Ethics and Explainability in Ai-driven Cmc Decisions
Year: 2025
Type: article
Abstract: AI decision-making process, especially within CMC systems, it is paramount to consider ethical and explicableaspects for regulated applications. This study examines the significance of ethics and explainability in AI-drivenCMC decisions by assessing governance frameworks that promote model validation, bias control, and auditability.We look at how XAI methods increase user confidence, enhance decision transparency, and ensure regulatorycompliance. The research leverages recent advancements in ethical AI models, bias mitigation techniques, andgovernance frameworks to ensure the safe implementation of AI systems within cybersecurity, healthcare, andfinancial risk analysis domains. Additionally, it touches on the challenges of introspection, interpretability, andbias elimination in opaque models as well as related regulatory issues and best practices to combat biases.Ultimately, there is a need to pay attention to the ethics and explainability of AI as design features to createtrustworthy CMC.
Author: Pawankumar Suresh
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7082154454
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