Testing artificial intelligence- and machine learning-based systems presents two key challenges. First, the same input can trigger different responses as the system learns and adapts to new conditions. Second, it tends to be difficult to determine exactly what the correct response of the system should be. Such system characteristics make test scenarios difficult to set up and reproduce and can cause us to lose confidence in test results. Yury Makedonov will explain how to test AI/ML-based systems by combining black box and white box testing techniques. His "gray box" testing approach...
Yury Makedonov
Test Manager
Accenture
Yury Makedonov was trained as a researcher and worked in a research and development institution dealing with composite materials. He has a Ph.D. degree in physics and math, though he is not a rocket scientist anymore; now he is using his skills and knowledge to improve software quality. Yury has more than twenty years of testing experience, from small startups to large companies and government organizations, and recently has been working as a QA manager, test manager, and consultant.