the future landscape of ethical AI development. |
|---|---|
| ISSN: | 25819615 |
| DOI: | 10.30574/wjarr.2025.26.1.1297 |