Author: Dr. Aditi Sharma, Mr. Rohan Mehta.
Abstract: Artificial Intelligence (AI) systems are transforming industries across the globe, yet the complexity and unpredictability inherent in AI algorithms pose significant challenges to software quality assurance (SQA). This paper presents a comprehensive exploration of SQA practices tailored for AI systems, highlighting the need for rigorous validation, transparency, and ethical considerations. The study outlines key methodologies, evaluation metrics, and process models to ensure AI systems meet performance, reliability, and fairness standards. Special emphasis is placed on explainable AI, data quality, and continuous monitoring in deployment phases.
Keywords: Software Quality Assurance, Artificial Intelligence, Explainable AI, Validation, Testing, Ethical AI
Full Issue
| View or download the full issue | PDF 21-25 |